Amity University

By

Mr. Nishant Singhai

Management

Information System

Short for management information system or management information services, and pronounced

as separate letters, MIS refers broadly to a computer-based system that provides managers with

the tools for organizing, evaluating and efficiently running their departments. In order to provide

past, present and prediction information, an MIS can include software that helps in decision

making, data resources such as databases, the hardware resources of a system, decision support

systems, people management and project management applications, and any computerized

processes that enable the department to run efficiently.

Within companies and large organizations, the department responsible for computer systems is

sometimes called the MIS department. Other names for MIS include IS (Information Services) and

IT (Information Technology).

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Preface

Information Systems (IS) enables new approaches to improve efficiency and

efficacy of business models. This course will equip the students with

understanding of role, advantages and components of an Information System.

The objective of the course is to help students integrate their learning from

functional areas, decision making process in an organization and role of

Information Systems to have a vintage point in this competitive world.

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Updated Syllabus

Course Contents:

Module I Role of data and information, Organization structures, Business Process, Systems Approach and

introduction to Information Systems.

Module II Resources and components of Information System, integration and automation of business functions and

developing\ business models. Classification of Information System

Module III Architecture, development and maintenance of Information Systems, Centralized and Decentralized

Information Systems, Factors of success and failure, value and risk of IS.

Module IV Decision Making Process, Decision Support Systems, Models and approaches to DSS

Module V Introduction to Total Quality Management and Enterprise Resource Planning. ERP: role, advantages,

reasons of success and failure,

Module VI Financial Management Information Systems in Developing Countries by International Monetary Fund

Text & References:

Text:

MIS: Managing the digital firm, Kenneth C.Landon, Jane P. Landon, Pearson Education.

References:

Management Information Systems, Effy OZ, Thomson Leaning/ Vikas Publications

Management Information Systems, James A. O’Brein, Tata McGraw-Hill

Management Information System, W.S Jawadekar, Tata Mc Graw Hill Publication.

Management Information System, David Kroenke, Tata Mc Graw Hill Publication.

MIS: Management Perspective, D.P. Goyal, Macmillan Business Books.

MIS and Corporate Communications, Raj K. Wadwha, Jimmy Dawar, P. Bhaskara Rao, Kanishka

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Index

Module I - page no. 4 Role of data and information, Organization structures, Business Process, Systems Approach and introduction to Information Systems. Module II - page no. 35 Resources and components of Information System, integration and automation of business functions and developing\ business models. Classification of Information System Module III - page no. 61 Architecture, development and maintenance of Information Systems, Centralized and Decentralized Information Systems, Factors of success and failure, value and risk of IS. Module IV - page no. 77 Decision Making Process, Decision Support Systems, Models and approaches to DSS Module V - page no.118 Introduction to Total Quality Management and Enterprise Resource Planning. ERP: role, advantages, reasons of success and failure, Module VI - page no. 135 Financial Management Information Systems in Developing Countries by International Monetary Fund

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Module 1

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DATA

The term data means groups of information that represent the qualitative or

quantitative attributes of a variable or set of variables. Data (plural of "datum",

which is seldom used) are typically the results of measurements and can be the

basis of graphs, images, or observations of a set of variables. Data are often viewed

as the lowest level of abstraction from which information and knowledge are

derived. In discussions of problems in geometry, mathematics, engineering, and so

on, the terms givens and data are used interchangeably. Also, data is a

representation of a fact, figure, and idea. Such usage is the origin of data as a

concept in computer science: data are numbers, words, images, etc., accepted as

they stand. Data is now often treated as a singular mass noun in informal usage,

but usage in scientific publications shows a divide between the United

States and United Kingdom. In the United States the word data is sometimes used

in the singular, though scientists and science writers more often maintain the

traditional plural usage. Some major newspapers such as the New York Times use it

alternately in the singular or plural. In the New York Times the phrases "the survey

data are still being analyzed" and "the first year for which data is available" have

appeared on the same day. In scientific writing data is often treated as a plural, as

in These data do not support the conclusions, but many people now think of data

as a singular mass entity like information and use the singular in general usage.

British usage now widely accepts treating data as singular in standard

English, including everyday newspaper usage at least in non-scientific use. UK

scientific publishing still prefers treating it as a plural. Some UK university style

guides recommend using data for both singular and plural use and some

recommend treating it only as a singular in connection with computers.

Raw data refers to a collection of numbers, characters, images or other outputs

from devices to convert physical quantities into symbols, that are unprocessed.

Such data is typically further processed by a human or input into

a computer, stored and processed there, or transmitted (output) to another human

or computer (possibly through a data cable). Raw data is a relative term; data

processing commonly occurs by stages, and the "processed data" from one stage

may be considered the "raw data" of the next.

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Information

Information as a concept has many meanings, from everyday usage to technical

settings. The concept of information is closely related to notions of constraint,

communication, control, data, form, instruction, knowledge, meaning, mental

stimulus, pattern, perception, and representation.

The English word was apparently derived from the Latin accusative form

(informationem) of the nominative (informatio): this noun is in its turn derived

from the verb "informare" (to inform) in the sense of "to give form to the mind",

"to discipline", "instruct", "teach": "Men so wise should go and inform their

kings." (1330) Inform itself comes (via French) from the Latin verb informare, to

give form to, to form an idea of. Furthermore, Latin itself already contained the

word informatio meaning concept or idea, but the extent to which this may have

influenced the development of the word information in English is unclear.

Information is the state of a system of interest. Message is the information

materialized.

Information is a quality of a message from a sender to one or more receivers.

Information is always about something (size of a parameter, occurrence of an

event, value, ethics, etc). Viewed in this manner, information does not have to be

accurate; it may be a truth or a lie, or just the sound of a falling tree. Even a

disruptive noise used to inhibit the flow of communication and create

misunderstanding would in this view be a form of information. However, generally

speaking, if the amount of information in the received message increases, the

message is more accurate.

Even though information and data are often used interchangeably, they are actually

very different. Data is a set of unrelated information, and as such is of no use until

it is properly evaluated. Upon evaluation, once there is some significant relation

between data, and they show some relevance, then they are converted into

information. Now this same data can be used for different purposes. Thus, till the

data convey some information, they are not useful and therefore not information.

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Meaning of data, information and knowledge

The terms information and knowledge are frequently used for overlapping

concepts. The main difference is in the level of abstraction being considered. Data

is the lowest level of abstraction, information is the next level, and finally,

knowledge is the highest level among all three. Data on its own carries no

meaning. In order for data to become information, it must be interpreted and take

on a meaning. For example, the height of Mt. Everest is generally considered as

"data", a book on Mt. Everest geological characteristics may be considered as

"information", and a report containing practical information on the best way to

reach Mt. Everest's peak may be considered as "knowledge".

Information as a concept bears a diversity of meanings, from everyday usage to

technical settings. Generally speaking, the concept of information is closely related

to notions of constraint, communication, control, data, form, instruction,

knowledge, meaning, mental stimulus, pattern, perception, and representation.

It is people and computers who collect data and impose patterns on it. These

patterns are seen as information which can used to enhance knowledge. These

patterns can be interpreted as truth, and are authorized as aesthetic and ethical

criteria. Events that leave behind perceivable physical or virtual remains can be

traced back through data. Marks are no longer considered data once the link

between the mark and observation is broken. In other words, when an occurrence

leaves perceivable marks, those marks attain the status of data.

In many a case, the business organizations started as a one-man show but with the

passage of time, their size has increased manifold. Although the functions

performed are basically the same, the volume and complexity of operations have

increased geometrically. As With all growing companies, new products are

developed, Sales volume grows, the number of employees increased, factors

outside the company become increasingly complex, and the managerial problems

surrounding the operation of the organization generally expand more rapidly than

the company size. Communications channels are more difficult, authority must be

delegated and information needs expand. The increase in company size results in

the need for additional information collection, processing and distribution. It now

becomes necessary to handle many customer accounts, many production records,

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and many more interrelation- ships among functions. In addition, it becomes

necessary to assign people to supervise other people.

Before we come to our purpose to speak about MIS, we should give a general

outline what a company's or how we can describe a company. Other- wise we

would have problems to understand MIS, which is part of company.

Hence, large business organization, whether it has developed from a one man show

or otherwise, has to perform a lot of functions to achieve the objectives/ goals set

and in the process deploys lot of resources viz., men, material, machine money etc.

The systems concept is of immense use in understanding business organization and

their functions. We define a system as a group of elements either physical or non-

physical in nature that exhibits a set of interrelationship among them. The elements

of a system may interact with each other towards a common goal i.e., the system is

a goal (objective) seeking one. However, not all systems are goal seeking.

A business organization system consists of a group of people who process material

and informational resources towards a set of multiple common goals including an

economic profit for the business by performing financing, design, production and

marketing functions to achieve finished goods and their sale at a specified

minimum per year.

Business organizations are usually systems operating within larger systems

(industry or economy) and interact with their environment, hence they act as open

systems i.e., the individual business organizations are influenced by the changes in

the environment or industry. The company can be identified as an open system by

its individually small influence on its environment or vice versa. It reacts with its

environment in such a way as to improve its functioning, achievement or

probability of survival.

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Management Information Systems

Management information systems encompass a broad and complex topic. To make

this topic more manageable, boundaries will be defined. First, because of the vast

number of activities relating to management information systems, a total review is

not possible. Those discussed here is only a partial sampling of activities,

reflecting the author's viewpoint of the more common and interesting

developments. Likewise where there were multiple effects in a similar area of

development, only selected ones will be used to illustrate concepts. This is not to

imply one effort is more important than another. Also, the main focus of this paper

will be on information systems for use at the farm level and to some lesser extent

systems used to support researchers addressing farm level problems (e.g.,

simulation or optimization models, geographic information systems, etc.) and those

used to support agribusiness firms that supply goods and services to agricultural

producers and the supply chain beyond the production phase.

Secondly, there are several frameworks that can be used to define and describe

management information systems. More than one will be used to discuss important

concepts. Because more than one is used, it indicates the difficult of capturing the

key concepts of what is a management information system. Indeed, what is viewed

as an effective and useful management information system is one environment may

not be of use or value in another.

Lastly, the historical perspective of management information systems cannot be

ignored. This perspective gives a sense of how these systems have evolved, been

refined and adapted as new technologies have emerged, and how changing

economic conditions and other factors have influenced the use of information

systems.

Before discussing management information systems, some time-tested concepts

should be reviewed. Davis offers a commonly used concept in his distinction

between data and information. Davis defines data as raw facts, figures, objects, etc.

Information is used to make decisions. To transform data into information,

processing is needed and it must be done while considering the context of a

decision. We are often awash in data but lacking good information. However, the

success achieved in supplying information to decision makers is highly variable.

Barabba, expands this concept by also adding inference, knowledge and wisdom in

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his modification of Haechel's hierarchy which places wisdom at the highest level

and data at the lowest. As one move up the hierarchy, the value is increased and

volume decreased. Thus, as one acquires knowledge and wisdom the decision

making process is refined. Management information systems attempt to address all

levels of Haechel's hierarchy as well as convertingdata into information for the

decision maker. As both Barabba and Haechel argue, however, just supplying more

data and information may actually be making the decision making process more

difficult. Emphasis should be placed on increasing the value of information by

moving up Haechel's hierarchy.

Another important concept from Davis and Olsen is the value if information. They

note that ―in general, the value of information is the value of the change in decision

behavior caused by the information, less the cost of the information.‖ This

statement implies that information is normally not a free good. Furthermore, if it

does not change decisions to the better, it may have no value. Many assume that

investing in a ―better‖ management information system is a sound economic

decision. Since it is possible that the better system may not change decisions or the

cost of implementing the better system is high to the actual realized benefits, it

could be a bad investment. Also, since before the investment is made, it is hard to

predict the benefits and costs of the better system, the investment should be viewed

as one with risk associated with it.

Another approach for describing information systems is that proposed by Harsh

and colleagues. They define information as one of four types and all these types are

important component of a management information system. Furthermore, the

various types build upon and interact with each other. A common starting level is

Descriptive information. This information portrays the ―what is‖ condition of a

business, and it describes the state of the business at a specified point in time.

Descriptive information is very important to the business manager, because

without it, many problems would not be identified. Descriptive information

includes a variety of types of information including financial results, production

records, test results, product marketing, and maintenance records.

Descriptive information can also be used as inputs to secure other needed types of

information. For example, ―what is‖ information is needed for supplying restraints

in analyzing farm adjustment alternatives. It can also be used to identify problems

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other than the ―what is‖ condition. Descriptive information is necessary but not

completely sufficient in identifying and addressing farm management problems.

The second type of information is diagnostic information, this information portrays

this ―what is wrong‖ condition, where ―what is wrong‖ is measured as the disparity

between ―what is‖ and ―what ought to be.‖ This assessment of how things are

versus how they should be (a fact-value conflict) is probably our most common

management problem. Diagnostic information has two major uses. It can first be

used to define problems that develop in the business. Are production levels too

low? Is the rate earned on investment too low? These types of question cannot be

answered with descriptive information alone (such as with financial and production

records). A manager may often be well supplied with facts about his business, yet

be unable to recognize this type of problem. The manager must provide norms or

standards which, when compared with the facts for a particular business, will

reveal an area of concern. Once a problem has been identified, a manager may

choose an appropriate course of action for dealing with the problem (including

doing nothing). Corrective measures may be taken so as to better achieve the

manager’s goals. Several pitfalls are involved for managers in obtaining diagnostic

information. Adequate, reliable, descriptive information must be available along

with appropriate norms or standards for particular business situations. Information

is inadequate for problem solving if it does not fully describe both ―what is‖ and

―what ought to be.‖

As description is concerned with ―what is‖ and diagnostics with ‖what is wrong,‖

prediction is concerned with ―what if...?‖ Predictive information is generated from

an analysis of possible future events and is exceedingly valuable with ―desirable‖

outcomes. With predictive information, one either defines problems or avoids

problems in advance. Prediction also assists in analysis. When a problem is

recognized, a manager will analyze the situation and specify at least one alternative

(including doing nothing) to deal with it. Predictive information is needed by

managers to reduce the risk and uncertainty concerning technology, prices, climate,

institutions, and human relationships affecting the business. Such information is

vital in formulating production plans and examining related financial impacts.

Predictive information takes many forms. What are the expected prices next year?

What yields are anticipated? How much capital will be required to upgrade

production technologies? What would be the difference in expected returns in

switching from a livestock farm to a cropping farm? Management has long used

various budgeting techniques, simulation models, and other tools to evaluate

expected changes in the business.

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Without detracting from the importance of problem identification and analysis in

management, the crux of management tasks is decision making. For every problem

a manager faces, there is a ―right‖ course of action. However, the rightness of a

decision can seldom, if ever, be measured in absolute terms. The choice is

conditionally right, depending upon a farm manager’s knowledge, assumptions,

and conditions he wishes to impose on the decision. Prescriptive information is

directed toward answering the ―what should be done‖ question. Provision of this

information requires the utilization of the predictive information. Predictive

information by itself is not adequate for decision making. An evaluation of the

predicted outcomes together with the goals and values of the manger provides that

basis for making a decision. For example, suppose that a manager is considering a

new changing marketing alternative. The new alternative being considered has

higher ―predicted‖ returns but also has higher risks and requires more management

monitoring. The decision as to whether to change plans depends upon the

managers evaluation of the worth of additional income versus the commitment of

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additional time and higher risk. Thus, the goals and values of a farm manager will

ultimately enter into any decision.

A management information system (MIS) is a system or process that provides the

information necessary to manage an organization effectively. MIS and the

information it generates are generally considered essential components of prudent

and reasonable business decisions.

MIS is viewed and used at many levels by management. It should be supportive of

the institution's longer term strategic goals and objectives. To the other extreme it

is also those everyday financial accounting systems that are used to ensure basic

control is maintained over financial recordkeeping activities.

Financial accounting systems and subsystems are just one type of institutional

MIS. Financial accounting systems are an important functional element or part of

the total MIS structure. However, they are more narrowly focused on the internal

balancing of an institution's books to the general ledger and other financial

accounting subsystems. For example, accrual adjustments, reconciling and

correcting entries used to reconcile the financial systems to the general ledger are

not always immediately entered into other MIS systems.

Accordingly, although MIS and accounting reconcilement totals for related listings

and activities should be similar, they may not necessarily balance.

MIS in an INSTITUTION

An institution's MIS should be designed to achieve the following goals:

• Enhance communication among employees.

• Deliver complex material throughout the institution.

• Provide an objective system for recording and aggregating information.

• Reduce expenses related to labor-intensive manual activities.

• Support the organization's strategic goals and direction.

Because MIS supplies decision makers with facts, it supports and enhances the

overall decision making process. MIS also enhances job performance throughout

an institution. At the most senior levels, it provides the data and information to

help the board and management make strategic decisions. At other levels, MIS

provides the means through which the institution's activities are monitored and

information is distributed to management, employees, and customers.

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Effective MIS should ensure the appropriate presentation formats and time frames

required by operations and senior management are met. MIS can be maintained

and developed by either manual or automated systems or a combination of both. It

should always be sufficient to meet an institution's unique business goals and

objectives. The effective deliveries of an institution's products and services are

supported by the MIS. These systems should be accessible and useable at all

appropriate levels of the organization.

MIS is a critical component of the institution's overall risk management strategy.

MIS supports management's ability to perform such reviews. MIS should be used

to recognize, monitor, measure, limit, and manage risks. Risk management

involves four main elements:

• Policies or practices.

• Operational processes.

• Staff and management.

• Feedback devices.

Frequently, operational processes and feedback devices are intertwined and cannot

easily be viewed separately. The most efficient and useable MIS should be both

operational and informational. As such, management can use MIS to measure

performance, manage resources, and help an institution comply with regulatory

requirements. One example of this would be the managing and reporting of loans

to insiders. MIS can also be used by management to provide feedback on the

effectiveness of risk controls.

Controls are developed to support the proper management of risk through the

institution's policies or practices, operational processes, and the assignment of

duties and responsibilities to staff and managers.

Technology advances have increased both the availability and volume of

information management and the directors have available for both planning and

decision making. Correspondingly, technology also increases the potential for

inaccurate reporting and flawed decision making. Because data can be extracted

from many financial and transaction systems, appropriate control procedures must

be set up to ensure that information is correct and relevant. In addition, since MIS

often originates from multiple equipment platforms including mainframes,

minicomputers, and microcomputers, controls must ensure that systems on smaller

computers have processing controls that are as well defined and as effective as

those commonly found on the traditionally larger mainframe systems.

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MIS for Farm Management

The importance of management information systems to improve decision making

has long been understood by farm management economists. Financial and

production records have long been used by these economists as an instrument to

measure and evaluate the success of a farm business. However, when computer

technology became more widely available in the late 1950s and early 1960s, there

was an increased enthusiasm for information systems to enhance management

decision processes. At an IBM hosted conference, Ackerman, a respected farm

management economist, stated that:

―The advances that have taken place in calculating equipment and methods make it

possible to determine the relationship between ultimate yields, time of harvest and

climatic conditions during the growing season. Relationship between the

perspective and actual yields and changing prices can be established. With such

information at hand the farmer should be in a position to make a decision on his

prediction with a high degree of certainty at mid-season regarding his yield and

income at harvest time.‖

This statement, made in 1963, reflects the optimism that prevailed with respect to

information systems. Even though there was much enthusiasm related to these

early systems they basically concentrated on accounting activities and production

records. Examples include the TelFarm electronic accounting system at Michigan

State University and DHIA for dairy operations. These early systems relieved on

large mainframe computers with the data being sent to a central processing center

and the reports send back to the cooperating businesses. To put these early efforts

into a management information system framework, the one proposed by Alder is

useful. (See Figure ). They would be defined as data oriented systems with limited

data analysis capabilities beyond calculating typical ratios (e.g., return on assets,

milk per cow, etc.).

By the mid 1960s it became clear that the accounting systems were fairly effective

in supplying descriptive and diagnostic information but they lacked the capacity to

provide predictive and prescriptive information. Thus, a new approach was needed

– a method of doing forward planning or a management information system that

was more models oriented. Simulation models for improving management skills

and testing system interaction were developed. As an example, Kuhlmann, Giessen

University, developed a very robust and comprehensive whole farm simulation

model (SIMPLAN) that executed on a mainframe computer. This model was based

on systems modeling methods that could be used to analyze different production

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strategies of the farm business. To be used by managers, however, they often

demanded that the model developer work closely with them in using the model.

Types of Information Systems

Another important activity during this period was the ―Top-Farmer Workshops‖

developed by Purdue University. They used a workshop setting to run large linear-

programming models on mainframe computers (optimization models) to help crop

producers find more efficient and effective ways to operate their business.

As mainframe timeshare computers emerged in the mid-1960's, I became possible

to remotely access the computer with a terminal and execute software. Systems

such TelPlan developed by Michigan State University made it possible for

agricultural producers to run a farm related computer decision aids. Since this

machine was shared by many users, the cost for executing an agriculturally related

decision aid was relatively inexpensive and cost effective. These decision aids

included optimization models (e.g., least cost animal rations) budgeting and

simulation models, and other types of decision aids. These decision aids could be

accessed by agricultural advisor with remote computer terminals (e.g., Teletype

machine or a touch-tone telephone). These advisors used these computer models at

the farm or at their own office to provide advice to farm producers.

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These were exciting times with many people becoming involved in the

development, testing, refining, and implementation of information systems for

agriculture. Computer technology continued to advance at a rapid pace, new

communication systems were evolving and the application of this technology to

agriculture was very encouraging. Because of the rapid changes occurring, there

were international conferences held where much of the knowledge learned in

developing these systems was shared. One of the first of these was held in

Germany in the mid-1980s.

It was also clear from these early efforts that the data oriented systems where not

closely linked to the model oriented systems. Information for the data oriented

systems often did not match the data needed for the model oriented systems. For

example, a cash-flow projection model was not able to directly use financial data

contained in the accounting system. In most cases, the data had to be manually

extracted from the accounting system and re-entered into the planning model. This

was both a time consuming and error prone process.

Because of the lack of integration capabilities of various systems, they were devoid

of many of the desirable characteristics of an evolving concept describes as

decision support systems (DSS). These systems are also known as Executive

Support Systems, and Management Support System, and Process Oriented

Information Systems. The decision support system proposed by Sprague and

Watson (House, ed.) has as its major components a database, a modelbase, a

database/modelbase management system and a user interface (see Figure). The

database has information related to financial transactions, production information,

marketing records, the resource base, research data, weather data and so forth. It

includes data internally generated by the business (e.g., financial transactions and

production data) and external data (e.g., market prices). These data are stored in a

common structure such that it is easily accessible by other database packages as

well as the modelbase.

The modelbase component of the system has decision models that relate to

operational, tactical and strategic decisions. In addition, the modelbase is able to

link models together in order to solve larger and more complex problems,

particularly semi-structured problems. The database/modelbase management

system is the bridge between database and modelbase components. It has the

ability to extract data from the database and pass it to the modelbase and vice

versa. The user interface, one of the more critical features of the system, is used to

assist the decision maker in making more efficient and effective use of the system.

Lastly, for these systems to be effective in supporting management decision, the

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decision maker must have the skills and knowledge on how to correctly use these

systems to address the unique problem situation at hand.

Several follow-up international conferences were held to reflect these new

advances in management information systems. The first of these conferences

focused on decision support systems was held in Germany. This conference

discussed the virtues of these systems and the approach used to support decisions.

Several prototype systems being developed for agriculture were presented. From

these presentations, it was clear that the decision support systems approach had

many advantages but the implementation in agriculture was going to be somewhat

involved and complex because of the diversity of agricultural production systems.

Nevertheless, there was much optimism for the development of such systems.

Decision Support System

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A couple of years later, another conference were held in Germany that focused on

knowledge-based systems with a major emphasis on expert systems and to a lesser

extent optimum control methods and simulation models. Using Alter’s scheme to

describe information systems, for the most part these would be described as

suggestion models. It was interesting to note that the prototype knowledge-based

systems for the most part did not utilize the concepts of decisions support systems

which were the focus of the earlier conference. Perhaps this was related to the fact

that many of the applications were prototypes.

The international conference that followed in France focused on the low adaption

rate of management information systems. This was a topic of much discussion but

there were few conclusions reached except the systems with the highest adaption

rate were mainly data-oriented ones (e.g., accounting systems, field record

systems, anaimal production and health records, etc.) which provide mainly

descriptive and diagnostic information.

The international conferences that followed had varying themes. One of the major

themes was precision agriculture with several conferences held. These conferences

extolled the use of geographic information systems (GIS) in conjunction with

geographic positioning systems (GPS) to record and display data regarding

cropping operations (e.g., yields obtained) and to control production inputs (e.g.,

fertilizer levels). Other conference addressed the use of information systems to

more tightly control agriculture production such as those developed for greenhouse

businesses.

To briefly summarize the historical developments, there have been significant

efforts devoted to improving the management information systems from the early

computerized activities forty years earlier. The decision aids available have grown

in number and they are more sophisticated. There has been some movement toward

integration of the data oriented systems and the model oriented systems. An

examination of our current usage of management information systems, however,

suggests that we have not nearly harnessed the potential of the design concepts

contained modern management information systems.

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Traditional MIS have evolved to serve structured, functional, permanent

organizations. Project information systems more recently have emerged to serve

temporary, relatively short-lived, multi-functional projects. Project MIS, compared

to the various organizational MIS, must handle more diverse information and be

more predictive and integrative in nature over a longer time span. The result is that

project MIS are generally more difficult to implement, and their implementation

often reveals existing incompatibilities with and between the various

organizational MIS which provide information to project systems.

Specific product and project planning and control functions and tools are identified

in this paper, and the types and sources of incompatibilities are discussed.

Suggested methods of minimizing the problems are briefly presented.

The underlying thesis of this discussion is that a better understanding of the

differences and interfaces between project and organizational MIS will help to

resolve current problems and avoid future difficulties in the implementation of

information systems to serve operating project managers.

MIS IN GENERAL In this discussion, I refer to management information systems (MIS) as identifiable

sets of policies, models, procedures and files of information which operate to

record, manipulate, store, retrieve, process and display information useful in

managing some aspect of an organized enterprise. Such systems may depend only

on rather simple mechanical devices operated directly by human hands, such as

pencils, pens, ledgers, charts, and so on; or they may also depend on more complex

devices and machines, such as slide rules, calculators and electronic data

processing systems. They all seem to depend on paper to a great extent!

Perhaps Moses had the first MIS when he came down the mountain with the Ten

Commandments chiseled into stone tablets. At least today's reports carry more

information per pound, but they are certainly no lighter to carry than the stone

tablets of Moses' day.

The basic classes of primary management information

systems may be identified as follows:

• General management

• Financial

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• Logistics

• Business acquisition

• Resources

General management information systems are concerned with the overall,

integrative planning and direction of the total enterprise. They include methods of

generating, recording and processing information related to:

• Strategic objectives and goals

• Financial objectives

• Business, market and product plans to achieve the objectives

• Overall performance measurement and evaluation compared to objectives.

These general management information systems depend heavily on the financial

MIS, and to a lesser extent on all other types of MIS.

Financial management information systems are familiar to us all, and deal with

the basic element of resource that we all understand (at least to some extent):

Money. With these systems we are able to:

• Translate the strategic, market and product plans of the enterprise into the

common denominator of money.

• Plan, control and account for the production, distribution and inventory of money,

resulting from the basic operations of the enterprise.

• Analyze the basic operations in monetary terms.

This class includes systems for financial planning, budgeting, cash handling,

accounts and financial analysis.

Logistics management information systems enable us to plan, control and

account for the acquisition, inventory, processing, conversion, assembly and

distribution of goods and services -- the tangible repetitious transactions or work --

which generate the outflow and inflow of money. Systems within this class include

purchasing, work authorization and control, production and inventory planning and

control, and product distribution.

Business acquisition management information systems include procedures for

handling information related to markets, products, capabilities, competitors,

customers, proposals and selling, and orders (contracts or sales). In this class are

found marketing and sales systems and procedures, such as order booking,

processing and billing, collections and contract administration.

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Resources management information systems deal with the basic resources of a

company other than financial), including people, know-how, plant facilities, and

equipment. Included here are personnel information systems, as well as those

dealing with the acquisition and utilization of capital facilities, installed equipment

and other types of equipment and resources required to produce the goods and

services which are delivered or sold by the organization.

Project management information systems (PMIS) enable us to plan, schedule,

execute and control projects -- those complex, unique efforts which cut across

organizational and functional lines, and which must achieve the specified results at

a particular point in time and within a given cost of budget. Projects may be

viewed as temporary profit centers which subcontract most if not all of the actual

work required to complete them. The verb "to project" or to forecast or predict,

conveys the fundamental purpose of various related PMIS: to predict how the

project will come out, based on progress to date and current plans for the future.

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MIS FOR ORGANIZATIONS

An organizational chart is a diagram that shows the structure of

an organization and the relationships and relative ranks of its parts and

positions/jobs. The term is also used for similar diagrams, for example

ones showing the different elements of a field of knowledge or a group

of languages.

Organizations of all types -- business, industrial, institutional, governmental - are

structured and shaped to meet the needs of the primary purpose of each individual

organization. This structure invariably results in some form of hierarchy or

bureaucracy, segregating and dividing the various functions such as marketing,

manufacturing, engineering, and so on. The financial, logistics, business

acquisition and resources management information systems which we have today

are designed to serve the structural, hierarchical organization which has a certain

permanency associated with it. Financial budgets and reports are provided for

organizational sections, departments and divisions, for example. Production control

systems serve the manufacturing division and have nothing to do directly with

engineering. Information is provided to each functional manager concerning his

limited segment of the total operation as orders are obtained and fed into

production, and as the raw materials are purchased, processed and shipped to the

customers.

The organization structure, portrayed by the familiar pyramidal chart of boxes and

lines, forms a fairly stable skeleton on which most, perhaps all, of these

management information systems are based.

A Company can have different subsystems (departments). For a given company it

depends on its purpose, size and sometimes on his history which departments it

has. Each of these departments have different responsibilities and tasks.

The organization structure of an organization manufacturing paperboard cartons

for a wide variety of users and also paperboard used in the cartons is shown in Fig.

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The responsibilities of such of the functions should be clearly defined so as the

objectives/goals of the organization are achieved. Unless and until the objectives of

each of the function are identified properly, we shall not be in a position to

evaluate the achievements of each of the functions, their weak- nesses or strengths.

As an example, we can identify the responsibilities of marketing function as

followings:

i) Formulation of sales budget.

ii) The inventory of finished goods.

iii). Cash receipts from sales and debtors.

iv). Personnel expenses and communication expenses.

v). Sales promotion expenses, advertising expenses, outward freight

expenses, warehousing expenses etc.

vi). Loss of sales due to poor advertising, improper distribution etc.

vii). Achieving the sales target.

Similarly, we can fix the responsibility for procurement function as given below:

i). Formulation of procurement budget.

ii). Manpower planning for departmental requirement.

iii). Requirement and utilization of equipment.

iv). Selection of suppliers.

v). Planning of safety stocks.

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vi). Disposal of unwanted stocks.

vii). Controlling of budget expenses.

viii). Controlling of excess procurement expenses.

ix). Controlling of loss of sales due to lack of raw material.

x). Controlling of receiving expenses.

In a similar manner, we can identify the responsibility of all functions, in a manner

so as to achieve the corporate objectives.

FUNCTIONAL ORGANIZATION CHART

Information Technology Management

Information Technology Training

Systems Analysis and Systems Development

Vendor Analysis/Software Package

Procurement and Assistance

Information Technology Resource Contracts Assistance

GIS Data Administration

GIS User Support

GIS Systems Development

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STAFFING ORGANIZATION CHART

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MANAGEMENT

Management can be defined as the planning, organizing and control of personnel

and material resources of the company in order to achieve the established

objectives. Getting things done through people and selecting, training and

motivating of people, is assumed part of the control function hence the importance

of management activities.

Tasks of Management

Management tasks can be described as decision making, planning and controlling

to achieve the objectives.

Decision Making

Decision making is basic to all management activities and can be defined as the

process of selecting a best alternative from among several alternatives, which may

be either quantitative or qualitative) for achieving the objectives. Increase in

number of alternatives makes decisions more and more complex and this decision

complexity decides the time of decision making. The decision complexity may be

because of:

i) Variety

ii) Uncertainty

iii) Time Horizon, and

iv) Implications.

In an organization, decisions are made for planning, organizing, directing,

motivating and controlling of various resources. An orderly process of deriving a

decision contains following elements:

i). Knowledge of situation.

ii). Factors affecting the decision.

iii). Constraints imposed.

iv). Developing alternatives.

v). Criteria of evaluation.

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vi) Method of evaluation.

vii) Implications of the alternatives.

viii) Selection of best alternatives.

EVOLUTION OF MIS FOR PROJECTS

The emergence in the past fifteen years of more numerous projects within most

organizations, and the difficulties experienced in trying to plan, execute and

control temporary projects using management information systems designed to

serve permanent organizations, has led to the development of this new class of

MIS specifically designed to manage projects.

We know that many organizations, such as the large engineering construction

companies, have had some form of PMIS in operation for as long as they have

been in business, because projects are essentially their only business. However, my

experience indicates that these companies typically form a pyramidal, hierarchical

organization structure for each major project, and thus they are able to use the

more traditional MIS, which we have seen were designed to serve such structures.

At some point, 10 to 15 years ago, we realized that we cannot always form a

separate functional, self-supporting organization for each project. The large

engineering-construction and aerospace firms continue this practice to a degree,

but even they are finding that it is more efficient to be able to handle a number of

projects within one basic organization, and to retain the functional structure to the

maximum extent possible.

Other industries of many types have found it even less practical to set up project

organizations for their numerous projects. To illustrate the diversity of business,

industries, and governments presently concerned with managing projects, here is a

breakdown of the more than 500 members of the Project Management Institute

(PMI), representing 310 companies and organizations, and 15 universities located

in 16 countries:

Processing/manufacturing/producing 31%

Engineer/constructor 20%

Consultant (all fields) 20%

Educational/government 11%

Instruments/computers/electronics/electrical equipment 11%

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Other 7%

So the need to be able to plan, execute and control many projects as they passed

through the functional, divisionalized organization forced the evolution of PMIS in

support of the project management capabilities of organizations. Network planning

(both the activity-event and the procedure diagram techniques) emerged as a

powerful tool, if properly applied -- and as a great waste of time and effort if not

properly used. This tool is one form of PMIS. From the project management

viewpoint, its primary advantage is the ability to integrate the plans of many

separate responsibilities and analyze both the logical sequences and the utilization

of time and other resources in these plans, in terms of the total project and, in fact,

many projects.

We could characterize functional management as divisive (as it divides the work

along functional lines) and project management as integrative (as its prime purpose

is to manage the project as a whole.) In this respect, project management is

identical to general management: the former dealing in an integrative manner with

each project, and the latter integrating the enterprise as a whole. Just 10 years ago,

with the publication in 1962 of the U.S. Department of Defense/NASA PERT

COST document, the concept of the "work breakdown structure" emerged. This

followed closely the work I was involved with at Hughes Aircraft Company, where

we developed an operating "PERT Cost" system in 19611. PERT Cost became

rather infamous in the next few years, and the concept went through a series of

name changes and improvements. Presently, the general term "Performance

Measurement Systems" is used in U.S. governmental programs and projects, but

the essential PMIS elements that were present in PERT Cost are still evident in the

current documentation.

A key concept which has emerged from this very expensive effort with the

Defense/Space industry is the systematic definition of projects – the project

breakdown structure (PBS)2. It is through the PBS that we can create a skeleton or

framework, specifically adapted to each project, which fulfills the same

fundamental purpose (from the MIS viewpoint) as the organization structure. This

concept of a structured, systematic subdivision of projects enables the development

of truly integrative PMIS, just as the organization structure has enabled the

development of organizational MIS. It is impossible to budget and control the work

of a large company without subdividing it into divisions, departments and sections;

similarly it is impossible to plan, budget, schedule and control a large project

without subdividing it into manageable tasks. We must also be able, in both. cases,

to summarize information at successively higher levels, and identify deviations

from plan on an exception basis. The PBS provides this capability for PMIS.

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Business process

A business process or business method is a collection of related, structured

activities or tasks that produce a specific service or product (serve a particular

goal) for a particular customer or customers. There are three types of business

processes:

1. Management processes, the processes that govern the operation of a

system. Typical management processes include "Corporate Governance" and

"Strategic Management".

2. Operational processes, processes that constitute the core business and

create the primary value stream. Typical operational processes are

Purchasing, Manufacturing, Marketing and Sales.

3. Supporting processes, which support the core processes. Examples

include Accounting, Recruitment, Technical support.

A business process begins with a customer’s need and ends with a customer’s need

fulfillment. Process oriented organizations break down the barriers of structural

departments and try to avoid functional silos.

A business process can be decomposed into several sub-processes, which have

their own attributes, but also contribute to achieving the goal of the super-process.

The analysis of business processes typically includes the mapping of processes and

sub-processes down to activity level.

Business Processes are designed to add value for the customer and should not

include unnecessary activities. The outcome of a well designed business process is

increased effectiveness (value for the customer) and increased efficiency (less

costs for the company).

Business Processes can be modeled through a large number of methods and

techniques. For instance, the Business Process Modeling Notation is a Business

Process Modeling technique that can be used for drawing business processes in a

workflow.

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The existing system in the organization is totally reexamined and radically

modified for incorporating the latest technology. This process of change for the

betterment of the organization is called as Business process reengineering.

With Business process being reengineered, the organizations have to change the

workflow and business procedures for efficiency in the organization. Latest

software is used and accordingly the business procedures are modified, so that

documents are worked upon more easily and efficiently. This is called as

workflow management.

Business process reengineering is a major innovation changing the way

organizations conduct their business. Such changes are often necessary for

profitability or even survival. BPR is employed when major IT projects such as

ERP are undertaken. Reengineering involves changes in structure, organizational

culture and processes. Many concepts of BPR changes organizational structure.

Team based organization, mass customization, empowerment and telecommuting

are some of the examples. The support system in any organization plays a

important role in BPR. ES, DSS, AI (discussed later) allows business to be

conducted in different locations, provides flexibility in manufacturing permits

quicker delivery to customers and supports rapid paperless transactions among

suppliers, manufacturers and retailers. Expert systems can enable organizational

changes by providing expertise to non experts. It is difficult to carry out BPR

calculations using ordinary programs like spreadsheets etc. Experts make use of

applications with simulations tools for BPR.

Reengineering is basically done to achieve cost reduction, increase in quality,

improvement in speed and service. BPR enable a company to become more

competitive in the market. Employees work in team comprising of managers and

engineers to develop a product. This leads to the formation of interdisciplinary

teams which can work better than mere functional teams. The coordination

becomes easier and faster results can be achieved. The entire business process of

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developing a product gets a new dimension. This has led to reengineering of many

old functional processes in organizations.

BPR – the current focus

Apart from the usual ways of managing a process in any business information

system, it is necessary to enhance the value of the process and also the methods

used in improving the process. Some of the concepts of information management

for effective information systems are the traditional concept of database, the

emerging concepts of data mining and data warehousing.

Concept of Database – Database is a data structure used to store organized

information.

A database is typically made up of many linked tables of rows and columns. For

example, a company might use a database to store information about their

products, their employees, and financial information. Databases are now also used

in nearly all ecommerce sites to store product inventory and customer information.

Database software, such as Microsoft Access, FileMaker Pro, and MySQL is

designed to help companies and individuals organize large amounts of information

in a way where the data can be easily searched, sorted, and updated.

Data Mining - Data mining is primarily used as a part of information system

today, by companies with a strong consumer focus retail, financial,

communication, and marketing organizations. It enables these companies to

determine relationships among "internal" factors such as price, product positioning,

or staff skills, and "external" factors such as economic indicators, competition, and

customer demographics. And, it enables them to determine the impact on sales,

customer satisfaction, and corporate profits. Finally, it enables them to "drill down"

into summary information to view detail transactional data. With data mining, a

retailer could use point of sale records of customer purchases to send targeted

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promotions based on an individual's purchase history. By mining demographic data

from comment or warranty cards, the retailer could develop products and

promotions to appeal to specific customer segments.

Data Warehousing – A data warehouse is a copy of transaction data specifically

structured for querying and reporting. The main output from data warehouse

systems are either tabular listings (queries) with minimal formatting or highly

formatted "formal" reports on business activities. This becomes a convenient way

to handle the information being generated by various processes. Data warehouse is

an archive of information collected from wide multiple sources, stored under a

unified scheme, at a single site. This data is stored for a long time permitting the

user an access to archived data for years. The data stored and the subsequent report

generated out of a querying process enables decision making quickly. This concept

is useful for big companies having plenty of data on their business processes. Big

companies have bigger problems and complex problems. Decision makers require

access to information from all sources. Setting up queries on individual processes

may be tedious and inefficient. Data warehouse may be considered under such

situations.

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Module 2

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Components of Information Systems

An information system has the following components:

1. Hardware ( machines and media)

2. Software (program and procedures)

3. Data ( data and knowledge)

4. Network ( communication Media)

5. People ( end user and specialists)

All five components and arranged and interrelated to perform input, process,

output, feedback and control that converts data resources into information. The

figure shows interrelation between these components

From the figure it can be concluded that:

1. Five basic operating elements of Information system are:

a. Hardware

b. Software

c. Databases

d. Network

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e. People

2. Hardware includes processor, I/O devices, operating system and media

devices. Software includes programs and procedures. Databases includes

data and knowledge base. Network includes communication media and

network devices. People includes operating Personal and System specialists.

3. Database are processed to get the desired information for end user.

4. Information processing consists of input, process, output, data storage and

control.

a. INPUT – Data and instruction

b. Process – Maintain master files, reports, process inquiries, interactive

dialogues

c. OUTPUT – Transaction documents and screen reports.

Information System Resources

Any information system model has five major resources. Basic concepts of

resources and their roles in a system are discussed here.

Hardware Resources

Hardware resources comprises the physical aspect of information system. The term

hardware is generally associated with computers but it also includes peripherals or

data media ( storage devices). Today even the smallest firms, as well as many

households, own or lease computers. These are usually microcomputers, also

called personal computers. Large organizations typically employ multiple

computer systems, from a few powerful mainframe machines (or even more

powerful supercomputers) and minicomputers to widely deployed personal

computers. Together with computer peripheral equipment, such as magnetic disks,

input-output devices, and telecommunications gear, these constitute the hardware

of information systems. The cost of hardware has steadily and rapidly decreased,

while processing speed and storage capacity have increased vastly.

1) Computer systems

a. A modern computer system can be considered as a system with four

main subsystem: inputs, processing, storage and output.

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b. Input to a computer is achieved through variety of input devices.

Special devices are used depending on type of data being captured.

Computers are now able to capture data from multipLe media:

Character based data, sound, images, graphics and movements.

c. Processing subsystems is known as the Central Processing Unit

(CPU). The Central Processing Unit can be subdivided into following

components: Control Unit, Logic unit, Primary storage, Registers.

d. Storage subsystem is used to store the processed data. Data is stored

in the storage system for short-term or long-term use. Data for short-

term use is stored in primary storage. Data for long-term is used in

secondary storage.

e. Output from computer is achieved through a variety of output devices.

Typical output devices include sound based output devices, image

based and graphics-based output devices.

f. Major types of computer systems are personal computers, mini-

computers, mainframe computers.

2) Computer Peripherals:

Computer peripherals are devices other than Computer. Computer

peripherals can be any input devices, output device or storage device. e.g.

keyboard. mouse, monitor, printer, magnetic or optical disks.

Software Resources

The term software is generally used to describe computer programs. A program is

a sequence of instructions given to a computer. Programs must be written in some

formal language known as programming language. All software are essentially

programs. Computer software falls into two broad classes: system software and

application software. The principal system software is known as the operating

system. It manages the hardware, files, and other system resources and provides a

systematic and consistent means for controlling the computer, most commonly via

a graphical user interface (GUI). Application software is programs designed to

handle specialized tasks; many of these programs are sold as ready-to-use

packages. Examples include general-purpose spreadsheet and word processing

programs, as well as ―vertical‖ applications that serve a specific industry

segment—for instance, an application that schedules, routes, and tracks package

deliveries. Larger firms often develop their own application software or customize

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existing packages to meet specific needs. Some companies, known as application

service providers (ASPs), have begun to rent specialized application software on a

per-use basis over the Web.

Types of Software:

Three major levels of software are - system software, communication software and

application software. This forms the software architecture at some information

system.

A. System Software:

a. System software refers to that collection of programs which co-

ordinate .ie activities at hardware and all programs running on the

computer system. System software acts as an interlace between

application software and hardware.

b. One most important type of system software is the operating system.

This is the piece of software that supervises the running of all other

programs on some hardware. The operating system undertakes tasks

such as scheduling the running of programs, controlling input and

output to programs also managing files on secondary storage.

B. Communication Software:

a. This is special type of software used to enable intercommunication

between different computing devices in a network.

C. Application Software:

a. Software application or application system is normally written using

some language or tool set and designed to perform a particular set at

tasks for some oganization.

b. Application software can be distinguished in terms of the number of

people that use of software:

i. Personal productivity Software: This is a software that is

designed for individual use e.g. word processing package.

ii. Workgroup Software (Groupware): This software is designed to

be used across the major part of the organization or the entire

enterprise e.g. accounting software, enterprise resource

planning software.

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Databases

Databases are most important component of information system. Data is the basic

raw material for information system. Data has to he represented in specific manner

(data structuring) for storage and manipulation by Computer hardware and

software also for transmission by communication network. Effective data

structuring will benefit all end users in organization. Various forms of data are

alphanumeric data, text data, image data, audio data. Many information systems

are primarily delivery vehicles for databases. A database is a collection of

interrelated data (records) organized so that individual records or groups of records

can be retrieved that satisfy various criteria. Typical examples of databases include

employee records and product catalogs. Particularly valuable are customer

databases that can be ―mined‖ for information in order to design and market new

products more effectively. Anyone who has ever purchased something with a

credit card—in person, by mail order, or over the Web—is included within some of

the numerous customer databases.

Network Resources

A network is any set of Computer systems joined by some communications

technology, networks can be described in terms of their technology and coverage

e.g. LAN, WAN, MAN and ring, star, bus networks. Telecommunications network

provide the telecommunication structure used to transmit data from one site to

another. Telecommunications network consists of computers, processors, switches,

transmission media and communication software.

Telecommunications are used to connect, or network, computer systems and

transmit information. Various computer network configurations are possible,

depending on the needs of an organization. Local area networks (LANs) join

computers at a particular site, such as an office building or an academic campus.

Wide area networks (WANs) connect machines located at different sites, and often

within different organizations. The Internet is a network of networks, connecting

millions of computers located on every continent. Through networking, personal

computer users gain access to information resources, such as large databases, and

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to human resources, such as coworkers and people who share their professional or

private interests.

Typically used communications networks are Internet, intranet and extranets.

Network resources may be classified into two segments.

(I) Communication Media

(ii) Network Support

A. Communication Media:

Various telecommunication media can be employed for transmission

of data in communication networks: twisted pair cable, co-axial cable,

fiber optic cable, microwave transmission, infrared transmission. A

telecommunication device is a hardware set that allows electronic

communication to occur. Various types of telecommunication devices

are used in communication networks, for example, modems,

multiplexers, front end processors.

B. Network Support:

Network support includes all resources that support the operation and

use of communication networks e.g. people (end user specialists)

hardware (Computer, modem, processor), software (control software,

operating system software).

People Resources

For proper operation of information system people resources are required. These

people may be end user or information system specialists. Qualified people are a

vital component of any information system. Technical personnel include

development and operations managers, systems analysts and designers, computer

programmers, and computer operators. In addition, workers in an organization

must be trained to utilize the capabilities of information systems. Hundreds of

millions of people around the world are learning about information systems as they

use the Web.

Procedures for using, operating, and maintaining an information system are part of

its documentation. For example, procedures need to be established to run a payroll

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program, including when to run it, who is authorized to run it, and who has access

to the output.

A. End-user:

End users are people who uses information system. Information

system user may be any professional like engineer, doctor, salesman,

accountant or shopkeeper also an individual. End user are also called

as clients.

B. SystemSpecialists:

System specialists are people who develop and operate information

systems. Information system specialists include system analysts

programmers and administrators. System analysts! specialists must

design the information as per the requirements of end-user. The

information products should fulfill the need of end-users.

The information system resources and their contents are summarized

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in table

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Classification of Information system

Information system can be classified into various ways. Basis of classification:

A. By function

a. Operations

b. Administrative/ tactical

c. Planning and Control/ Strategic Planning

B. By type of processing

a. Batch

b. Online / Real time

c. Distributed

C. By usage

a. Transaction processing

b. Management Information

c. Decision support

D. By application

a. Manufacturing

b. Distribution

c. Marketing

d. Serials

e. Banking

f. Transportation

E. By resources

a. Information

b. Financial

c. Personal

d. Marketing

In business organization, Information System is classified according to the role it

plays i.e. operation support systems and management support systems. These can

be further divided into few categories:

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Operations Support Systems

In business organization the data generated is processed .by information system

for the use of end user. Variety of information products (reports) are to be

generated from Internal and external users. Such a system is called Operations

support system. At the operational level are transaction processing systems through

which products are designed, marketed, produced, and delivered. These systems

accumulate information in databases that form the foundation for higher-level

systems.

In today’s leading organizations, the information systems that support various

functional units—marketing, finance, production, and human resources—are

integrated into what is known as an enterprise resource planning (ERP) system.

ERP systems support the entire sequence of activities, or value chain, through

which a firm may add value to its goods and services. For example, an individual

or other business may submit a custom order over the Web that automatically

initiates ―just-in-time‖ production to the customer’s exact specifications through an

approach known as mass customization. This involves sending orders to the firm’s

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warehouses and suppliers to deliver materials just in time for a custom-production

run. Finally, financial accounts are updated accordingly, and billing is initiated.

Along with helping to integrate a firm’s own value chain, transaction processing

systems can also serve to integrate an organization’s overall supply chain. This

includes all of the various firms involved in designing, marketing, producing, and

delivering the goods and services—from raw materials to final delivery. Thus,

interorganizational information systems are essential to supply-chain management.

For example, purchasing an item at a Wal-Mart store generates more than a cash

register receipt; it also automatically sends a restocking order to the appropriate

supplier. Suppliers can also access a retailer’s inventory database over the Web to

schedule efficient and timely deliveries.

Many transaction processing systems support electronic commerce over the

Internet. Among these are systems for on-line shopping, banking, and securities

trading. Other systems deliver information, educational services, and entertainment

on demand. Yet other systems serve to support the search for products with desired

attributes, price discovery (for example, via an auction), and delivery of products

in an electronic form (software, music, movies, or greeting cards). A growing array

of specialized services and information-based products are offered by various

organizations on the Web, as an infrastructure for electronic commerce is emerging

on a global scale.

Operations Support System is employed for efficient processing of business

transactions, control industrial process, support communications and to

update corporate databases.

Three major types of operations support systems are -

1. Transaction Processing Systems (TPS)

2. Process Control System (PCS)

3. Enterprise Collaboration System (FCS)

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Transaction Processing Systems (TPs)

A Transaction Processing System (TPS) is a type of information system that collects, stores,

modifies and retrieves the data transactions of an enterprise.

A transaction is any event that passes the ACID test in which data is generated or

modified before storage in an information system

Features of Transaction Processing Systems

The success of commercial enterprises depends on the reliable processing of

transactions to ensure that customer orders are met on time, and that partners and

suppliers are paid and can make payment. The field of transaction processing,

therefore, has become a vital part of effective business management, led by such

organisations as the Association for Work Process Improvement and the

Transaction Processing Performance Council.

Transaction processing systems offer enterprises the means to rapidly process

transactions to ensure the smooth flow of data and the progression of processes

throughout the enterprise. Typically, a TPS will exhibit the following

characteristics:

Rapid Processing

The rapid processing of transactions is vital to the

success of any enterprise – now more than ever, in

the face of advancing technology and customer

demand for immediate action. TPS systems are

designed to process transactions virtually instantly

to ensure that customer data is available to the

processes that require it.

Reliability

Similarly, customers will not tolerate mistakes. TPS systems must be designed to

ensure that not only do transactions never slip past the net, but that the systems

themselves remain operational permanently. TPS systems are therefore designed to

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incorporate comprehensive safeguards and disaster recovery systems. These

measures keep the failure rate well within tolerance levels.

Standardization

Transactions must be processed in the same way each time to maximize efficiency.

To ensure this, TPS interfaces are designed to acquire identical data for each

transaction, regardless of the customer.

Controlled Access

Since TPS systems can be such a powerful business tool, access must be restricted

to only those employees who require their use. Restricted access to the system

ensures that employees who lack the skills and ability to control it cannot influence

the transaction process.

Transactions Processing Qualifiers

In order to qualify as a TPS, transactions made by the system must pass the ACID

test. The ACID tests refers to the following four prerequisites:

Atomicity

Atomicity means that a transaction is either completed in full or not at all. For

example, if funds are transferred from one account to another, this only counts as a

bone fide transaction if both the withdrawal and deposit take place. If one account

is debited and the other is not credited, it does not qualify as a transaction. TPS

systems ensure that transactions take place in their entirety.

Consistency

TPS systems exist within a set of operating rules (or integrity constraints). If an

integrity constraint states that all transactions in a database must have a positive

value, any transaction with a negative value would be refused.

Isolation

Transactions must appear to take place in isolation. For example, when a fund

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transfer is made between two accounts the debiting of one and the crediting of

another must appear to take place simultaneously. The funds cannot be credited to

an account before they are debited from another.

Durability

Once transactions are completed they cannot be undone. To ensure that this is the

case even if the TPS suffers failure, a log will be created to document all

completed transactions.

These four conditions ensure that TPS systems carry out their transactions in a

methodical, standardised and reliable manner.

Types of Transactions

While the transaction process must be standardised to maximise efficiency, every

enterprise requires a tailored transaction process that aligns with its business

strategies and processes. For this reason, there are two broad types of transaction:

Batch Processing

Batch processing is a resource-saving transaction type that stores data for

processing at pre-defined times. Batch processing is useful for enterprises that need

to process large amounts of data using limited resources.

Examples of batch processing include credit card transactions, for which the

transactions are processed monthly rather than in real time. Credit card transactions

need only be processed once a month in order to produce a statement for the

customer, so batch processing saves IT resources from having to process each

transaction individually.

Real Time Processing

In many circumstances the primary factor is speed. For example, when a bank

customer withdraws a sum of money from his or her account it is vital that the

transaction be processed and the account balance updated as soon as possible,

allowing both the bank and customer to keep track of funds.

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Components of TPS

There are several types of transaction processing systems. Likewise, TPS in a

Manufacturing firm can be:

TPS Typical Transactions

Sales Sales order, Sales return

Cash Cash receipts

Accounts receivables Credit sates, credit slips

Cost accounting Accounting for labour and material used in production

Materials inventory Materials receipts & delivery

Plant and machinery Depreciation, additions & dispositions

Engineering Engineering systems

Personnel - New employees. promotions, Transfers

Purchase Purchase orders

Marketing Research Consumer Survey results

Process Control System (PCS) Operations Support System is also used to control operational processes by making

suitable decisions. The inCormation System that helps to control operational

process is called Process Control System. It helps to control production process by

taking decisions automatically by Computers. Typical example of process control

system is chemical process for measuring level. The chemical process is monitored

by electronic sensors attached to computer system.

The Computer monitors the process capture the process data sensed by sensors and

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takes suitable decisions.

Enterprise Collaboration System (ECs) • Enterprise Collaboration System is a type of information system that uses

different information technologies to help people so that they can work together.

• Enterprise collaboration system helps to communicate data, share resources. In a

business organization ECs uses information technology to improve productivity

and creativity of teams. Different workgroups of internal and external members

may be formed for improvement and new product development. They can make

use of Internet, intranet and extranets also collaboration software known as

groupware may be used. For more efficient way of communication data and video

conferencing may be employed.

Management Support Systems

Management support system helps managers in effettive decision making by

providing information in required format. In an organization, management

information system (MIS) is used for efficient and effective data processing. There

are two important reasons of using MIS.

a) Management orientation - In business, the Mis emphasis the management

orientation of information technology. A Computer based information

system must not only process the data generated by business transaction but

it should support in decision making.

b) System Framework:. A system Framework must be used for organizing

information system applications. Applications of information technology are

interrelated and integrated computer based information system (CBIS). The

figure shows this interrelated and integrated computer based information

subsystem.

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CBIS provides information and support to all levels of management in required

form. Different information system focuses on different areas of aspects of

business organization. Table shows important types of information systems and the

area it is related to.

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Types of Information System Area

Management Information

System

Information, for managers & end

users

Decision support system (DSS) Decision making, for managers

Expert system (ES) Knowledge, from experts

Accounting Information

System

Information, for managers, users

Management Information System (MIS)

MIS is the most common type of management support system. MIS provides

information to the managers to help in routine decision making process. It

provides reports in different formats as desired by the managers. It uses

internal data bases and transaction processing system to update the

information. Sometimes data from external sources are also used.

Various information products are available in different forms, it can be

generated on any at the following conditions.

o On demand

o Periodically

o Whenever exceptional conditions occur

A Sales Manager can obtain information –

o instantly about sales at his workstation

o by accessing weekly sales report.

o Whenever sales target is not achieved or any sales person tails to

produce sales report.

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Decision Support System (DSS)

DSS is an improved form of information reporting system and transaction

processing system (TPS). Managers are able to tailor the computer output to

participate quality — related problems.

DSS is an interactive computer based information system (CBIS) which uses

specialized databases for decision making models. But DSS is different than TPS

since it does not focuses on data generated by transactions Operations. DSS is

also different than MIS because it does not provide information in prescribed

form that is used for routine decisions.

DSS provides information in interactive session on adhoc or temporary basis.

Decision support system has following features .

1. Analytical modelling

2. Simulation

3. Data retrieval

4. Information presentation capability.

All information systems support decision making, however indirectly, but decision

support systems are expressly designed for this purpose. The two principal

varieties of decision support systems are model-driven and data-driven.

In a model-driven decision support system, a preprogrammed model is applied to a

limited data set, such as a sales database for the present quarter. During a typical

session, an analyst or sales manager will conduct a dialog with this decision

support system by specifying a number of ―what-if‖ scenarios. For example, in

order to establish a selling price for a new product, the sales manager may use a

marketing decision support system. Such a system contains a preprogrammed

model relating various factors—the price of the product, the cost of goods, and the

promotion expense—to the projected sales volume over the first five years on the

market. By supplying different product prices to the model, the manager can

compare predicted results and select the most profitable selling price.

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The primary objective of data-driven decision support systems is to analyze large

pools of data, accumulated over long periods of time in ―data warehouses,‖ in a

process known as data mining. Data mining searches for significant patterns, such

as sequences (buying a new house, followed by a new dinner table) and clusters

(large families and van sales), with which decisions can be made. Data-driven

decision support systems include a variety of statistical models and rely on various

artificial intelligence techniques, such as expert systems, neural networks, and

intelligent agents.

An important category of decision support systems enables a group of decision

makers to work together without necessarily being in the same place at the same

time. These group decision systems include software tools for brainstorming and

reaching consensus. Another category, geographic information systems, can help

analyze and display data by using digitized maps. By looking at a geographic

distribution of mortgage loans, for example, one can easily establish a pattern of

discrimination.

Executive information system EIS, Executive Information System is a reporting application targeted for use by

executives.

Executive information system is a type of management information system.

EIs are designed to meet the strategic information needs of top level

management. Executive receives the necessary information from letters,

memos, reports, periodicals and by Computer System. Other information

sources are meetings, Telephone calls and social activities. It can be observed

that top executives receives major information from non- computer sources.

The objective of computer based executive information systems is to provide

top management an easy access to selective information about firm's strategy

EIS are easy to understand and operate. DSs and EIs generally are proposed

for providing data in support of unstructured decision making. A decision is

unstructured it the decision making process can not be described in details.

This may be because the problem has not arisen before. It is characterized by

incomplete an uncertain knowledge or uses non-quantifiable data. Examples

of unstructured decision-making are selecting personnel and determining

investment.

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EIS make a variety of critical information readily available in a highly summarized

and convenient form. Senior managers characteristically employ many informal

sources of information, however, so that formal, computerized information systems

are of limited assistance. Nevertheless, this assistance is important for the chief

executive officer, senior and executive vice presidents, and the board of directors

to monitor the performance of the company, assess the business environment, and

develop strategic directions for the future. In particular, these executives need to

compare their organization’s performance with that of its competitors and

investigate general economic trends in regions or countries for potential expansion.

Often relying on multiple media, executive information systems give their users an

opportunity to ―drill down‖ from summary data to increasingly detailed and

focused information.

Executive Information Systems (EIS) provide high level views of an

organization by aggregating data from various sources from within the

organization and also external sources. Ad hoc enquiries provide

performance data and trend analysis for top level management. Ease of use is

an important feature so that enquiries can be made without a detailed

knowledge of the underlying data structures. Graphical interfaces (GUI)

make it possible to request reports and queries without resorting to

programming

EIS provides information about current status and projected trends for certain

important factors. For this, access for internal and external database is

provided. Also EIs provides information to executives in easily usable

formats or in graphical patterns.

Classification Based on Activities • Depending on activities of an organization information system can be classified

into three types.

1. Strategic planning information system.

2. Tactical information system.

3. Operational information system.

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1. Strategic planning information system:

Strategic planning systems arc designed for top level management. Top level

management uses these information systems for long term organizational

planning.

2. Tactical information system:

Tactical systems are designed for middle level management. Middle level

management uses tactical system for monitoring and control operations and

to allocate resources effectively.

3. Operational Systems:

Operational system is designed for Ievel managcment. Management uses the

system for day to day operations e.g. accounts, sales, inventories,

transportation.

Other classification of Information Systems

Many different information systems are being used for either operations or

management applications. These include expert systems, knowledge

management systems, strategic management systems and business

information systems.

A. Expert Systems

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Unlike DSS, expert systems have the potential to extend a manager's problem

solving ability beyond his or her normal capabilities. An expert system consists of

four main components:

a user interface

a knowledge base

an inference engine

a development engine

The knowledge base uses rules to express the logic of the problem that the expert

system is designed to help solve. The inference engine uses reasoning similar to

human in processing the contents of knowledge base. The development engine

consists of either programming languages or prewritten inference engines called

expert system shells. Prototyping is especially applicable to the development of an

expert system. Artificial intelligence is applied in expert system.

Artificial intelligence (AT) - is the activity of providing computers within the

ability to display behaviour that is regarded as intelligence observed in humans.

Such as reasoning, learning and problem solving. An expert system is also known

as knowledge based system i.e. a computer program that attempts to represent the

knowledge of human experts in the form of heuristics. Heuristic is rule of good

guessing. Expert system is being applied in various fields such as engineering,

sciences, medicines and in business.

B. Knowledge Management system (KMS)

Knowledge management system (KMS) are a group of information

technologies used for managing knowledge within organizations. Knowledge is information in a network of relations with rules for the use of information.

In todays competitive business environment companies are trying to become

knowledge creating companies’ i.e. creating new business knowledge and creating

new business services or products. This is essential in order to survive and to

sustain in rapidly changing environment. KMS involves integrating tacit (stored in

mind) with explicit (stored in database) knowledge. Tacit knowledge is clearly

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understood knowledge in individual, knowledge from books, knowledge from

experience while explicit knowledge is process and procedures.

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C. Strategic Information System (SIS)

A strategic information system (SIS) may be defined as any information system

which directly assists on organization in achieving its organization strategy.

SISs are information systems that impact on competitive Position of the

organization. They are systems that directly support organizational strategy and are

critical elements of an organizations informatics strategy. SIS can be used to

improve competitive advantage in terms of cost, differentiation and location SIS

generally have a short life - span because competitors soon replicate the system.

Any type of IS can be strategic information system i.e. MIS, TPS, 0SS.

Essentials of SIS

Essential of strategic information system are mentioned here .

1. SIS must be a Part of strategic plan of the organization.

2. SIS must have support from top management.

3. SIS must not be owned by any one departmental but must belong to all

departments.

Sources of SIS

1. Existing system: Potential use of existing system for strategic advantage can be

recognized.

2. Excess information: Excess information collected previously may turn out to be

a source of strategic information.

3. New Technology: New developed technology can be adopted to get competitive

advantage.

D. Business Information system (BIS)

The information systems required for smooth operations and management

activities (accounting. finance, human resource management. marketing) are

business information systems. The business information system provides

variety of information products to the managers for decision - making for

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example. Marketing manager requires information about sales volume, target

and individual Performance, area wise sales etc.

E. Integrated Information Systems

In real world application an integrated form of information systems are used.

Generally classification of information system is done as per their functional roles.

These functional roles are interrelated hence it is necessary to use cross functional

information systems. For example, sales order processing that is a operation

support system and sales analysis which is marketing information system. These

two information system are integrated information system. Sales order processing

data is input for sales analysis system.

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Business model

The approach to information system is to first develop a business model comprised

of the business processes or activities that are the essence of the business. This is

not the mathematical model, but the portrayal of a business as a one large system

showing the inter connections and the sequence of the business subsystem or

processes that comprise it. The planning is accomplished from the top down while

the implementation is from the bottom up.

Based on business strategy and objectives, a business model comprised of business

processes are managed and controlled by various organization. The information

system is developed to provide the required information to the organization to

manage the processes that are part of the business model. The database is the

source of information and drive the IS.

Examples for business model:

1. B2B

2. B2C

3. C2C

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Module 3

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Information system infrastructure and architecture

A well-designed information system rests on a coherent foundation that supports

modifications as new business or administrative initiatives arise. Known as the

information system infrastructure, the foundation consists of core

telecommunications networks, databases, software, hardware, and procedures.

Managed by various specialists, information systems frequently incorporate the use

of general information and telecommunication utilities, such as the Internet. Owing

to business globalization, an organization’s infrastructure often crosses many

national boundaries. Creating and maintaining such a complex infrastructure

requires extensive planning and consistent implementation to handle strategic

corporate initiatives, transformations, mergers, and acquisitions.

When organized into a coherent whole, the specific information systems that

support operations, management, and knowledge work constitute the system

architecture of an organization.

Clearly, an organization’s long-term general strategic plans must be considered

when designing an information system infrastructure and architecture.

Architecture

We define architecture of a system as a set of related models that describe the

essentials of a system. The variety of models describes different components

(parts) and different views (aspects) of the system. Components are building

blocks: a system can be constructed by gluing together the components according

to some rules. Views differ from components in the sense that they do not occur as

a system on their own. To illustrate this we consider the building industry. Each

floor of a building can be seen as a different component and the water supply

system or the electricity systems are examples of views. The latter systems are

realized in parts that belong to components. In information systems the database

(sub) system and user-interface (sub) system are examples of components and the

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structure of the communication and data are two examples of views. Usually we

distinguish several standard views of a system: a business view, a functional view

and a technical view. Each of these views can be split into parts. The technical

view is split into a software view and a network view. So we divide the

architecture of an information system into four levels:

1. Business architecture. Business processes and the object classes that play a role

considered from the perspective of the information system

2. Functional architecture. The logical decomposition of the system into (logical)

components and the assignment of processes and object classes to these

components

3. Software architecture. Software components that realize the functional

architecture, e.g the database management system, the workflow engine and the

connectivity software (middleware)

4. Network architecture. A computer and communications network together with

their operating systems

In case of a system that is implemented on a stand alone computer the network

architecture is trivial: just one node. In our life cycle we recommend that all

architecture is designed in the second phase. In some other life cycle models the

business architecture is considered to be part of the requirements analysis.

Information systems are a discrete dynamic system, which means that these

systems can be viewed as transition systems that have a (finite or countable

infinite) state space and that make transitions through that state space at discrete

points in time. We distinguish between static models and dynamic models. Static

models describe the structure of a system or the state space (i.e. the set of states the

systems might be in). Dynamic models describe the behavior of the system, i.e. the

possible sequences of transitions a system can make.

The models architecture consists of may be of different type. A verbal description

can be a model, all sorts of diagrams can be models and a set of mathematical or

logical formulas can be a model. We distinguish informal and formal models.

Informal models have a (often sloppy) syntax and an intuitive semantics, like

verbal models and many diagram techniques. Formal models have besides a syntax

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a formal defined semantics. The combination of a modeling syntax and a formal

semantics is called a modeling framework. Mathematical and logical formulas are

examples of formally models. Informal models are used in communications with

stakeholders of a system (persons who have some say in the development of the

system, e.g. potential users). Formal models are meant for systems engineers,

programmers and for software tools that are able to analyze or interpret the models.

There are modeling tools that can generate a simulation model from a description

of the modeling framework. The simulation model is supposed to behave as the

modeled system.

Architecture should have two important properties: consistency and completeness.

"Consistency" means that all models are consistent internally and that they do not

imply any contradiction or conflict when they are put together. Internal consistency

should be defined in terms of the modeling framework. One simple but important

consistency property is that a model is syntactically correct. A more advanced

consistency property that is often required is that the systems are free of deadlocks.

With completeness. We mean that all models together provide sufficient

information for constructing a system with the same functionality as the modeled

system. A practical test for completeness is that from the set of models the external

behavior of the system is fully defined and that a simulation model of the system

can be generated and tested in the environment where the real system should

operate. Note that in general the simulation model is not the same as the real

system because the simulation model captures only the functional requirements of

a system and not necessarily the non-functional requirements, such as the response

times and scalability.

For the verification of the consistency and completeness we have several formal

methods. Although the quality and scope of these methods are increasing rapidly

there are many properties that can not be verified in a formal way. These properties

should be checked by testing methods, i.e. by means of experiments with the

system itself or with a model of the system. An example of a property that can not

be verified by formal methods is "user friendliness" of a system. We call the

checking of properties by means of testing: validation. It is well-known that the

cost of correction of errors increases with the discovery in later stages of

development. Therefore it is important to try to verify and validate a system as

much as possible in the design stage. The architecture is a base for verification. In

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this course we focus on a particular way of verification: correctness by

construction. In this approach we construct models using predefined patterns from

which it is known that they imply correct behavior. This method is not a panacea

for all verification issues.

However a nice feature of this approach is that it does not require searching the

state space but only the diagrams of the models. System architecture is the base for

the development of the software and for the maintenance of a system.

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Organization of information services

An information services unit is typically in charge of an organization’s information

systems. Where information services are centralized, this unit is responsible for

planning, acquiring, operating, and maintaining information systems for the entire

organization. In decentralized structures the central unit is responsible only for

planning and maintaining the infrastructure, while business and administrative

specialists provide systems and services for their own units. Additionally, a variety

of intermediate organizational forms are possible.

In many organizations, information systems are headed by a chief information

officer (CIO). The activities of information services are usually supervised by a

steering committee, consisting of the executives representing various functional

units of the organization. As described in the next section, Information systems

security and control, a vital responsibility of information services is to ensure

uninterrupted service in the face of many security threats.

Information systems security and control

Information systems security

Information systems security is responsible for the integrity and safety of system

resources and activities. Most organizations in developed countries are dependent

on the secure operation of their information systems. In fact, the very fabric of

societies often depends on this security. Information systems are at the heart of

intensive-care units and air-traffic-control systems. Financial institutions could not

survive a total failure of their information systems for longer than a day or two.

Electronic funds transfer systems (EFTS) handle immense amounts of money that

exist only as electronic signals over telecommunications lines or as magnetized

spots on computer disks. Information systems are vulnerable to a number of

threats, which require strict controls as countermeasures and regular audits to

ensure that the system remains secure. The relationship between security measures

is shown in the figure

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.

Although instances of computer crime and abuse receive extensive media attention,

human error is estimated to cause greater losses in information systems operation.

Disasters such as earthquakes, floods, and fires are the particular concern of

disaster recovery planning, which is a part of a corporate business continuation

plan. A contingency scheme is also necessary to cover the failure of corporate

servers or telecommunications networks.

Computer crime and abuse

Computer crime—illegal acts in which computers are the primary tool—costs the

world economies many billions of dollars annually. Computer abuse does not rise

to the level of crime, yet it involves some unethical use of a computer. Some of the

more widespread security threats related to computer crime or abuse include

impersonation, Trojan horse attack, logic bombs, and computer viruses and worms.

Impersonation, as the name implies, involves gaining access to a system by

impersonating a legitimate user—a feat that usually requires knowing or guessing a

legitimate user’s password. In a Trojan horse attack, the malefactor conceals

unauthorized instructions within an authorized program. A logic bomb consists of

hidden instructions, often introduced with the Trojan horse technique, that stay

dormant until a specific event occurs, at which time the instructions are activated.

In one well-known case, a programmer placed a logic bomb in his company’s

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human resources system; when his name was later deleted from the company’s

employee database, the entire database was erased.

Computer viruses are a particularly common form of attack. These are program

instructions that are able not only to perform malicious acts but also to insert

copies of themselves into other programs and e-mail and onto diskettes placed in

the ―infected‖ personal computers, from which they may spread to other computer

systems. Similar to viruses, worms are complete computer programs that replicate

through telecommunications networks.

Information systems controls

To ensure secure and efficient operation of information systems, an organization

institutes a set of procedures and technological measures called controls.

Information systems are safeguarded through a combination of general and

application controls.

General controls apply to information system activities throughout an organization.

The most important general controls are the measures that control access to

computer systems and the information stored there or transmitted over

telecommunications networks. General controls include administrative measures

that restrict employee access to only those processes directly relevant to their

duties. As a result, these controls limit the damage that any individual employee or

employee impersonator can do. Fault-tolerant computer systems installed in critical

environments, such as in hospital information systems or securities marketplaces,

are designed to control and isolate problems so that the system can continue to

function.

Application controls are specific to a given application and include such measures

as validating input data, regularly archiving copies of various databases, and

ensuring that information is disseminated only to authorized users.

Securing information

Controlling access to information systems became profoundly more difficult with

the spread of wide area networks (WANs) and the Internet. Users, as well as

interlopers, may access systems from any unattended computer within an

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organization or from virtually anywhere over the Internet. One security measure is

to require some form of physical authentication, such as an object (a key or a smart

card) or a personal characteristic (fingerprint, retinal pattern, hand geometry, or

signature). Another common security measure is to assign a unique password to

each legitimate user. Many systems combine these types of measures—such as

automatic teller machines, which rely on a combination of a personal identification

number (PIN) and a magnetic-strip identification card. Security measures placed

between an organization’s internal network and the Internet are known as firewalls.

A different way to prohibit access to information is via data encryption, which has

gained particular importance in electronic commerce. To ensure confidentiality,

only the intended addressee has the key needed to decrypt messages. Furthermore,

authentication of both parties in an electronic transaction is possible through the

use of digital signatures—an additional code attached to the message to verify its

origin—and by digital certificates issued to both parties by a trusted third party. A

type of antitampering code can also be attached to a message to indicate

interception or corruption. Similar means are available to ensure that parties to an

electronic exchange cannot later repudiate their participation. Some messages

require additional attributes. For example, electronic cash is a type of message as

well, and sometimes encryption is used to ensure the purchaser’s anonymity.

Information systems audit

The effectiveness of an information system’s controls is evaluated through an

information systems audit. It is a part of a more general financial audit that verifies

an organization’s accounting records and financial statements. Information systems

are designed so that every financial transaction can be traced. In other words, an

audit trail must exist that can establish where each transaction originated and how

it was processed. Aside from financial audits, operational audits are used to

evaluate the effectiveness and efficiency of information systems operations.

Impacts of information systems

Organizational impacts of information systems

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Information systems bring new options to the way companies interact, the way

organizations are structured, and the way workplaces are designed. In general, use

of network-based information systems can significantly lower the costs of

communication among workers and firms and enhance coordination on

collaborative projects. This has led many organizations to concentrate on their core

competencies and to outsource other parts of their value chain to specialized

companies. The capability to communicate information efficiently within a firm

has also led to the deployment of flatter organizational structures with fewer

hierarchical layers.

Nevertheless, information systems do not uniformly lead to higher profits. Success

depends on both the skill with which information systems are deployed and the

availability of other assets. In particular, ―virtual‖ organizations have emerged that

do not rely on physical offices and standard organization charts. Two notable

forms are a network organization and a cluster organization.

In a network organization, long-term corporate partners supply goods and services

to and through a central firm. Together, a network of small companies can present

the appearance of a large corporation. Indeed, at the core of such an organization

may be nothing more than a single entrepreneur supported by only a few

employees. Thanks to information systems, product specifications in an electronic

form can be modified during computerized video conferences between employees

throughout an organization—after which supplies can be secured and distribution

coordinated, using automatic electronic forms as sales orders are received. Wide

area networks, and the Internet in particular, help partnering organizations to

facilitate the interaction of widely dispersed business units.

In a cluster organization, the principal work units are permanent and temporary

teams of individuals with complementary skills. Team members, who are often

widely dispersed around the globe, are greatly assisted in their work by the use of

corporate intranets and groupware.

Information systems built around portable computers, mobile telecommunications,

and groupware have enabled employees to work not just outside the corporate

offices but virtually anywhere. ―Work is the thing you do, not the place you go to,‖

has become the slogan of the emerging new workplace. Virtual workplaces include

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home offices, regional work centres, customers’ premises, and mobile offices of

people such as insurance adjusters. Employees who work in virtual workplaces

outside their company’s premises are known as telecommuters.

Information systems in the economy and society

Along with the global transportation infrastructure, network-based information

systems have been a factor in the growth of international business and

corporations. Although studies have yet to show a relationship between the

deployment of information systems and higher productivity, it is widely believed

that such a relationship exists. In addition to investing in other information

systems, a large and growing number of organizations have embraced electronic

commerce over the Internet.

As the use of information systems has become pervasive in advanced economies

and societies at large, several ethical and social issues have moved into the

forefront. The most important are issues of individual privacy, property rights,

universal access and free speech, information accuracy, and quality of life.

Individual privacy involves the right to control personal information. While

invasion of privacy is generally perceived as an undesirable loss of autonomy,

government and business organizations do need to collect data in order to facilitate

administration and exploit marketing opportunities. Electronic commerce presents

a particular challenge to privacy, as personal information is routinely collected and

disseminated in a largely unregulated manner. Preventing abusive invasions of

privacy is complicated by the lack of an international legal standard.

Intellectual property, such as computer software, books, music, and movies, is

protected, albeit imperfectly, by patents, trade secrets, and copyrights. However,

such essentially intangible goods can be easily copied and transmitted

electronically over the Web for unlawful reproduction and use. Combinations of

legal statutes and technological safeguards, such as antipiracy encryption and

electronic watermarks, are emerging.

Access to public information systems, such as the World Wide Web, is

increasingly necessary for full participation in modern society. In particular, it is

necessary to avoid the emergence of ―digital divides‖ between nations and between

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social and ethnic groups. Open access to the Internet as a medium for human

communication and as a repository for shared knowledge is treasured. Indeed,

many people consider free speech a universal human right and the Internet the

most widely accessible means to exercise this right. Yet legitimate concerns arise

about protecting children without resorting to censorship. Technological solutions,

such as software that filters out pornography, are partially successful.

Of concern to everyone is the accuracy and security of information contained in

databases—whether in health and insurance records, credit bureau records, or

government files—as misinformation can adversely affect personal safety,

livelihood, and everyday life. Individuals must cooperate in reviewing and

correcting their files, and organizations must ensure appropriate access to and use

of such files.

Information systems have affected the quality of personal and working lives. In the

workplace, information systems can be deployed to eliminate tedious tasks and

give workers greater autonomy, or they can be used to eliminate jobs and subject

the remaining workforce to pervasive electronic surveillance. Consumers can use

the Internet to comparison shop for everything from manufactured goods to

financial services or even to participate in auctions—but at the cost of contending

with spam (unsolicited e-mail), intercepted credit card numbers, and malicious

computer viruses.

Information systems can expand participation by ordinary citizens in government

through electronic elections, referendums, and polls and also provide electronic

access to government services and information—permitting, for instance,

electronic filing of taxes, direct deposit of government checks, and distant viewing

of current and historical government documents and photographs. Yet information

systems have also conjured Orwellian images of government surveillance and

intrusion into private lives. It remains for society to harness the power of

information systems by strengthening legal, social, and technological controls.

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Risks Associated With MIS

Risk reflects the potential, the likelihood, or the expectation of events that could

adversely affect earnings or capital. Management uses MIS to help in the

assessment of risk within an institution. Management decisions based upon

ineffective, inaccurate, or incomplete MIS may increase risk in a number of areas

such as credit quality, liquidity, market/pricing, interest rate, or foreign currency. A

flawed MIS causes operational risks and can adversely affect an organization's

monitoring of its fiduciary, consumer, fair lending, Bank Secrecy Act, or other

compliance-related activities.

Since management requires information to assess and monitor performance at all

levels of the organization, MIS risk can extend to all levels of the operations.

Additionally, poorly programmed or non-secure systems in which data can be

manipulated and/or systems requiring ongoing repairs can easily disrupt routine

work flow and can lead to incorrect decisions or impaired planning.

Assessing Vulnerability to MIS Risk

To function effectively as an interacting, interrelated, and interdependent feedback

tool for management and staff, MIS must be "useable." The five elements of a

useable MIS system are: timeliness, accuracy, consistency, completeness, and

relevance. The usefulness of MIS is hindered whenever one or more of these

elements is compromised.

Timeliness

To simplify prompt decision making, an institution's MIS should be capable of

providing and distributing current information to appropriate users. Information

systems should be designed to expedite reporting of information. The system

should be able to quickly collect and edit data, summarize results, and be able to

adjust and correct errors promptly.

Accuracy

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A sound system of automated and manual internal controls must exist throughout

all information systems processing activities. Information should receive

appropriate editing, balancing, and internal control checks. A comprehensive

internal and external audit program should be employed to ensure the adequacy of

internal controls.

Consistency

To be reliable, data should be processed and compiled consistently and uniformly.

Variations in how data is collected and reported can distort information and trend

analysis. In addition, because data collection and reporting processes will change

over time, management must establish sound procedures to allow for systems

changes. These procedures should be well defined and documented, clearly

communicated to appropriate employees, and should include an effective

monitoring system.

Completeness

Decision makers need complete and pertinent information in a summarized form.

Reports should be designed to eliminate clutter and voluminous detail, thereby

avoiding "information overload."

Relevance

Information provided to management must be relevant. Information that is

inappropriate, unnecessary, or too detailed for effective decision making has no

value. MIS must be appropriate to support the management level using it. The

relevance and level of detail provided through MIS systems directly correlate to

what is needed by the board of directors, executive management, departmental or

area mid-level managers, etc. in the performance of their jobs.

Achieving Sound MIS

The development of sound MIS is the result of the development and enforcement

of a culture of system ownership. An "owner" is a system user who knows current

customer and constituent needs and also has budget authority to fund new projects.

Building "ownership" promotes pride in institution processes and helps ensure

accountability.

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Although MIS does not necessarily reduce expenses, the development of

meaningful systems, and their proper use, will lessen the probability that erroneous

decisions will be made because of inaccurate or untimely information. Erroneous

decisions invariably misallocate and/or waste resources. This may result in an

adverse impact on earnings and/or capital. MIS which meets the five elements of

useability is a critical ingredient to an institution's short- and long-range planning

efforts. To achieve sound MIS, the organization's planning process should include

consideration of MIS needs at both the tactical and strategic levels. For example, at

a tactical level MIS systems and report output should support the annual operating

plan and budgetary processes. They should also be used in support of the long term

strategic MIS and business planning initiatives. Without the development of an

effective MIS, it is more difficult for management to measure and monitor the

success of new initiatives and the progress of ongoing projects. Two common

examples of this would be the management of mergers and acquisitions or the

continuing development and the introduction of new products and services.

Management needs to ensure that MIS systems are developed according to a sound

methodology that encompasses the following phases:

• Appropriate analysis of system alternatives, approval points as the system is

developed or acquired, and task organization.

• Program development and negotiation of contracts with equipment and software

vendors.

• Development of user instructions, training, and testing of the system.

• Installation and maintenance of the system.

Management should also consider use of "project management techniques" to

monitor progress as the MIS system is being developed. Internal controls must be

woven into the processes and periodically reviewed by auditors. Management also

should ensure that managers and staff receive initial and ongoing training in MIS.

In addition, user manuals should be available and provide the following

information:

• A brief description of the application or system.

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• Input instructions, including collection points and times to send updated

information.

• Balancing and reconciliation procedures.

• A complete listing of output reports, including samples.

Depending on the size and complexity of its MIS system, an institution may need

to use different manuals for different users such as first-level users, unit managers,

and programmers.

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Module 4

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Decision Making

Decision making is the process of choosing alternatives to achieve a desired goal.

According to Hebert Simon (1977, The New Science of Management Decision)

managerial decision making is synonymous with the whole process of

management.

The module not only summarizes management decision as a function of time span,

information characteristics and structure, but also implies that evaluation of a given

scenario may be a function of our position in the management structure. Given the

Information Age, an individual professional faces a similar environment, can use

similar tools in the decision making process. A brief look at some of the "Greatest

Management Decisions" as described in 1988 by Management Review, may

provide context to the decision making disciplines involved.

Making Decisions:

Decision Process

Collect Data

Identify Problems & Opportunities

Make Choices

Decision behaviour:

Stage Activities

Intelligence Awareness of problem

Awareness that a decision must be made

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Design Identify all possible solutions

Examine possible solutions

Examine implications of possible solutions

Choice Select best solution

Implementation Implement solution

Evaluation Evaluate effectives/success of decision

Decision Types:

Programmed decisions

A decision made using a rule, procedure, or

quantitative method.

Easy to computerize using traditional information

systems

Non-programmed decisions

decisions that deal with unusual or exceptional

situations

Not easily quantifiable

Problem Solving Approaches:

Optimization Model

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find the best solution, usually the one that will best

help the organization meet its goals

Satisficing Model

find a good (but not necessarily the best) solution to a

problem

The word satisfice was coined by Herbert Simon. He

pointed out that human beings lack the cognitive

resources to maximize: we usually do not know the

relevant probabilities of outcomes, we can rarely

evaluate all outcomes with sufficient precision, and

our memories are weak and unreliable.

Heuristics: Commonly accepted guidelines or procedures

that usually find a good solution

Decision characteristics:

Management

level

Decision

type

Timescale Impact Decision

frequency

Strategic Unstructured Long Large Infrequent

Tactical Both Medium Medium Both

Operational Structured Short Small Frequent

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Data, Information, and Knowledge:

Data: raw facts

Information: collection of facts organized in such a way

that they have value beyond the facts themselves

Knowledge: awareness and understanding of a set of

information and ways that information can be made useful

to support a specific task or reach a decision

Data Manipulation:

Data is manipulated to make useful information

A survey is a common method of collecting data

Raw data is hard to read

Information is more useful to business than data

Generating Information:

A process:

Is manipulation of data

Usually produces information

May produce more data and often useless

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A piece of information in one context may be considered

data in another context

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Decision-Making Tools

Two tools frequently used by teams to make decisions are Multivoting and

Nominal Group Technique. While idea-generating tools such as Brainstorming

produce a list of possible alternatives, Multivoting and Nominal Group Technique

help

to identify the important or popular items or prioritize the items on a list

NOTE: It is important to remember that not all decisions are made in a team

situation. Of those decisions that are made by teams, not every one is going to be

made using these tools.

How does a team select the right tool to use?

Try Multivoting if you need to:

o Reduce a long list of ideas and assign priorities quickly and with a

high degree of team agreement

o Identify the important items on a list

Try Nominal Group Technique if you need a more structured approach to:

o Generate, clarify, and evaluate a sizable list of ideas, problems, or

issues

o Prioritize the items on a list

What is Multivoting?

Multivoting is a group decision-making technique used to reduce a long list of

items to a manageable number by means of a structured series of votes

The result is a short list identifying what is important to the team.

When should a team use Multivoting?

Use Multivoting whenever a Brainstorming session has generated a list of items

that is too extensive for all items to be addressed at once. Because Multivoting

provides a quick and easy way for a team to identify the most popular or highest

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priority items on a list—those that are worthy of immediate attention—this tool

can be helpful when you need to.

Reduce a large list of items to a workable number quickly, with limited

discussion and little difficulty.

Prioritize a large list without creating a situation in which there are winners

and losers in the group that generated the list.

Identify the important or popular items on a large list.

What are the procedures for Multivoting?

Follow these steps to conduct Multivoting:

Step 1 - Work from a large list of items developed by Brainstorming or another

appropriate idea-generating technique.

Step 2 - Assign a letter to each item to avoid confusion of item designations with

the vote tally.

Step 3 - Vote

Each team member selects the most important one-third (or no more than

one half of the items) by listing the letters which appear next to those items.

For example, if there are 60 items, each person should choose the 20 items

(one third of the total) he or she thinks are most important.

Each team member may cast only one vote per idea and must cast all

allotted votes.

Voting may be done either by a show of hands or by paper ballot when the

team chooses to preserve confidentiality.

Step 4 - Tally the votes. Place a checkmark next to each item for each vote it

received. Retain the items with the most votes for the next round of voting.

Scholtes, in The Team Handbook provides the following

Rule of Thumb for deciding how many items to eliminate in each round,

depending on the size of the group:

If the team has 5 or fewer members, eliminate those items that receive 2 or

fewer votes.

If the team has 6 to 15 members, eliminate all items that receive 3 or fewer

votes.

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If the team has more than 15 members, eliminate all items that receive 4 or

fewer votes.

Step 5 - Repeat. In the second round, each person again selects the top one-third

of the items. Repeat steps 3 and 4 until only a few items remain. Never multivote

down to only one item.

The items that were not identified as priorities should be retained as backup data or

for future use by the team in its improvement efforts.

How can our team practice Multivoting?

Three exercises that will enable teams to practice this tool are on the following

pages. But first, let's walk through an example adapted from the U.S. Air Force

Process Improvement Guide.

EXAMPLE:

Members of a Command's Planning Board for Training conducted meetings which

were not always as productive as they might have been. The XO called a meeting

to identify the reasons for the lack of meeting productivity and to determine which

reasons the team thought most important. The XO led a Brainstorming session

which produced the following list:

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Lack of Meeting Productivity

A. No agenda

B. Problems not mentioned

C. No clear objectives

D. Interrupted by phone calls

E. Going off on tangents

F. Few meaningful metrics

G. Extraneous topics

H. Interrupted by visitors

I. Too many "sea stories"

J. No administrative support

K. Vital members missing

L. Meetings extended beyond from meeting allotted time

M. Not enough preparation

N. Members distracted by for meetings pressing operations

O. Too much "dog and pony"

P. Unclear charts

The team used Multivoting to reduce this list to a manageable size:

Each of the 6 members of the team was allowed 8 votes (half the number of

items).

The votes were tallied, as shown in Viewgraph 6, and the top 8 items were

carried forward to the second round.

The items that had 4 or more votes in the first round were reduced to 4 in a

second round of voting.

The group chose to focus on problems F, G, H, and J,

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What Is Nominal Group Technique?

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Nominal Group Technique, or NGT, is a weighted ranking method that enables a

group to generate and prioritize a large number of issues within a structure that

gives everyone an equal voice (Viewgraph 12). The tool is called nominal because

there is limited interaction between members of the group during the NGT process.

When should a team use NGT?

When a team needs to create a list of options and rank them, using NGT effectively

neutralizes the domination of the loudest person, or the person with the most

authority, over the decision-making process. This tool can also help a team achieve

consensus about the relative importance of issues. The final result may not be

everyone's first priority, but they can live with it. NGT is a good tool to use when

dealing with controversial or emotional issues, or when a group is stuck. It is

particularly useful when you need to:

Reduce the number of issues for easier handling.

Get input from all team members.

Rank items in priority order.

What are the procedures for NGT?

NGT is a facilitated process that has two parts. The following description of how to

conduct an NGT session is adapted from The Team Handbook:

NGT PART I - The issue is defined and the team generates ideas.

Introduce and clarify the issue to be addressed by the team. Write the issue

on a chartpack where everybody can see it. Allow for clarification, but do

not let the group engage in a discussion of the issue itself. Remember to

define unclear terms.

Generate ideas to address the issue at hand.

o Working in silence, each team member writes down his or her ideas

on a piece of paper. People should not confer with each other and

should sit quietly until everyone finishes writing.

o Depending on the complexity of the topic, 5 to 10 minutes should be

allowed for the silent process. People need to have enough time to get

the broad, general ideas down, but not enough to create long, detailed

lists.

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o Collect the team's ideas. Each team member in turn reads out one of

his or her ideas. Write each idea on the chartpack. This round robin

should continue until all of the ideas have been offered and recorded.

There should be no discussion or side conversations during this part

of the session.

NOTE: If post-are available, you may want to ask the participants to write

each of their ideas on a separate sheet and hand them in. You can display the

ideas randomly, rather than writing them down. These post- can be used

later to create an Affinity Diagram.

Clarify ideas. Read each idea out loud. If clarification is needed, the person

who provided the idea should explain it now. This is an opportunity to clean

up the wording of any unclear statements. Others may contribute if

necessary.

Combine ideas. Combine like ideas when feasible, but only if both

o Originators agree to it. If they cannot agree, leave the two ideas

separate.

Assign a letter designation to each separate idea. As with Multivoting, the

facilitator assigns a letter to avoid confusion with the vote tally.

Rank the ideas independently. Each team member writes down the items

by their letter designations and assigns them a numeric value based on his or

her judgment of what is most important and what is least important. The

highest number is assigned to the most important idea and the lowest to the

least important idea. For example, if there are 8 items lettered A to H, the

most important receives an 8 and the least important, a 1.

NOTE: An alternative approach is to use the one-half-plus-one rule described in

The Memory Jogger. When there is a list with many items to rank, you may want

to limit the number of items to consider. Team members then rank one-half the

number of items on the list plus one.

For example, if there were 20 items on the list, team members would rank 11

ideas. The most important item receives the highest value—in this case, 11.

Collate the rankings. The facilitator transcribes the team members'

rankings onto a chartpack, writing each number next to the corresponding

idea.

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Add the rankings. The facilitator adds the numbers across. The idea with

the highest point total is the one of most importance to the whole team. It is

the highest priority item.

Rewrite the list. The facilitator rewrites the list of ideas in the order of their

importance to the team.

Perform a sanity check. Does the prioritization make sense?

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Decision:

Making up your mind to do something

Making a judgment on what ought to be done

To do nothing and wait for things to happen can also be a decision

Decision Making vs. Decision Taking:

Decision making involves a series of steps that ultimately culminates in a

resolution

Decision taking may be instantaneous, impulsive, unconscious, intuitive

Decision making is usually systematic and based on thinking

Decision taking may usually rely on gut feeling

Decision making vs. Problem solving:

Problem solving and Decision making are inter-twined

Information is required for both problem solving and decision making

Why decision making is difficult?

Too many options/ alternatives from which to decide

High cost of wrong decisions

Increasingly dynamic environment with greater uncertainties

Competitor moves and counter-moves at extremely fast pace

Herbert Simon’s Model of decision making:

Decision making is a rational process comprising three major phases:

Intelligence

Design

Choice

Simon’s Model:

Intelligence Phase:

Scan the environment for a problem.

Determine if decision-maker can solve the problem.

Within scope of influence

Fully define the problem by gathering more information about the problem.

Design:

Decision maker identifies alternative courses of action to solve a problem

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This can be a creative activity requiring brain storming, analogies, checklists

etc.

Not all alternatives are clearly visible; they have to be unearthed from a heap

of possibilities

Only a finite and limited number of alternatives can be finally evaluated

Choice Phase:

Select the solution to implement.

More detailed analysis of selected solutions might be needed.

Verify initial conditions.

Analyze proposed solution against real-world constraints.

Phases of Decision-Making:

Simon’s original three phases:

Intelligence

Design

Choice

He added fourth phase later:

Implementation

Book adds fifth stage:

Monitoring

Typology of Decisions:

Robert Anthony’s Classification:

Strategic Planning

Management Control

Operational Control

Simon’s Classification

Programmed/ structured decisions

Nonprogrammed/ Unstructured decisions

Properties of Programmed/ structured decisions:

Well-defined decision situation

Some specified procedure or decision rule can be applied

Routine and repetitive

Can be modeled as a quantitative model

Can be delegated to lower levels or automated

Properties of Non-programmed/ unstructured decisions:

Not well-defined

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Have no pre-specified procedure or decision rule

Decision situation may be novel one (e.g.: catastrophe)

Or it may be related to recurring problems where conditions change very

frequently and so substantially that no decision rule can be specified

Can’t be delegated to lower levels and can’t be automated

Semi-structured/ partially programmed decisions:

Decisions falling within the two extremes

Some semblance of structuring is possible, which is then programmed

Human judgment is applied to the situational factors which are not

structured and thus not programmed

Classifying Decisions on the basis of - Knowledge of Outcomes:

Decisions under certainty

Outcome of each alternative is fully known

Only one outcome for each alternative

Decisions under risk

Possibility of multiple outcomes

Probability of occurrence can be attached

Decisions under uncertainty

Number of outcomes for each alternative and their probabilities of

occurrence not known

Roadblocks to Good Decision Making:

Human cognition

Our mental ability to comprehend and understand something

Human perception

Difficulty isolating problems

Tend to think of only narrow range of possible solution

Human bias

Tendency to shape responses based on stereotypes, memory, and

current position

How to Overcome the Roadblocks:

Decision support systems (DSS) are one tool

A computer-based system that supports and improves human decision

making

Helps analyze complex problems

Process vast amounts of analytical data

Group decision support systems (GDSS)

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Tool for supporting team decision making

Executive information system (EIS)

Decision Support System

Abbreviated DSS, the term refers to an interactive computerized system that

gathers and presents data from a wide range of sources, typically for business

purposes. DSS applications are systems and subsystems that help people make

decisions based on data that is culled from a wide range of sources.

For example: a national on-line book seller wants to begin selling its products

internationally but first needs to determine if that will be a wise business decision.

The vendor can use a DSS to gather information from its own resources (using a

tool such as OLAP) to determine if the company has the ability or potential ability

to expand its business and also from external resources, such as industry data, to

determine if there is indeed a demand to meet. The DSS will collect and analyze

the data and then present it in a way that can be interpreted by humans. Some

decision support systems come very close to acting as artificial intelligence agents.

Information Systems researchers and technologists have built and investigated

Decision Support Systems (DSS) for approximately 40 years. This paper

chronicles and explores the developments in DSS beginning with building model-

driven DSS in the late 1960s, theory developments in the 1970s, and the

implementation of financial planning systems, spreadsheet DSS and Group DSS in

the early and mid 80s. Data warehouses, Executive Information Systems, OLAP

and Business Intelligence evolved in the late 1980s and early 1990s. Finally, the

chronicle ends with knowledge-driven DSS and the implementation of Web-based

DSS in the mid-1990s.

DSS applications are not single information resources, such as a database or a

program that graphically represents sales figures, but the combination of integrated

resources working together.

A decision support system is a way to model data and make quality decisions

based upon it. Making the right decision in business is usually based on the

quality of your data and your ability to sift through and analyze the data to find

trends in which you can create solutions and strategies for. DSS or decision

support systems are usually computer applications along with a human

component that can sift through large amounts of data and pick between the many

choices.

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While many people think of decision support systems as a specialized part of a

business, most companies have actually integrated this system into their day to

day operating activities. For instance, many companies constantly download and

analyze sales data, budget sheets and forecasts and they update their strategy once

they analyze and evaluate the current results. Decision support systems have a

definite structure in businesses, but in reality, the data and decisions that are based

on it are fluid and constantly changing.

The key to decision support systems is to collect data, analyze and shape the data

that is collected and then try to make sound decisions or construct strategies from

analysis. Whether computers, databases or people are involved usually doesn't

matter, however it is this process of taking raw or unstructured data, containing

and collecting it and then using it to help aid decision making.

It is important to note that although computers and artificial intelligence is at

work or in play with data, it is ultimately up to humans to execute these strategies

or comprehend the data into a usable hypothesis.

It is important to note that the field of DSS does not have a universally accepted

model, meaning that there are many theories vying for supremacy in this broad

field. Because of there are many working theories in the topic of DSS, there are

many ways to classify DSS.

For instance, one of the DSS models available is with the relationship of the user

in mind. This model takes into consideration passive, active and cooperative DSS

models.

Decision support systems that just collect data and organize it effectively are

usually called passive models, they do not suggest a specific decision, and they

only reveal the data. An active decision support system actually processes data

and explicitly shows solutions based upon that data. While there are many

systems that are able to be active, many organizations would be hard pressed to

put all their faith into a computer model without any human intervention.

A cooperative decision support system is when data is collected, analyzed and

then is provided to a human component which then can help the system revise or

refine it. It means that both a human component and computer component work

together to come up with the best solution.

While the above DSS model takes the relationship of the user in mind, another

popular DSS model takes into consideration the mode of assistance as the

underlying basis of the DSS model. This includes the Model Driven DSS,

Communications Driven DSS, Data Driven DSS, Document Driven DSS, and

Knowledge Driven DSS.

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Model Driven DSS is when decision makers use statistical, simulations or

financial models to come up with a solution or strategy. Keep in mind that these

decisions are based on models; however they do not have to be overwhelming

data intensive.

A Communications Driven DSS models is when many collaborators work

together to come up with a series of decisions to set in motion a solution or

strategy. This communications driven DSS model can be in an office environment

or on the web.

A Data Driven DSS model puts its emphasis on collected data that is then

manipulated to fit the decision maker's needs. This data can be internal, external

and in a variety of formats. It is important that usually data is collected and

categorized as a time series which is a collection of data that forms a sequence,

such as daily sales, operating budgets from one quarter to the next, inventory

levels over the previous year, etc.

A Document Driven DSS model uses documents in a variety of data types such a

text documents, spreadsheets and database records to come up with decisions a

well as further manipulate the information to refine strategies.

A Knowledge Driven DSS model uses special rules stored in a computer or used

by a human to determine whether a decision should be made. For instance, for

many day traders a stop loss limit can be seen as a knowledge driven DSS model.

These rules or facts are used in order to make a decision.

You can also look at the scope in which decisions are made as a model of DSS.

For instance, an organizational wide decision, department decision or single user

decision, can be seen in the scope wide model.

Brief History

In the 1960s, researchers began analytically studying the use of computerized

quantitative models to assist in decision making and planning (Raymond, 1966;

Turban, 1967; Urban, 1967, Holt and Huber, 1969). Ferguson and Jones (1969)

reported the first investigational study using a computer aided decision system.

They investigated a production scheduling application running on an IBM 7094. In

retrospect, a major historical turning point was Michael S. Scott Morton's (1967)

dissertation field research at Harvard University.

Scott Morton’s study involved building, implementing and then testing an

interactive, model-driven management decision system. Fellow Harvard Ph.D.

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student Andrew McCosh asserts that the ―concept of decision support systems was

first articulated by Scott Morton in February 1964 in a basement office in Sherman

Hall, Harvard Business School‖ (McCosh email, 2002) in a discussion they had

about Scott Morton’s dissertation. During 1966, Scott Morton (1971) studied how

computers and analytical models could help managers make a recurring key

business planning decision. He conducted an research in which managers actually

used a Management Decision System (MDS). Marketing and production managers

used an MDS to coordinate production planning for laundry equipment. The MDS

ran on an IDI 21 inch CRT with a light pen connected using a 2400 bps modem to

a pair of Univac 494 systems.

The pioneering work of George Dantzig, Douglas Engelbart and Jay Forrester

likely influenced the feasibility of building computerized decision support systems.

In 1952, Dantzig became a research mathematician at the Rand Corporation, where

he began implementing linear programming on its experimental computers. In the

mid-1960s, Engelbart and colleagues developed the first hypermedia—groupware

system called NLS (oNLine System). NLS facilitated the creation of digital

libraries and the storage and retrieval of electronic documents using hypertext.

NLS also provided for on-screen video teleconferencing and was a forerunner to

group decision support systems. Forrester was involved in building the SAGE

(Semi-Automatic Ground Environment) air defense system for North

America completed in 1962. SAGE is probably the first computerized data-driven

DSS. Also, Professor Forrester started the System Dynamics Group at the

Massachusetts Institute of Technology Sloan School. His work on corporate

modeling led to programming DYNAMO, a general simulation compiler.

In 1960, J.C.R. Licklider published his ideas about the future role of multi access

interactive computing in a paper titled ―Man-Computer Symbiosis.‖ He saw man-

computer interaction as enhancing both the quality and efficiency of human

problem solving and his paper provided a guide for decades of computer research

to follow. Licklider was the architect of Project MAC at MIT that furthered the

study of interactive computing.

By April 1964, the development of the IBM System 360 and other more powerful

mainframe systems made it practical and cost-effective to develop Management

Information Systems (MIS) for large companies (cf., Davis, 1974). These early

MIS focused on providing managers with structured, periodic reports and the

information was primarily from accounting and transaction processing systems, but

the systems did not provide interactive support to assist managers in decision

making.

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Around 1970 business journals started to publish articles on management decision

systems, strategic planning systems and decision support systems

(cf., Sprague and Watson 1979).. For example, Scott Morton and

colleagues McCosh and Stephens published decision support related articles in

1968. The first use of the term decision support system was in Gorry and Scott-

Morton’s (1971) Sloan Management Review article. They argued that

Management Information Systems primarily focused on structured decisions and

suggested that the supporting information systems for semi-structured and

shapeless decisions should be termed ―Decision Support Systems‖.

T.P. Gerrity, Jr. focused on Decision Support Systems design issues in his 1971

Sloan Management Review article titled "The Design of Man-Machine Decision

Systems: An Application to Portfolio Management". The article was based on his

MIT Ph.D. dissertation. His system was designed to support investment managers

in their daily management of a clients' stock portfolio.

John D.C. Little, also at Massachusetts Institute of Technology, was studying DSS

for marketing. Little and Lodish (1969) reported research on MEDIAC, a media

planning support system. Also, Little(1970) identified criteria for designing models

and systems to support management decision-making. His four criteria included:

robustness, ease of control, simplicity, and completeness of relevant detail. All four

criteria remain relevant in evaluating modern Decision Support Systems. By

1975, Little was expanding the frontiers of computer-supported modeling.

His DSS called Brandaid was designed to support product, promotion, pricing and

advertising decisions. Little also helped develop the financial and marketing

modeling language known as EXPRESS.

In 1974, Gordon Davis, a Professor at the University of Minnesota, published his

influential text on Management Information Systems. He defined a Management

Information System as "an integrated, man/machine system for providing

information to support the operations, management, and decision-making functions

in an organization.

Peter Keen and Charles Stabell claim the concept of decision support systems

evolved from "the theoretical studies of organizational decision making done at the

Carnegie Institute of Technology during the late 1950s and early '60s and the

technical work on interactive computer systems, mainly carried out at the

Massachusetts Institute of Technology in the 1960s

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In 1995, Hans Klein and Leif Methlie noted ―A study of the origin of DSS has still

to be written. It seems that the first DSS papers were published by PhD students or

professors in business schools, who had access to the first time-sharing computer

system: Project MAC at the Sloan School, the Dartmouth Time Sharing Systems at

the Tuck School. In France, HEC was the first French business school to have a

time-sharing system (installed in 1967), and the first DSS papers were published

by professors of the School in 1970.

Computerized decision support systems became practical with the development of

minicomputers, timeshare operating systems and distributed computing. The

history of the implementation of such systems begins in the mid-1960s. In a

technology field as diverse as DSS, chronicling history is neither neat nor linear.

Different people perceive the field of Decision Support Systems from various

vantage points and report different accounts of what happened and what was

important (cf., Arnott & Pervan, 2005; Eom & Lee, 1990b; McCosh & Correa-

Perez, 2006; Power, 2003; Power, 2004a; Silver, 1991). As technology evolved

new computerized decision support applications were developed and studied.

Researchers used multiple frameworks to help build and understand these systems.

This hypertext document is a starting point in explaining the origins of the various

technology threads that are converging to provide integrated support for managers

working alone, in teams and in organization hierarchies to manage organizations

and make more rational decisions. History is both a guide to future activity in this

field and a record of the ideas and actions of those who have helped advance our

thinking and practice. Historical facts can be sorted out and better understood, but

more information gathering is necessary. This web page is a starting point in

collecting more first hand accounts and in building a more complete mosaic of

what was occurring in universities, software companies and in organizations to

build and use DSS.

This document traces decision support applications and research studies related to

model and data-oriented systems, management expert systems, multidimensional

data analysis, query and reporting tools, online analytical processing (OLAP),

Business Intelligence, group DSS, conferencing and groupware, document

management, spatial DSS and Executive Information Systems as the technologies

emerge, converge and diverge. All of these technologies have been used to support

decision making.

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The study of decision support systems is an applied discipline that uses knowledge

and especially theory from other disciplines. For this reason, many DSS research

questions have been examined because they were of concern to people who were

building and using specific DSS.

Some professional say Decision Support Systems (DSS) are a specific class of

computerized information system that supports business and organizational

decision-making activities. A properly designed DSS is an interactive software-

based system intended to help decision makers compile useful information from

raw data, documents, personal knowledge, and/or business models to identify and

solve problems and make decisions.

Typical information that a decision support application might gather and present

would be:

Accessing all of your current information assets, including legacy and

relational data sources, cubes, data warehouses, and data marts

Comparative sales figures between one week and the next

Projected revenue figures based on new product sales assumptions

The consequences of different decision alternatives, given past experience in

a context that is described

The best decision

support systems include high-level summary reports or charts and allow the user to

drill down for more detailed information.

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This set of tools, in conjunction with 2-dimensional hydraulic modeling, is being

used to estimate the effects of reservoir level and water discharge fluctuations on

aquatic and terrestrial habitats in John Day Reservoir. Different scenarios being

studied now range from typical reservoir levels at high and low discharges to a

simulation of what things might be like if the river were to return to natural

conditions

Classifying DSS

There are several ways to classify DSS applications. Not every DSS fits neatly into

one category, but a mix of two or more architecture in one.

Holsapple and Whinston classify DSS into the following six frameworks: Text-

oriented DSS, Database-oriented DSS, Spreadsheet-oriented DSS, Solver-oriented

DSS, Rule-oriented DSS, and Compound DSS.

A compound DSS is the most popular classification for a DSS. It is a hybrid

system that includes two or more of the five basic structures described by

Holsapple and Whinston.

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The support given by DSS can be separated into three distinct, interrelated

categories: Personal Support, Group Support, and Organizational Support.

DSS components may be classified as:

1. Inputs: Factors, numbers, and characteristics to analyze

2. User Knowledge and Expertise: Inputs requiring manual analysis by the

user

3. Outputs: Transformed data from which DSS "decisions" are generated

4. Decisions: Results generated by the DSS based on user criteria

DSSs which perform selected cognitive decision-making functions and are based

on artificial intelligence or intelligent agents technologies are called Intelligent

Decision Support Systems (IDSS).

The nascent field of Decision engineering treats the decision itself as an engineered

object, and applies engineering principles such as Design and Quality assurance to

an explicit representation of the elements that make up a decision.

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Types of Decision Support Systems (DSS)

Decision Support Systems (DSS) are a class of computerized information system

that support decision-making activities. DSS are interactive computer-based

systems and subsystems intended to help decision makers use communications

technologies, data, documents, knowledge and/or models to complete decision

process tasks.

A decision support system may present information graphically and may include

an expert system or artificial intelligence (AI). It may be aimed at business

executives or some other group of knowledge workers.

Typical information that a decision support application might gather and present

would be, (a) Accessing all information assets, including legacy and relational data

sources; (b) Comparative data figures; (c) Projected figures based on new data or

assumptions; (d) Consequences of different decision alternatives, given past

experience in a specific context.

There are a number of Decision Support Systems. These can be categorized into

five types:

Communication-driven DSS

Most communications-driven DSSs are targetted at internal teams, including

partners. Its purpose are to help conduct a meeting, or for users to

collaborate. The most common technology used to deploy the DSS is a web

or client server. Examples: chats and instant messaging softwares, online

collaboration and net-meeting systems.

Data-driven DSS

Most data-driven DSSs are targeted at managers, staff and also

product/service suppliers. It is used to query a database or data warehouse to

seek specific answers for specific purposes. It is deployed via a main frame

system, client/server link, or via the web. Examples: computer-based

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databases that have a query system to check (including the incorporation of

data to add value to existing databases.

Document-driven DSS

Document-driven DSSs are more common, targeted at a broad base of user

groups. The purpose of such a DSS is to search web pages and find

documents on a specific set of keywords or search terms. The usual

technology used to set up such DSSs are via the web or a client/server

system. Examples:

Knowledge-driven DSS:

Knowledge-driven DSSs or 'knowledgebase' are they are known, are a catch-

all category covering a broad range of systems covering users within the

organization seting it up, but may also include others interacting with the

organization - for example, consumers of a business. It is essentially used to

provide management advice or to choose products/services. The typical

deployment technology used to set up such systems could be slient/server

systems, the web, or software runnung on stand-alone PCs.

Model-driven DSS

Model-driven DSSs are complex systems that help analyse decisions or choose

between different options. These are used by managers and staff members of a

business, or people who interact with the organization, for a number of purposes

depending on how the model is set up - scheduling, decision analyses etc. These

DSSs can be deployed via software/hardware in stand-alone PCs, client/server

systems, or the web.

DSS in accounting firms by Dr. SHMUEL (SAM) VAKNIN

Many companies in developing countries have a very detailed reporting system

going down to the level of a single product, a single supplier, a single day.

However, these reports – which are normally provided to the General Manager -

should not, in my view, be used by them at all. They are too detailed and, thus,

tend to obscure the true picture. A General Manager must have a bird's eye view of

his company. He must be alerted to unusual happenings, disturbing financial data

and other irregularities.

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As things stand now, the following phenomena could happen:

a. That the management will highly leverage the company by assuming

excessive debts burdening the cash flow of the company and / or

b. That a false Profit and Loss (PNL) picture will emerge - both on the single

product level - and generally. This could lead to wrong decision making,

based on wrong data.

c. That the company will pay excessive taxes on its earnings and / or

d. That the inventory will not be fully controlled and appraised centrally and /

or

e. That the wrong cash flow picture will distort the decisions of the

management and lead to wrong (even to dangerous) decisions.

To assist in overcoming the above, there are four levels of reporting and flows of

data which every company should institute:

The first level is the annual budget of the company which is really a business plan.

The budget allocates amounts of money to every activity and / or department of the

firm.

As time passes, the actual expenditures are compared to the budget in a feedback

loop. During the year, or at the end of the fiscal year, the firm generates its

financial statements: the income statement, the balance sheet, the cash flow

statement.

Put together, these four documents are the formal edifice of the firm's finances.

However, they can not serve as day to day guides to the General Manager.

The second tier of financial audit and control is when the finance department

(equipped with proper software – Solomon IV is the most widely used in the West)

is able to produce pro forma financial statements monthly.

These financial statements, however inaccurate, provide a better sense of the

dynamics of the operation and should be constructed on the basis of Western

accounting principles (GAAP and FASBs, or IAS).

But the Manager should be able to open this computer daily and receive two kinds

of data, fully updated and fully integrated:

1. Daily financial statements;

2. Daily ratios report.

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The daily financial statements

The Manager should have access to continuously updated statements of income,

cash flow, and a balance sheet. The most important statement is that of the cash

flow. The manager should be able to know, at each and every stage, what his real

cash situation is - as opposed to the theoretical cash situation which includes

accounts payable and account receivable in the form of expenses and income.

These pro forma financial statements should include all the future flows of money -

whether invoiced or not. This way, the Manager will be able to type a future date

into his computer and get the financial reports and statements relating to that date.

In other words, the Manager will not be able to see only a present situation of his

company, but its future situation, fully analysed and fully updated.

Using today's technology - a wireless-connected laptop – managers are able to

access all these data from anywhere in the world, from home, while traveling,

and so on.

The daily ratios report

This is the most important part of the decision support system.

It enables the Manager to instantly analyse dozens of important aspects of the

functioning of his company. It allows him to compare the behaviour of these

parameters to historical data and to simulate the future functioning of his company

under different scenarios.

It also allows him to compare the performance of his company to the performance

of his competitors, other firms in his branch and to the overall performance of the

industry that he is operating in.

The Manager can review these financial and production ratios. Where there is a

strong deviation from historical patterns, or where the ratios warn about problems

in the future – management intervention may be required.

Instead of sifting through mountains of documents, the Manager will only have to

look at four computer screens in the morning, spot the alerts, read the explanations

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offered by the software, check what is happening and better prepare himself for the

future.

Examples of the ratios to be included in the decision system

a. SUE measure - deviation of actual profits from expected profits;

b. ROE - the return on the adjusted equity capital;

c. Debt to equity ratios;

d. ROA - the return on the assets;

e. The financial average;

f. ROS - the profit margin on the sales;

g. ATO - asset turnover, how efficiently assets are used;

h. Tax burden and interest burden ratios;

i. Compounded leverage;

j. Sales to fixed assets ratios;

k. Inventory turnover ratios;

l. Days receivable and days payable;

m. Current ratio, quick ratio, interest coverage ratio and other liquidity and

coverage ratios;

n. Valuation price ratios;

and many others.

The effects of using a decision system

A decision system has great impact on the profits of the company. It forces the

management to rationalize the depreciation, inventory and inflation policies. It

warns the management against impending crises and problems in the company. It

specially helps in following areas:

1. The management knows exactly how much credit it could take, for how long

(for which maturities) and in which interest rate. It has been proven that

without proper feedback, managers tend to take too much credit and burden

the cash flow of their companies.

2. A decision system allows for careful financial planning and tax planning.

Profits go up, non cash outlays are controlled, tax liabilities are minimized

and cash flows are maintained positive throughout.

3. As a result of all the above effects the value of the company grows and its

shares appreciate.

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4. The decision system is an integral part of financial management in the West.

It is completely compatible with western accounting methods and derives all

the data that it needs from information extant in the company.

So, the establishment of a decision system does not hinder the functioning of the

company in any way and does not interfere with the authority and functioning of

the financial department.

Decision Support Systems cost as little as 20,000 USD (all included: software,

hardware, and training). They are one of the best investments that a firm can make.

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Models

A major element of a Decision Support System (refer to decision making process)

is a Model, a simplified representation of reality. Models are classified according

to the degree of abstraction:

Iconic - least abstract, a physical replica of a system

Analog model - functional equivalent, but does not look like the system

Mathematical/Quantitative - more abstract mathematical or other

quantitative models.

TYPES OF ANALYTICAL MODELS

What if analysis - Observing how changes to selected variables affect other

variables. Example: What happens to sales if we cut advertising by 10%? Sensitivity analysis - Observing how repeated changes to a single variable

affect other variables. Example: If advertising is cut by $100 repeatedely,

to see how sales change Goal-seeking analysis - Making repeated changes to selected variables until

a chosen variable reaches a target value. Example, Increase advertising until

sales reaches $5,000,000 USD. Optimization analysis - Finds an optimum value for selected variable given

certain constraints: Example: What is the best amount of advertising to

have, given budget and media choice?

QUANTITATIVE MODEL COMPONENTS

Decision variables Un-controllable variables Result variables Mathematical Relationship

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DESCRIPTIVE MODELS –

Descriptive Models are mathematically-based and include"

Information Flow Scenario Analysis Financial Planning Inventory Decisions Predictions (Markov analysis) Simulation ( Optimization Modeling) Technological Forecasting Queuing Management

SPREADSHEET MODELS

For example, The Green River Basin Water Plan - Surface Water Models are

available online at http://waterplan.state.wy.us/plan/green/models/models.html

The spreadsheet models were developed to determine average monthly streamflow

in the Green River Basin during normal, wet, and dry years. In addition, these

models aid in validating existing basin uses, assist in determining timing and

location of water available for future development, and help to assess impacts of

future water supply alternatives.

Result variables Mathematical

Relationship

Decision variables

Un-controllable

variables

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Some other models

The InvestSmart Market Simulation. This interactive educational stock and

mutual fund simulation uses real stock and mutual fund delayed quotes from the

major US exchanges such as NYSE, AMEX, and NASDAQ.

Iowa Electronic Markets - This is an on-line futures market where contract payoffs

are based on real-world events such as political outcomes, companies' earnings per

share (EPS), and stock price returns. It is run as a non-profit educational and

research project by faculty at University of Iowa Henry B. Tippie College of

Business. Most of the markets use real money, although there is a free practice

market.

Stock Market Game (SMG Worldwide) - Provided by a consortium of educational

organizations, This is a dedicated educational stock market game. The game can be

played using a Javascript-enabled web browser. Games run over set time periods,

and there are separate divisions for adults and school teams.

Make Your Own Indicator of Sustainable Economic Welfare - The focus of this

interactive site is the comparison between GDP and welfare. It allows the user to

select and balance several factors to produce a customised indicator. Java is used to

plot a graph of this indicator over the second half of the Twentieth Century, with a

plot of GDP for comparison.

Virtual Economy - A detailed model of the UK Economy, based on the H.M.

Treasury model, which puts you in the position of Chancellor, showing you the

macro- and micro-economic consequences of your budgets. Users can choose to

alter a limited number of variables, or the full set. As well as very professional

design and presentation, the site offers background material on macroeconomic

theory.

2005: A Game for Macroeconomists (USA) - Worth Publishers' companion site to

Mankiw's textbook hosts several interactive features using Shockwave. One of

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them is an online game in which the student takes the role of American President,

setting rates of taxes and government spending and viewing the effects on a variety

of indicators

National Budget Simulation - Anders Schneiderman and Nathan Newman - Center

for Community Economic Research, U.C. Berkeley

This simulation challenges the user to balance the 1995 US Budget by

making a serious of choices from drop-down menus. There are "short" and

"long" lists of choices, so you can choose the level of detail. The site works

mostly in text, but has an optional graphing feature.

Virtual Stock Exchange - VirtualStockExchange is a simulated securities broker

that provides mock trading of all securities listed on the major U.S. exchanges.

Distinction between MIS and DSS:

MIS DSS

Decision support

provided

Provide information about

organisation’s performance

for general control

Provide support in

analyzing specific

problems and arriving at

decision options

Information form

& frequency

Periodic, exception, demand

and push/ routine reports

Interactive queries and

responses

Information

format

Pre-specified, fixed format Ad hoc, flexible and

adaptable format

Information

processing

methodology

processing of data Analytical modeling of

data

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Earlier Versions of DSS:

Stand-alone systems

Model-driven

Usually developed by end-user divisions

Newer Versions of DSS:

Data from various enterprise-based systems/ TPS collected in data

warehouses (DWH)

Include a large pool of customer related data and any other relevant external

data

Analyze DWH data through Online Analytical Processing (OLAP) and Data

mining

Characteristics of a DSS:

System Description: Common Decision Support Systems

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DSS Process:

DSS Examples:

General Accident Insurance: Customer buying patterns and fraud detection

Bank of America: Customer profiles

Frito-Lay, Inc.: Price, advertising, and promotion selection

Burlington Coat Factory:Store location and inventory mix

Keycorp: Targeting direct mail marketing customers

National Gypsum: Corporate planning & forecasting

Southern Railway: Train dispatching and routing

Texas Oil & Gas: Evaluation of potential drilling sites

United Airlines: Flight scheduling, passenger demand forecasting

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Geographic Information Systems (GIS):

Computer system with software that can analyze and display data using

digitized maps. Enables display and analysis of spatial information.

Examples – Location analysis, law enforcement, identifying efficient

delivery routes

Decision Support Systems:

Intelligence Phase

Automatic

Data Mining

Expert systems, CRM, neural networks

Manual

OLAP

KMS

Reporting

Routine and ad hoc

Design Phase

Financial and forecasting models

Generation of alternatives by expert system

Relationship identification through OLAP and data mining

Recognition through KMS

Business process models from CRM, RMS, ERP, and SCM

Choice Phase

Identification of best alternative

Identification of good enough alternative

What-if analysis

Goal-seeking analysis

May use KMS, GDSS, CRM, ERP, and SCM systems

Implementation Phase

Improved communications

Collaboration

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Training

Supported by KMS, expert systems, GDSS

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Why use DSS?

Perceived benefits

decision quality

improved communication

cost reduction

increased productivity

time savings

improved customer and employee satisfaction

Pivot Table:

A PivotTable Report (commonly called a pivot table) is a specialized report

in Microsoft Excel that summarizes and analyzes data from an outside

source like a

spreadsheet or similar table.

a pivot table is a tool for taking a large and complete amount of data and

formatting it in a table that makes that same information easier to understand

and assimilate.

You generally will create a pivot table when

you want to do one of the following:

extract a smaller amount of data from a larger set of data

sum up a large amount of data and compare one section of the original data

with another or

organize sub-categories of data within larger categories.

Groups Decision Support Systems:

Having multiple participants in the decision process adds potential problems

Production blocking

Evaluation apprehension

Social loafing

Group think

GDSS tools contain special tools to overcome these problems

GDSS Tools:

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Brainstorming tools

Commenter tools

Categorizing tools

Idea-ranking tools

Electronic-voting tools

Group facilitator

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Module 5

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What is ERP?

Enterprise Resource Planning (ERP) programs are core software used by companies to coordinate information in

every area of the business. ERP (pronounced E-R-P) programs how to manage company. business processes, using

a common database and shared management reporting tools. A business process is a collection of activities that

takes one or more kinds of input and creates an output. Such as a report or forecast, that is of value to the customer.

ERP software supports the efficient operation of business processes by integrating throughout a business tasks

related to sales, marketing, manufacturing, logistics, accounting, and staffing.

This chapter provides a background for learning about ERP software.

ERP stands for Enterprise Resource Planning. ERP is a way to integrate the data

and processes of an organization into one single system. Usually ERP systems will

have many components including hardware and software, in order to achieve

integration, most ERP systems use a unified database to store data for various

functions found throughout the organization.

The term ERP originally referred to how a large organization planned to use

organizational wide resources. In the past, ERP systems were used in larger more

industrial types of companies. However, the use of ERP has changed and is

extremely comprehensive, today the term can refer to any type of company, no

matter what industry it falls in. In fact, ERP systems are used in almost any type of

organization - large or small.

In order for a software system to be considered ERP, it must provide an

organization with functionality for two or more systems. While some ERP

packages exist that only cover two functions for an organization (QuickBooks:

Payroll & Accounting), most ERP systems cover several functions.

Today's ERP systems can cover a wide range of functions and integrate them into

one unified database. For instance, functions such as Human Resources, Supply

Chain Management, Customer Relations Management, Financials, Manufacturing

functions and Warehouse Management functions were all once stand alone

software applications, usually housed with their own database and network, today,

they can all fit under one umbrella - the ERP system

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Enterprise Resource Planning software, or ERP, doesn't live up to its acronym.

Forget about planning—it doesn't do that—and forget about resource, a throwaway

term. But remember the enterprise part. This is ERP's true ambition. It attempts to

integrate all departments and functions across a company onto a single computer

system that can serve all those different departments' particular needs.

That is a tall order, building a single software program that serves the needs of

people in finance as well as it does the people in human resources and in the

warehouse. Each of those departments typically has its own computer system, each

optimized for the particular ways that the department does its work. But ERP

combines them all together into a single, integrated software program that runs off

a single database so that the various departments can more easily share information

and communicate with each other.

Integration is Key to ERP

That integrated approach can have a tremendous payback if companies install the

software correctly. Take a customer order, for example. Typically, when a

customer places an order, that order begins a mostly paper-based journey from in-

basket to in-basket around the company, often being keyed and re-keyed into

different departments' computer systems along the way. All that lounging around

in in-baskets causes delays and lost orders, and all the keying into different

computer systems invites errors. Meanwhile, no one in the company truly knows

what the status of the order is at any given point because there is no way for the

finance department, for example, to get into the warehouse's computer system to

see whether the item has been shipped. "You'll have to call the warehouse," is the

familiar refrain heard by frustrated customers.

Integration is an extremely important part to ERP's. ERP's main goal is to integrate

data and processes from all areas of an organization and unify it for easy access

and work flow. ERP's usually accomplish integration by creating one single

database that employs multiple software modules providing different areas of an

organization with various business functions.

Although the ideal configuration would be one ERP system for an entire

organization, many larger organizations usually create and ERP system and then

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build upon the system and external interface for other stand alone systems which

might be more powerful and perform better in fulfilling an organizations needs.

Usually this type of configuration can be time consuming and does require lots of

labor hours.

The Ideal ERP System

An ideal ERP system is when a single database is utilized and contains all data for

various software modules. These software modules can include:

Manufacturing: Some of the functions include; engineering, capacity, workflow

management, quality control, bills of material, manufacturing process, etc.

Financials: Accounts payable, accounts receivable, fixed assets, general ledger

and cash management, etc.

Human Resources: Benefits, training, payroll, time and attendance, etc

Supply Chain Management: Inventory, supply chain planning, supplier

scheduling, claim processing, order entry, purchasing, etc.

Projects: Costing, billing, activity management, time and expense, etc.

Customer Relationship Management: sales and marketing, service,

commissions, customer contact, calls center support, etc.

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Data Warehouse: Usually this is a module that can be accessed by an

organizations customers, suppliers and employees.

How can ERP improve a company's business performance?

ERP automates the tasks involved in performing a business process—such as order

fulfillment, which involves taking an order from a customer, shipping it and billing

for it. With ERP, when a customer service representative takes an order from a

customer, he or she has all the information necessary to complete the order (the

customer's credit rating and order history, the company's inventory levels and the

shipping dock's trucking schedule). Everyone else in the company sees the same

computer screen and has access to the single database that holds the customer's

new order. When one department finishes with the order it is automatically routed

via the ERP system to the next department. To find out where the order is at any

point, one need only log into the ERP system and track it down. With luck, the

order process moves like a bolt of lightning through the organization, and

customers get their orders faster and with fewer errors than before. ERP can apply

that same magic to the other major business processes, such as employee benefits

or financial reporting.

ERP Improves Productivity

Before ERP systems, each department in an organization would most likely have

their own computer system, data and database. Unfortunately, many of these

systems would not be able to communicate with one another or need to store or

rewrite data to make it possible for cross computer system communication. For

instance, the financials of a company were on a separate computer system than the

HR system, making it more intensive and complicated to process certain functions.

Once an ERP system is in place, usually all aspects of an organization can work in

harmony instead of every single system needing to be compatible with each other.

For large organizations, increased productivity and less types of software are a

result.

That, at least, is the dream of ERP. The reality is much harsher.

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Let's go back to those inboxes for a minute. That process may not have been

efficient, but it was simple. Finance did its job, the warehouse did its job, and if

anything went wrong outside of the department's walls, it was somebody else's

problem. Not anymore. With ERP, the customer service representatives are no

longer just typists entering someone's name into a computer and hitting the return

key. The ERP screen makes them business people. It flickers with the customer's

credit rating from the finance department and the product inventory levels from the

warehouse. Will the customer pay on time? Will we be able to ship the order on

time? These are decisions that customer service representatives have never had to

make before and which affect the customer and every other department in the

company. But it's not just the customer service representatives who have to wake

up. People in the warehouse who used to keep inventory in their heads or on scraps

of paper now need to put that information online. If they don't, customer service

will see low inventory levels on their screens and tell customers that their

requested item is not in stock. Accountability, responsibility and communication

have never been tested like this before.

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How long will an ERP project take?

Companies that install ERP do not have an easy time of it. Don't be fooled when

ERP vendors tell you about a three or six month average implementation time.

Those short (that's right, six months is short) implementations all have a catch of

one kind or another: the company was small, or the implementation was limited to

a small area of the company, or the company only used the financial pieces of the

ERP system (in which case the ERP system is nothing more than a very expensive

accounting system). To do ERP right, the ways you do business will need to

change and the ways people do their jobs will need to change too. And that kind of

change doesn't come without pain. Unless, of course, your ways of doing business

are working extremely well (orders all shipped on time, productivity higher than all

your competitors, customers completely satisfied), in which case there is no reason

to even consider ERP.

The important thing is not to focus on how long it will take—real transformational

ERP efforts usually run between one to three years, on average—but rather to

understand why you need it and how you will use it to improve your business.

What will ERP fix in my business?

There are three major reasons why companies undertake ERP: To integrate

financial data. —As the CEO tries to understand the company's overall

performance, he or she may find many different versions of the truth. Finance has

its own set of revenue numbers, sales has another version, and the different

business units may each have their own versions of how much they contributed to

revenues. ERP creates a single version of the truth that cannot be questioned

because everyone is using the same system. To standardize manufacturing

processes. —Manufacturing companies—especially those with an appetite for

mergers and acquisitions—often find that multiple business units across the

company make the same widget using different methods and computer systems.

Standardizing those processes and using a single, integrated computer system can

save time, increase productivity and reduce headcount. To standardize HR

information. —Especially in companies with multiple business units, HR may not

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have a unified, simple method for tracking employee time and communicating with

them about benefits and services. ERP can fix that.

In the race to fix these problems, companies often lose sight of the fact that ERP

packages are nothing more than generic representations of the ways a typical

company does business. While most packages are exhaustively comprehensive,

each industry has its quirks that make it unique. Most ERP systems were designed

to be used by discreet manufacturing companies (who make physical things that

can be counted), which immediately left all the process manufacturers (oil,

chemical and utility companies that measure their products by flow rather than

individual units) out in the cold. Each of these industries has struggled with the

different ERP vendors to modify core ERP programs to their needs.

Will ERP fit the ways I do business?

It's critical for companies to figure out if their ways of doing business will fit

within a standard ERP package before the checks are signed and the

implementation begins. The most common reason that companies walk away from

multimillion dollar ERP projects is that they discover that the software does not

support one of their important business processes. At that point there are two

things they can do: They can change the business process to accommodate the

software, which will mean deep changes in long-established ways of doing

business (that often provide competitive advantage) and shake up important

peoples' roles and responsibilities (something that few companies have the stomach

for). Or they can modify the software to fit the process, which will slow down the

project, introduce dangerous bugs into the system and make upgrading the

software to the ERP vendor's next release excruciatingly difficult, because the

customizations will need to be torn apart and rewritten to fit with the new version.

Needless to say, the move to ERP is a project of breathtaking scope, and the price

tags on the front end are enough to make the most placid CFO a little twitchy. In

addition to budgeting for software costs, financial executives should plan to write

checks to cover consulting, process rework, integration testing and a long laundry

list of other expenses before the benefits of ERP start to manifest themselves.

Underestimate the price of teaching users their new job processes can lead to a

rude shock down the line, So can failure to consider data warehouse integration

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requirements and the cost of extra software to duplicate the old report formats. A

few oversights in the budgeting and planning stage can send ERP costs spiraling

out of control faster than oversights in planning almost any other information

system undertaking.

Implementing an ERP system is not an easy task to achieve, in fact it takes lots of

planning, consulting and in most cases 3 months to 1 year +. ERP systems are

extraordinary wide in scope and for many larger organizations can be extremely

complex. Implementing an ERP system will ultimately require significant changes

on staff and work practices. While it may seem reasonable for an in house IT staff

to head the project, it is widely advised that ERP implementation consultants be

used, due to the fact that consultants are usually more cost effective and are

specifically trained in implementing these types of systems.

One of the most important traits that an organization should have when

implementing an ERP system is ownership of the project. Because so many

changes take place and its broad effect on almost every individual in the

organization, it is important to make sure that everyone is on board and will help

make the project and using the new ERP system a success.

Usually organizations use ERP vendors or consulting companies to implement

their customized ERP system. There are three types of professional services that

are provided when implementing an ERP system, they are Consulting,

Customization and Support.

Consulting Services - usually consulting services are responsible for the initial

stages of ERP implementation, they help an organization go live with their new

system, with product training, workflow, improve ERP's use in the specific

organization, etc.

Customization Services - Customization services work by extending the use of the

new ERP system or changing its use by creating customized interfaces and/or

underlying application code. While ERP systems are made for many core routines,

there are still some needs that need to be built or customized for an organization.

Support Services- Support services include both support and maintenance of ERP

systems. For instance, trouble shooting and assistance with ERP issues.

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What does ERP really cost?

Meta Group recently did a study looking at the Total Cost of Ownership (TCO) of

ERP, including hardware, software, professional services, and internal staff costs.

The TCO numbers include getting the software installed and the two years

afterward, which is when the real costs of maintaining, upgrading and optimizing

the system for your business are felt. Among the 63 companies surveyed—

including small, medium and large companies in a range of industries—the

average TCO was $15 million (the highest was $300 million and lowest was

$400,000). While it’s hard to draw a solid number from that kind of a range of

companies and ERP efforts, Meta came up with one statistic that proves that ERP

is expensive no matter what kind of company is using it. The TCO for a ―heads-

down‖ user over that period was a staggering $53,320.

When will I get payback from ERP—and how much will it be?

Don’t expect to revolutionize your business with ERP. It is a navel gazing exercise

that focuses on optimizing the way things are done internally rather than with

customers, suppliers or partners. Yet the navel gazing has a pretty good payback if

you’re willing to wait for it—a Meta group study of 63 companies found that it

took eight months after the new system was in (31 months total) to see any

benefits. But the median annual savings from the new ERP system was $1.6

million per year.

Advantages of ERP Systems

There are many advantages of implementing an EPR system; here are a few of

them:

A totally integrated system

The ability to streamline different processes and workflows

The ability to easily share data across various departments in an organization

Improved efficiency and productivity levels

Better tracking and forecasting

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Lower costs

Improved customer service

Enterprise Resource Planning is very essential to enhance corporate effectiveness

in providing the demands and expectations of customers and clients. The

integration of the functions, files, and activities of companies stored in software

allows employees to access information that are significant to monitor the supply

chain, as well as the production chain. Aside from this, ERP helps corporations

save money since they do not have to allot a budget for the database management

software that each department uses. Additionally, the approach can also lessen

power consumption expenses. To maximize the implementation of this process,

companies are encouraged to assign IT employees to maintain and provide support

services for the ERP system.

Disadvantages of ERP Systems

While advantages usually outweigh disadvantages for most organizations

implementing an ERP system, here are some of the most common obstacles

experienced:

Usually many obstacles can be prevented if adequate investment is made and

adequate training is involved, however, success does depend on skills and the

experience of the workforce to quickly adapt to the new system.

Customization in many situations is limited

The need to reengineer business processes

ERP systems can be cost prohibitive to install and run

Technical support can be shoddy

ERP's may be too rigid for specific organizations that are either new or want

to move in a new direction in the near future.

When firms fail to allot sufficient investment for the Enterprise Resource Planning

software that they use, the approach can affect the functionalities and efficiency of

departments. In this regard, it is important that corporations create a policy that

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will protect the files stored in the system to prevent experiencing the common

problems associated with ERP.

One of the disadvantages of Enterprise Resource Planning is that the use of

software that will manage the activities of a firm can affect the workflow,

competitive advantage, and employee morale. In addition, the implementation of

this approach is very expensive and very risky. Since the files, activities, and

corporate reports are centralized, there is a high possibility that some important and

confidential files could be lost.

Instructions to Migrate Data to an ERP System

Data migration is a significant and sensitive process related to the implementation

of Enterprise Resource Planning in companies. Planning is important before firms

start with this process. To ensure successful transfer of business files, these are the

simple steps to follow.

1. Determine which of the corporate records should be transferred to the new

system.

2. Prepare a timeline for data migration.

3. Create templates for the data.

4. Do not forget to freeze and secure computer tools that will be used in the

migration.

5. Assess the efficiency and reliability of archiving settings to be implemented.

A few things to ponder when planning for ERP

• Which processes are most important now and why?

• Does this sytem meet our needs or go beyond them?

• Who will be the change champion(s)?

• Who are the stakeholders?

• What is the business culture at our company and what are its strengths?

• What subcultures do we have and what are their strengths?

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• How can we apply those strengths to business change?

• What cultural attributes are weak or will interfere with the change?

• What will be the toughest changes, and how will we address them?

• Who will be responsible for change management?

Cost savings alone won’t justify an ERP upgrade.

The bad news? ERP is still costly and time consuming. But the good news,

according to recent research by Boston-based AMR Research, is that

companies are finally accepting ERP as a strategic part of the business.

Accordingly, AMR analysts say, further investments in the technology will

require sound business reasoning beyond the cost-saving arguments that

initially brought ERP to life.

―It all has to do with the attitude that companies take with their ERP system,‖

says Alison Bacon, AMR analyst. ―The business people have to be involved

and realize that it’s not an IT-only issue any more.‖

AMR Research surveyed 109 companies (70 percent of which have annual

revenues exceeding $1 billion) and found that 85 percent of them listed

improved ease of use, additional functionality and improved collaboration as

the primary benefits to an ERP upgrade. Just 13 percent listed cost savings as

the main motivator.

―Increasingly, people are not looking at ERP systems as just a big piece of

software, but it's being seen as a core strategic asset of the company,‖ says

Judy Bijesse, AMR analyst. ―It’s much more important that the system

remains relevant and adds functionality.‖

Half of the companies surveyed added an average of three new functional areas to

their ERP systems. The most popular were portals, Internet-based procurement

applications, self-service HR and business intelligence. AMR Analyst Allison

Bacon says ERP is taking on an even broader set of applications today than before.

―Portals, business intelligence—those are applications that extend beyond

what we would deem to be traditional ERP systems,‖ Bacon says. ―The

vendors have done a great job upselling to their existing client base.‖

For the most part, the survey found that cost expectations hit the mark. Most

(76 percent) respondents said the costs of upgrading met their expectations.

On average, though, actual costs exceeded expected costs by about $100,000.

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The average cost of an ERP upgrade in this survey was $1.5 million or 18

percent of the cost of the initial ERP implementation.

The survey also found that small, incremental ERP upgrades drove costs

higher. Larger upgrades (those that affect the most users) provided better

economy of scale. Companies that were able to upgrade efficiently learned

from their initial implementations, says Bijesse. In fact, most companies

surveyed (65 percent) handled their ERP upgrades through an in-house group.

―Undertaking a big, big project like that requires internal expertise,‖ Bijesse

says. ―Companies that were able to maintain competency in–house were in

much better shape.‖

According to the survey, the average upgrade takes about seven months from

planning to the launch date. Planning consumes about 24 percent of the total

time while testing requires another 22 percent. Testing was ranked the most

difficult stage of ERP upgrading by 29 percent of respondents. Another 28

percent said data conversion/migration was the most difficult.

―The success of the planning phase determines the success of the overall project,‖

says Bijesse.

The Hidden Costs of ERP

Although different companies will find different land mines in the budgeting

process, those who have implemented ERP packages agree that certain costs

are more commonly overlooked or underestimated than others. Armed with

insights from across the business, ERP pros vote the following areas as most

likely to result in budget overrun.

1. Training

Training is the near-unanimous choice of experienced ERP implementers as

the most elusive budget item. It's not so much that this cost is completely

overlooked as it is consistently underestimated. Training expenses are high

because workers almost invariably have to learn a new set of processes, not

just a new software interface.

2. Integration and Testing

Testing the links between ERP packages and other corporate software links

that have to be built on a case-by-case basis is another often underestimated

cost. A typical manufacturing company may have add-on applications for

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logistics, tax, production planning and bar coding. If this laundry list also

includes customization of the core ERP package, expect the cost of

integrating, testing and maintaining the system to skyrocket.

As with training, testing ERP integration has to be done from a process-

oriented perspective. Instead of plugging in dummy data and moving it from

one application to the next, veterans recommend running a real purchase order

through the system, from order entry through shipping and receipt of

payment-the whole order-to-cash banana-preferably with the participation of

the employees who will eventually do those jobs.

3. Data conversion

It costs money to move corporate information, such as customer and supplier

records, product design data and the like, from old systems to new ERP

homes. Although few CIOs will admit it, most data in most legacy systems is

of little use. Companies often deny their data is dirty until they actually have

to move it to the new client/server setups that popular ERP packages require.

Consequently, those companies are more likely to underestimate the cost of

the move. But even cleandata may demand some overhaul to match process

modifications necessitated—or inspired—by the ERP implementation.

4. Data analysis

Often, the data from the ERP system must be combined with data from

external systems for analysis purposes. Users with heavy analysis needs

should include the cost of a data warehouse in the ERP budget—and they

should expect to do quite a bit of work to make it run smoothly. Users are in a

pickle here: Refreshing all the ERP data in a big corporate data warehouse

daily is difficult, and ERP systems do a poor job of indicating which

information has changed from day to day, making selective warehouse

updates tough. One expensive solution is custom programming. The upshot is

that the wise will check all their data analysis needs before signing off on the

budget.

5. Consultants Ad Infinitum

When users fail to plan for disengagement, consulting fees run wild. To avoid

this, companies should identify objectives for which its consulting partners

must aim when training internal staff. Include metrics in the consultants'

contract; for example, a specific number of the user company's staff should be

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able to pass a project-management leadership test—similar to what Big Five

consultants have to pass to lead an ERP engagement.

6. Replacing Your Best and Brightest

It is accepted wisdom that ERP success depends on staffing the project with

the best and brightest from the business and IS. The software is too complex

and the business changes too dramatic to trust the project to just anyone. The

bad news is, a company must be prepared to replace many of those people

when the project is over. Though the ERP market is not as hot as it once was,

consulting firms and other companies that have lost their best people will be

hounding yours with higher salaries and bonus offers than you can afford—or

that your HR policies permit. Huddle with HR early on to develop a retention

bonus program and to create new salary strata for ERP veterans. If you let

them go, you'll wind up hiring them—or someone like them—back as

consultants for twice what you paid them in salaries.

7. Implementation Teams Can Never Stop

Most companies intend to treat their ERP implementations as they would any other

software project. Once the software is installed, they figure, the team will be

scuttled and everyone will go back to his or her day job. But after ERP, you can't

go home again. You're too valuable. Because they have worked intimately with

ERP, they know more about the sales process than the salespeople do and more

about the manufacturing process than the manufacturing people do. Companies

can't afford to send their project people back into the business because there's so

much to do after the ERP software is installed. Just writing reports to pull

information out of the new ERP system will keep the project team busy for a year

at least. And it is in analysis—and, one hopes, insight—that companies make their

money back on an ERP implementation. Unfortunately, few IS departments plan

for the frenzy of post-ERP installation activity, and fewer still build it into their

budgets when they start their ERP projects. Many are forced to beg for more

money and staff immediately after the go-live date, long before the ERP project

has demonstrated any benefit.

What does the company get?

When CFOs look at enterprise resource planning (ERP) spending projections,

their eyes often get as big as silver dollars. To reassure themselves that their

math isn't completely out of whack, most companies want to compare notes

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with someone who has already lived through an ERP project. "Total installed

cost is probably the hottest issue in the market right now; users want to gut-

check with someone else," says Chris Jones, research director of business

applications at Gartner Group Inc.

Unfortunately, a total cost number-even if you can find a company willing to

share its figures-won't necessarily mean much. Jones notes that everyone

delves into ERP from a unique situation, depending on hundreds of variables,

including the existing hardware and network infrastructure, the number of

corporate divisions and users, the specific functions targeted for the ERP

system and the amount of process redesign. The cost of the software itself is

universally known to be a small slice of the total project outlay.

One attempt at a useful comparison is to look at the total cost as a multiple of

the software cost. There's no consensus, however, on what that multiple

should be. Meta Group Inc.'s Barry Wilderman, a vice president of application

delivery strategies, for example, says ERP implementation costs should fall in

the range of $3 to $10 per dollar spent on the software itself. Such a wide

range offers little predictive value, other than serving as a red flag for users

who anticipate spending $15 per software dollar. And even the use of such

broad numeric ranges has skeptics. "Never use a rule of thumb. This nonsense

about one-to-one, two-to-one-that's exactly what it is: nonsense. There is no

such thing as a standard cost to implement ERP," says Gartner's Jones.

A different benchmark compares the cost per user. Monsanto Co.'s Gary Banks, IT

lead for the company's SAP implementation, says the overall price tag for ERP can

be intimidating. However, his unscientific survey indicates that while other

software projects typically have a lower overall price, the cost per user is higher

than with ERP because fewer employees benefit from other kinds of software.

Again, remember that many variables affect the cost-per-user number. "I'm sure it

could be done for less with a more aggressive implementation," says Banks, noting

that Monsanto has invested a lot of time in choosing the processes and business

models best suited for the company.

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Module 6 Introducing Financial Management

Information Systems in Developing

Countries

By

Jack Diamond and Pokar Khemani

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THE IMPORTANCE OF FINANCIAL MANAGEMENT INFORMATION

SYSTEMS (FMISS)

In most developing countries (DCs), budget execution and accounting processes

were/are either manual or supported by very old and inadequately maintained

software applications. This has had deleterious effects on the functioning of their

public expenditure management (PEM) systems, that are often not adequately

appreciated. The consequent lack of reliable and timely revenue and expenditure

data for budget planning, monitoring, expenditure control, and reporting has

negatively impacted budget management. The results have been a poorly

controlled commitment of government resources, often resulting in a large buildup

of arrears; excessive borrowing, pushing up interest rates and crowding out

private-sector investment; and misallocation of resources, undermining the

effectiveness and efficiency of service delivery. Further, governments have found

it difficult to provide an accurate, complete, and transparent account of their

financial position to parliament or to other interested parties, including donors and

the general public. This lack of information has hindered transparency and the

enforcement of accountability in government, and has only contributed to the

perceived governance problems in many of these countries.

In light of these adverse developments, it is perhaps not surprising that many DCs

have pressed for, or have been pressed into, adopting financial management

information system (FMIS) projects to strengthen their PEM systems. The

establishment of an FMIS has consequently become an important benchmark for

the country’s budget reform agenda, often regarded as a precondition for achieving

effective management of the budgetary resources. Although it is not a panacea, the

benefits of an FMIS could be argued to be profound. First, the improved recording

and processing of government financial transactions also allows prompt and

efficient access to reliable financial data. This supports enhanced transparency and

accountability of the executive to parliament, the general public, and other external

agencies. Second, an FMIS strengthens financial controls, facilitating a full and

updated picture of commitments and expenditure on a continuous basis. Once a

commitment is made, the system should be able to trace all the stages of the

transaction processing from budget releases, commitment, purchase, payment

request, reconciliation of bank statements, and accounting of expenditure. This

allows a comprehensive picture of budget execution. Third, it provides the

information to ensure improved efficiency and effectiveness of government

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financial management. Generally, increased availability of comprehensive

financial information on current and past performance assists budgetary control

and improved economic forecasting, planning, and budgeting.

FEATURES OF AN FMIS

In terms of terminology, an FMIS usually refers to computerization of public

expenditure management processes including budget formulation, budget

execution, and accounting with the help of a fully integrated system for financial

management of the line ministries (LMs) and other spending agencies. The full

system should also secure integration and communication with other relevant

information systems. Because of the integration requirement, the FMIS is

commonly characterized as an integrated financial management information

system (IFMIS). Unfortunately, using the term ―integrated financial management

information system‖ can sometimes be erroneously interpreted as describing a

system that can capture all the functional processes, and the relevant financial

flows, within public expenditure management. However, the complexity of

information systems within the government sector is, to a large extent, due to the

multiplicity of functions and policy areas.

In many functional areas specialized information systems are in place and will still

be required even with the implementation of an FMIS. It should be noted that in

this paper the term FMIS has been used generically to include an IFMIS.

As the name implies, there are, and should be, three guiding characteristics for a

well-designed FMIS:

• It is a management tool

When developing an FMIS it is important that it cater to management needs—not

just those of the central agencies, but also line agencies. Moreover, as a

management tool it should support the management of change. It must be viewed

as an integral part of budget system reform—hence not be designed just to meet

present requirements, but also to support those needs that are likely to arise as

parallel budget reforms are implemented.

• It should provide a wide range of nonfinancial and financial information

As a tool of management it should provide the information required for decision

making. For this purpose it is anchored in the government accounting system, and

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should be designed to perform all necessary accounting functions as well as

generate custom reports for internal and external use. However, this does not mean

that it should exclusively concentrate on financial information. Managers will

require other nonfinancial information. For example, personnel information such as

numbers of employees, their grade within the organizational structure and rates of

remuneration. For performance-based budgets, performance information will be

important to managers, such as the identification of programs, the objectives or

outcomes of programs, the types of goods and services produced, as well as

indicators by which to judge the efficiency and effectiveness of programs.

• It is a system

Its role is to connect, accumulate, process, and then provide information to all

parties in the budget system on a continuous basis. All participants in the system,

therefore, need to be able to access the system, and to derive the specific

information they require to carry out their different functions. The converse is also

true, if the FMIS does not provide the required information—that is, has not the

right functionality—it will not be used, and will cease to fulfill its central function

as a system. Further, by automating procedures and internal controls, it strengthens

financial controls and promotes accountability.

Attributes of a Well-Designed FMIS

The FMIS should:

• be modular, and capable of progressive upgrading to cater to future needs;

• offer a common platform and user interface to the stakeholders in different

agencies responsible for financial management, for adding to and accessing the

information database (in its absence each agency will have the incentive to develop

―its own‖ FMIS to meet its currently perceived needs);

• maintain a historical database of budget and expenditure plans; transaction data at

the highest level of detail; cash flows and bank account operations including

checks issued, cancelled, and paid, cash balances and floats;

• have dedicated modules to handle monthly, rolling, short-term (one to three

months) and longer-term (three months to end of year) forward estimates of

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revenues, and expenditures prepared by agencies, and corresponding estimates of

the resulting cash flows;

• have built-in analytical tools to offer trend analysis of various elements of fiscal

operations to permit a forward look at the emerging events bearing on the fiscal

stance;

• compile formal government accounts from the database of authorizations and

cash allocations, primary revenue and expenditure transactions of the agencies; and

treasury operations, avoiding the need to duplicate data entry for accounting

purposes;

• enable real-time reconciliation of parallel but related streams of transaction

data—at the agency level: checks issued with those paid by the banks; at treasury:

receipts from banks with the checks paid by taxpayers; cash balances reflected in

the agency ledgers with the cash balances in the banks;

• mechanize all possible routine tasks at the central and spending agencies—

generating various forms/authorizations, checks, outputting hard copies of key

registers and statements, etc.; and

• be flexible enough to provide user-defined management information, aggregated

at the desired level of detail, from the database.

Although the FMIS does not capture all the information flows, adopting a

comprehensive approach in the development of the project is fundamental to

ensure that all functional interdependencies are identified, hence securing the

capture of all related information flows.

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Figure 1 sets the FMIS in a broader context of interrelated information systems,

and illustrates the main functional processes from medium-term planning and

budget preparation to budget execution and accounting.

Institutional Framework, Processes and Information Flows

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An FMIS will consist of several elements with different functions. In the

description that follows, the term ―module‖ will imply that the system is a sub-

element in a FMIS. The core of an FMIS could be expected to include the

following modules and systems:

• General ledger,

• Budgetary accounting

• Accounts payable

• Accounts receivable

The noncore or other modules are, inter alia:

• Payroll system

• Budget development

• Procurement

• Project ledger

• Asset module.

It is important to set priorities for the system implementation, that will usually start

with the core functions, namely budget execution, accounting, payment processing;

commitment control and financial reporting.

STRATEGIC FRAMEWORK FOR INTRODUCING AN FMIS IN A DEVELOPING

COUNTRY

The introduction of an FMIS in a developing country should be regarded as part of

a long process of reform. This process takes years to fully implement, costs

millions of dollars, and has a substantial recurring operating cost. Thus FMIS

should be regarded as a major project requiring a structured project management

approach.1 Viewed in this way there are four main stages in the process of

introducing an FMIS, which are presented in Figure 2: preparation, design,

procurement, and pilot and roll-out.

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Main Steps in Introducing an FMIS

Stage 1: Preparatory

- Preliminary concept design including an institutional and organizational

assessment

- Analysis of the key problem areas and ongoing reform programs

- Feasibility study

- Design project and draft project proposal

- Formal approval of the project-securing government approval and donors’

funding

Stage 2: Design

- Develop functional specification

- Outline information technology (IT) strategy, including hardware and

organizational issues

- Prepare tender documents

Stage 3: Procurement

- Issue tenders for hardware and software and associated requirements

- Evaluation of bids and award contract

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Stage 4: Implementation

- Configuration analysis and specify any additional IT, infrastructure, and

communication requirements

- Detailed business process and gap analysis mapping required functionality to

package and identifying and specifying detailed parameterization, customization,

procedural etc, changes

- Detailed action plan for phased implementation and the pilot-run of the system

- Agreed customization and configuration of the system

- Determine training needs and conduct training of personnel

- Pilot run—parallel run of the system, resolve initial problems and evaluate

system performance for roll-out

- Roll-out system to other ministries and agencies

- Phased implementation of additional modules

- Strengthening of internal system support and phasing out consultant/contractor

support

These four stages describe the main process followed in the design, procurement,

and implementation of an FMIS. As indicated in Figure 2, the successful

implementation of this process also requires three supporting elements: sound

project management; adequate resources and complementary organizational

development; and parallel improvements in business procedures and practices

supported by a suitable legal and regulatory framework. These supporting reforms

should not be neglected in FMIS design and implementation, and without them it

will not be possible to achieve the full benefits of an FMIS.

IV. REQUIREMENTS FOR INTRODUCING AN FMIS

Given the problems often encountered in FMIS projects, it is useful to specify in some detail the

essential requirements that should be met. As indicated, these requirements have been grouped in

three categories:

(i) Project management;

(ii) Organizational development;

(iii) Parallel reforms.

A. Project Management

As explained earlier, the whole process of developing an FMIS should be regarded

as a major project requiring a structured project management approach. The

essential elements of a sound project management are described below.

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Commitment, participation, and management model

The implementation of a government-wide FMIS is a substantial undertaking for

any administration, and it is essential that the participants are fully aware of the

magnitude of the undertaking. Ensuring project commitment at the highest levels of

the political system and bureaucracy, and continuous participation from the direct

users of the system and other stakeholders, is necessary in all phases of the project.

It is also necessary that the project planning methodologies are used to plan,

implement, and monitor the project, with project management responsibilities

clearly identified. The management model needs to ensure broad in-house

participation and involvement of all the relevant stakeholders, which usually are

the ministry of finance and other central agencies, the office of the auditor general,

the central bank and other banks handling government business, LMs, and local

governments. The finance minister, assisted by the permanent secretary

(PS/Finance) needs to take primary responsibility for overall management of the

project. Since accounting is the backbone of the information system, the treasury

that is in charge of this function—or in the Anglophone countries, the accountant

general (AG)—is a key institution. Under PS direction, the AG is usually asked to

take the lead role in the design, development, procurement, training, and

implementation processes relating to the FMIS. Typically the AG must also

collaborate with the head of the central information technology (IT) department in

the design, development, and implementation processes.

It is critical to mobilize internal management resources. The PS/Finance and the

AG should be assisted by a well-staffed project management team headed by a

full-time project manager. The project manager should be supported by a full-time

technical team consisting of a number of assistant project managers, with

specializations in IT, budgetary and accounting processes. To ensure continuous

commitment participation of top politicians and key stakeholders, it would be

useful to set up a steering committee under the chairmanship of the finance

minister to manage and coordinate the entire process of design, development, and

implementation of the FMIS. The committee should have considerable and

authoritative influence, and should meet on a monthly/quarterly basis depending on

the project progress.

The cabinet and the parliament also need to be informed periodically by the

steering committee on the progress in the implementation of the FMIS.

Necessary measures should also be taken to strengthen the capacity in the project

team as well as the AG’s office and the budget office through all project phases.

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Simultaneously, it is also necessary to develop the necessary skills and capacity of

the central IT department to provide strong support to the system. Continuity of

key personnel involved in the development and implementation processes is also

important for the success of the project.

Strategy for use of external consultants

In addition to in-house resources, an FMIS project requires careful choice of

external technical assistance during different parts of the process. The external

consultant should have extensive experience in public sector financial management

including:

• The design, implementation, management, and operation of government

accounting, budget, and financial management systems in a developing country

environment.

• Experience in the management and operation of modern computerized financial

systems in a government budgeting and accounting environment.

• Complementary experience in training, management development, human

resource management, and organizational change in developing countries.

• Experience in project management and implementation, working in the advisory

and training capacity in developing countries.

The external consultants need to be managed closely because they may tend to

pursue their own interests. They should be required to make extensive use of local

consulting or training organizations and in-house resources. The in-house

resources should be fully involved in the project design and planning, technical

implementation skills for both hardware and software, user support skills, etc.

Comprehensive perspective maintained with a modular approach

Although the implementation of an FMIS should be carried out in a modular way,

to avoid too much strain on the capacity of organizations; it is important to keep a

strategic and comprehensive view in the overall process of its planning and

development. International experience in implementing FMISs indicates that these

projects often lead to temporary disruptions of the normal functions in the budget

and accounts departments. This disruption may last for a period of 9 to 12 months,

depending on the absorptive capacities of the organizations involved. The time

schedule for the entire project can be expected to be approximately four to five

years after all the resources, including consultants, is appointed.

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Coordination with other development projects

The development of an FMIS in a country is typically part of a comprehensive

PEM reform strategy. Other important components relating to PEM reform are the

development of a medium-term budget framework (MTBF); the design,

procurement and implementation of a payroll and personnel administration system;

and the development of an auditing system. In addition, there are some other

initiatives for donor funded projects in individual LMs and local governments. It is

essential that all of these initiatives be coordinated at a senior central level, so as to

avoid duplication of effort and to ensure consistency of outputs. It is also equally

important to relate PEM reforms to other reforms in the public sector and the

improved delivery of public services.

B. Organizational Development

At the outset of an FMIS project, it is necessary to ensure the availability of

adequate financial resources. Experience has shown that the lack of sufficient

resources can serve as a serious obstacle to the successful implementation of the

project. Further, there is a need to clarify the future roles and responsibility for

different functions. Some of these critical functions are given below:

• System and data administration. Coordinating mechanisms should be created

to ensure that a common set of policies, procedures, and standards are in place for

managing data and systems government-wide. This could be achieved by

developing a national IT strategy, including the use of Information Technology and

Information Systems (IT/IS) in the public service.

• Wide consultation and acceptance. To be successful, the organization needs to

be prepared for the introduction of the FMIS and be willing to recognize and

accept the benefits that the changes will bring about and the costs of

implementation in their widest sense. The continuous consultation within

government departments is essential. This would be possible with the help of a

strong champion for the reforms.

• New job descriptions in ministries, departments, and provinces. An FMIS

will induce changes in the working environment. As a consequence of these

changes, new job descriptions or working processes should be formalized. The

civil service should be willing to accept that the FMIS would significantly change

their influence and responsibilities. As an example, the operations in the processing

of financial transactions will change dramatically from manual book-keeping to

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automated operations and processes. The role of both the head of finance and

accounting functions, and the auditors (internal as well external) will also clearly

change.

• Motivation. Defining and deciding upon new structures and working practices is

one thing, but implementing them is another. The challenges in organizational

development are multiple. For successful implementation, the stakeholders need to

participate and be motivated. Motivation and support for the decision of

implementing the new FMIS are critical. Participation, information, and adequate

training will often strengthen this support.

• Training. The training for the staff will not only include training in use of the

FMIS for their respective operations and functions, but also training in the new

legal and regulatory framework, the new codes and classifications, and the new

business procedures put in place. In the initial stage of implementation, there is a

need to develop new practices, and the associated training requires a great deal of

innovation and tailoring to the specific features and capacity of the organization. A

large proportion of the training should be on-the-job training, and be focused on

―super-users.‖ This implies decentralized on-the-job trainers deployed throughout

the implementation period. User support is also necessary as a permanent service.

• Change management. The FMIS steering committee needs to develop a change

strategy and establish a clear and agreed approach and timetable for implementing

the various changes associated with the system. Implementation needs to be phased

and flexible, and it is necessary for the ministry of finance to take a lead

coordinating role in the whole process. Donors are inevitably required to provide

technical and financial support for the entire process.

C. Parallel Reforms and Improvements to Business

Processes

Another significant concern is that without the essential PEM reforms in place, or

in the process of being implemented, no major gain will accrue from an FMIS.

There is little advantage in introducing an FMIS that merely follows existing PEM

working processes and practices. Restructuring of working processes and practices

requires new procedures to be formalized and unified throughout the government.

In developing countries there often is a lack of financial discipline, which also

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represents an important challenge. An FMIS is effective only if the underlying

budgetary and accounting systems are robust and well managed.

At the same time an FMIS can be a vehicle for change. Experience indicates that

an FMIS will induce several reforms in existing systems, including:

• Structure of the budget and the accounts. Introducing an FMIS necessitates

unifying the codes and classifications (both the budget classification and the chart

of accounts). These should be maintained at a central level. The reporting

requirements are the basis for defining the structures of these codes and

classifications. The new budget classification structure and chart of accounts

should be compliant with the classification framework in the IMF’s Government

Finance Statistics Manual 2001

Main budgeting and accounting principles. Typically, a number of DCs use a

single-entry accounting system in a manual mode, with the budgeting and

accounting system on a cash basis. Off-the-shelf systems are normally designed for

accrual accounting. With the implementation of an FMIS, financial transactions

will be entered into the accounts payable and accounts receivable modules with the

due dates, thus allowing for a gradual move toward an accrual basis. The DCs

could take a step toward modified cash basis accounting, while keeping the budget

on a cash basis in the early stages of implementing the FMIS.

• Cash management. To ensure that the budget and accounts are comprehensive,

it is essential that all the cash flows be channeled through the FMIS, and hence that

all transactions, both receipts and payments, are processed by the FMIS, including

the payroll payments. The FMIS could also aim at rationalizing the government

banking arrangements and establishing a treasury single account for optimizing the

management of government cash balances.

• Control structure. The design of the FMIS should introduce an improved system

of internal and external controls for financial management. The internal controls

regulate the cycle of recording, analyzing, classifying, summarizing,

communicating, and interpreting financial information. The internal audit function

helps the management in evaluating and assessing compliance with these controls.

The external control system is exercised through external auditing carried out by

the supreme audit institution.

Legal framework.

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While designing the FMIS, it is necessary to review the regulatory and legal

framework and agree on the necessary modifications to the overall framework for

government fiscal management. A legislative framework (Constitution, Finance

Act and Regulations) needs to include:

(i) the roles and responsibilities of the treasury, ministry of finance (MOF),

other ministries, and other stakeholders responsible for the control and

management of public finance;

(ii) the main form of government funds, receipt and custody of public funds, the

annual process, submission and approval of estimates and the procedures

for release of funds;

(iii) the basis of accounting and the form of annual accounts for audit and

presentation to Parliament; and

(iv) asset management and control; borrowing and investment.

V. COUNTRY EXPERIENCES WITH THE

IMPLEMENTATION OF FMISS

Given the extensive requirements for successful implementation of FMIS projects,

it is perhaps not surprising that these have proved particularly demanding on DC

administrations.

A small sample of project experience in Anglophone African countries highlights

some of the critical factors determining success or failure.

A. Tanzania

Since 1994 the government of Tanzania has implemented an ambitious reform

program to improve public sector financial management, which initially focused on

introducing effective and efficient budget formulation and expenditure

management systems and processes.

Specifically, two projects financed by the Swedish International Development

Agency (SIDA) were designed—the Government Accounting Development

Project (GADP) focusing on budget execution and the Interim Budget

Development Project (IBDP) focusing on budget formulation. In 1996, following

chronic problems in the financial management of the government, a decision was

taken to abolish all payment offices in the ministries, departments, and agencies

(MDAs), and establish a central payment system, and thereby obviate the need for

MDAs to have individual bank accounts.

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In 1998/99, the government decided to introduce an Integrated Financial

Management System (IFMS) in ten selected MDAs. Under this system, a central

server was placed at the treasury (in the Office of the Accountant General (AG)) to

which users were connected by a dedicated network. Also work stations were

provided for each of the MDAs from which they could access the system. Each

MDA had its own database held in the omnibus database in the central server.

MDAs’ transactions automatically update the database in real time, and thus the

general ledgers reflect the real position of balances at any particular point. By the

end of 2000 there were over 500 users of the system at more than 85 sites

throughout Tanzania. The system has now become the generic public sector

financial management system used by the entire public sector. At the local

government level, the system has been introduced to 32 local authorities, and a

roll-out to an additional 30 authorities was expected to be completed by the end of

2004.

The software package for the IFMS is a medium-sized financial management and

accounting package (Platinum SQL Financials from EPICOR). At present, the

IFMS is only using a few modules, namely General Ledger, Accounts Payable,

Accounts Receivable, Cash Management, Purchase Order, Multi-currency, Budget

Module, Foreign exchange report writer, and Crystal report writer. The accounts

are essentially maintained on a cash basis, though the authorities are planning to

use other modules like Asset and Inventory Management, and are working toward

accrual accounting.

The benefits of the IFMS have been extensive, with the restoration of expenditure

control and improved levels of transparency and accountability. The Commitment

Control System has led to the elimination of overspending, and a substantial

reduction in domestic arrears. A number of government bank accounts have been

reduced to treasury single accounts maintained at the central bank, and the lag in

reconciliation with banking data has been reduced from up to two years to

automatic reconciliation on a daily basis. Comprehensive and fully reconciled

fiscal data and reports are available on a continuous basis.

Currently, the IFMS in Tanzania appears to be the most successfully implemented

system in Anglophone African countries. Its implementation was distinguished by:

• An initial review of the PEM processes affecting budget execution, and the

introduction of an improved expenditure control framework and chart of accounts;

• Embedding the reform process in the MOF combined with an emphasis on

capacity building, particularly in the AG’s department, through training,

restructuring, and computerization;

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• Revising, developing and managing enabling legislation, accounting principles,

systems and organizational arrangements necessary for the management of

government budgetary and accounting systems;

• Selecting a mid range commercial software package, supported by a high quality

local consultancy company, an EPICOR partner, that provided a strong support to

the implementation process including training;

• Availability of adequate donors’ resources, combined with very experienced

international and local consultants;

• A solid backing at the political level, which trickled down to the management

level; with both political and management commitment being strong throughout

the entire reform process.

In Tanzania both the authorities and donors perceive the IFMS as a critical tool for

achieving accountability in the public sector. Donors are now more receptive to the

idea of using government systems to channel funds than ever before. However

there is a need to consolidate and deepen the system and build the capacity to

ensure its long-term sustainability. The system is primarily performing basic

budgeting and accounting functions, and other modules like Asset Management

and Inventory Management need to be implemented. Further, the system also

needs to be interfaced and achieve integration with other main systems like

Personnel Management and Debt Management systems

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B. Ghana

The government of Ghana launched an ambitious multi-faceted Public Financial

Management Reform Program (PUFMARP) in 1996, which aimed to introduce

comprehensive reforms to the budget and expenditure management processes. The

main components of the PUFMARP include the introduction of a medium-term

expenditure framework (MTEF) and the development of a computerized

government financial management information system, termed the Budget and

Public Expenditure Management System (BPEMS). In the early years of the

reform program, there was a mismatch between the (fast) rate of progress with the

MTEF and the (slow) progress on the BPEMS, The faster development of the

MTEF, relative to the BPEMS, caused significant accounting and reporting

problems. The new chart of accounts introduced by the MTEF was not coordinated

with a similar change in the then existing accounting system, although this was

rectified after a period of almost two years. However significant progress has been

made in strengthening the budget and expenditure management processes over the

past five years. In particular, the authorities have progressed from satisfying 1 of

15 Heavily Indebted Poor Countries (HIPC)

Assessment and Action Plan (AAP) benchmarks in 2001, to meeting 7 of 16

benchmarks in 2004, including building a sound regulatory and institutional

framework under PUFMARP.

In Ghana, the experience of the design, development, and pilot implementation of

the

BPEMS has not been satisfying. In the design of the BPEMS, the existing manual

budget execution and accounting processes seem to have been automated to a large

extent, without consideration of whether there was a better and more efficient

method of achieving the required result. The original plan to roll out the system by

the end of fiscal year 2001 was not achieved due to a number of factors. After

considerable delays, the system was installed, on a pilot basis, at the MOF and the

Controller and Accountant General’s Department (CAGD) in

January 2003. The roll-out for additional ministries of Education and Health

(planned before the end of 2003) was carried out in March/April 2004.

Despite substantial time spent in developing and customizing the software

application, the pilot implementation and the roll-out of the system has not

progressed well. The MOF and the CAGD are not fully satisfied with the BPEMS

reporting system, and this has been a major area of dispute between the

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government and the software team. There were also problems with the new

managers (Close Communications) hired by the government for implementing the

system.

The overarching concern is the significant delay, and limited involvement and

ownership of the BPEMS by the various stakeholders in the design and

development of the BPEMS.

Somehow, the development process was largely driven by consultants and donors

in the formative period of the project. The BPEMS had to be restructured several

times, and encountered significant design and implementation problems and

delays. The project implementation unit was also restructured several times, and

there have been a number of changes in the program coordinator and program

manager. Local capacity and know-how has always been and is still the major

issue, and the government still relies on the assistance of local vendors.7

Consequently several significant issues need to be addressed before BPEMS can be

made fully functional and rolled out.

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C. Uganda

The government of Uganda is in the process of implementing a comprehensive

financial management reform program to improve the budget and expenditure

management processes at the central and decentralized government levels. In the

early years, for a number of reasons, there were considerable delays in the

completion of the design and development phase of the FMIS. Finally, the

procurement and evaluation process was completed in February 2003 with the

award of a contract8 for the provision of a turnkey solution including hardware,

application software, a Wide Area Network (WAN), and supporting

training/change management.

The implementation of the system began in March 2003 with the mapping and

necessary configuration followed by user acceptance and testing operations in

February 2004. The pilot implementation phase is currently in progress in six line

ministries and four local governments. The pilot implementation covers the core

modules of the application, namely Budget Management, Purchase Order,

Accounts Payable, Accounts Receivable, Cash Management, General Ledger, and

Financial Reporting. The software package is essentially accrual based; however

the system provides a facility to allow the generation of cash based year-end

financial statements to meet the audit requirements.

An assessment of the pilot implementation is in progress before the system is

rolled out to other line ministries. The pilot-run has brought out a number of issues

in the system functionality, as well as treasury procedures, and these need to be

resolved before closing the pilot phase.

The roll-out9 has been planned in two phases—the second phase will cover all line

ministries and six additional local governments; and the third phase will cover the

remaining local governments. The full implementation may take another three to

four years. It is necessary to complete the roll-out of the system to the whole

government and ensure long term sustainability to reap the full benefits of the

system by: (i) ensuring the availability of adequate resources in terms of staff

capacity and maintenance budget, and (ii) progressively extending and deepening

the functionality and utilization of the system.

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D. Malawi

Since 1995, the government of Malawi has introduced a number of initiatives to

improve public expenditure management, most notably the medium-term

expenditure framework to improve the budget process, and the Integrated Financial

Management Information System (IFMIS) to computerize the budgetary and

accounting processes. In the latter case, the conceptual framework including

technical specifications was completed in time. The governance structures

including the steering committee, the project management team, and the

implementation structure between the contractor and the government were properly

set up.

The design and procurement process was completed in 2000 with the purchase of a

package solution, and the pilot run of the customized software started in 2001.

There have been significant implementation delays, and the pilot implementation is

yet to be approved by the government as successful. The pilot implementation did

not follow the standard implementation methodology for this type of software.

Some of the planned core modules for implementation have not been completed,

while others have not been implemented at all.

This project has encountered numerous difficulties. The project implementation

team was not well resourced, and was dismantled even before the implementation

was completed. Change management and communication activities did not receive

adequate attention, and there are inconsistent views within the implementation

team and implementing ministries. The software support arrangements have

changed over the years, and there have been various contracts for implementation

activities. Some of the contractual work has not been properly fulfilled. The

auditing aspects of the system have not been adequately planned and tested for live

operations. A fast review of the system conducted by the AG with the help of an

outside expert in July 2004 revealed a number of problems with the functionality

of the system, so that the roll-out has been delayed until the problems have been

resolved. These problems included serious deficiencies in expenditure control and

tracking processes.

In general, the implementation phase has not progressed well, primarily because of

clearly limited involvement and some neglect of the system by the main players,

including the MOF, AG and pilot ministries. There are several significant issues to

be addressed before the system can be made fully functional and rolled out.

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E. Kenya

Since 1997, the government of Kenya has been implementing a project for the

―strengthening of government finance and accounting functions‖ to improve

financial management, accountability, and transparency of public funds. During

the first two phases over the first three years, a number of diagnostic reviews were

conducted and a Financial Management Information Systems Strategy was

developed.

Following a procurement delay of almost two years, a contract for the purchase of

the software implementation was finally awarded during late 2002. Hardware

procurement was undertaken separately from the software. The pilot phase started

with the setting up of core procurement and accounting modules in the treasury as

well as two pilot ministries during 2003/04. The project is still in the final stages of

pilot testing, and the roll-out of the system is stalled due to lack of IT and

communications wide-area network architecture.

Further, the implementation of the budgeting and cash management modules has

been delayed for a number of reasons, and their pilot testing may commence with

the 2005/06 budget cycle.

The pilot implementation has raised a number of issues. The engagement of

internal and external audit staff has been inadequate, resulting in limited quality

control assurance. The revised classification and chart of accounts developed for

FMIS is not fully consistent with the IMF’s GFSM 2001 standards, and it is

necessary to eliminate inconsistencies and ensure conformity with that rubric.

Further, the new classification structure is still to be adopted for compilation of the

budget estimates.

Most important, the project management needs to be strengthened to ensure

strategic direction, leadership, and communication. Given this situation, the fiscal

year 2004/05 continues to be a pilot testing period, and being utilized for resolving

the current outstanding software and IT issues.

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WHY DO FMIS PROJECTS STALL IN DEVELOPING COUNTRIES? The above review of past experience in introducing an FMIS in DCs gives some

guidance on the key issues to be addressed, and also highlights some risks that

should be avoided. The following issues, in particular, that have contributed to the

limited success of FMIS projects may be worth noting in the DC context.

Lack of clarity in ownership of the system and unclear authority to implement

Public expenditure management in DCs is often segmented institutionally on

vertical rather than horizontal lines. For example, even when the MOF has been

given clear leadership, in Anglophone Africa it is not immediately clear who

should be in charge of an FMIS project- the MOF proper, in charge of budget

management, or the Accountant General’s Department, typically institutionally

separated, in charge of government accounting. Both bodies could be considered as

sharing a central role in the development and running of the new FMIS. The AG

has significant regulatory and control functions, while the Budget Department has

the dominant role in resource allocation. Although, it could be recommended that

these two bodies be nominated as joint owners of the new FMIS to ensure balanced

requirements for the system, at the same time joint ownership may involve a loss in

accountability and real ownership of the system. To counter this it is important to

get support for and commitment to the project at the highest level, say the minister

of finance or his deputy. This is important not only to resolve the identified

―ownership‖ problems, but in DCs to signal authority to push through government-

wide reforms in the face of strong ministries that may feel threatened by the level

of transparency that a FMIS imposes on them.

Failure to clearly specify the basic functionality

As a tool of management, an FMIS must be carefully designed to meet agencies’

needs, or functional requirements. Often this original design phase is the most

difficult part of an FMIS project, and does not receive the attention it merits. The

functional requirements document serves as the blueprint for later phases of the

FMIS project. It describes the accounting and financial management tasks the

system must perform, the agency’s information requirements, the operating

environment, and a plan for developing any necessary programming.

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The failure to spend enough time on the design phase

The functional requirements document that serves as the blueprint for later phases

of the system project is critical—if wrong, it is difficult to rectify the situation

later. Requirements analysis is important but tends to be an often neglected step. It

cannot be rushed: for the accounting function alone, a detailed analysis can take

three months to a year.

It is essential that sufficient time be taken during the planning of the project to list

all user requirements for information to be derived from the FMIS. This part of the

planning phase is time consuming but is essential if the building of the system is to

proceed smoothly. It is usual for all users of the system initially to simply list all

possible information requirements that they seek from the FMIS. A process of

review by a panel of major users would result in a rationalizing of the requirements

to a manageable level. Most important, managers should tell vendors what is

required and not the other way round. It also must be recognized that it is unusual

for one system to service the information requirements of all users. Although this

phase is crucial to the success of the project, it cannot be allowed to run too long

and encroach on the time available for the actual building of the system.

In the DC context this model approach poses some problems. Without a degree of

exposure to a modern PEM environment, what can be realistically expected of

managers in specifying such requirements? Often computerization is being

introduced with fundamental changes to current work practices. Without prior

experience, how can these managers anticipate the implications of these reforms?

Can managers really be expected to plan for these changes and be capable of

mapping out how their organization will get from where it is now to where it has to

be in a computerized environment? Not surprisingly, in these circumstances the

system requirements document is often externally generated, and much influenced

by the vendors.

Ideally, it should be the rule that any outside consultancy at this stage should be

independent of potential vendors, undertaken by business rather than IT experts,

and be developed in conjunction with the staff in the ministry to cater for local

conditions. In practice in DCs there may be a lack of capacity in the host MOF to

fully operationalize this approach.

Failure to reengineer procedures

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Establishing an FMIS should not be viewed as merely computerizing existing

procedures.

Peterson et al. (1996) make the case that computerization promotes two kinds of

reform: efficiency reforms that accelerate the operation of existing procedures and

effectiveness reforms that change existing procedures. Strassmann (1985) contends

that the real payoff from IT is when it makes organizations more effective, not

simply more efficient. Introducing an FMIS should thus be viewed as an

organizational reform. Redesigning information flows—the way those flows are

processed, managed, distributed, and used for decisions—usually requires

changing operating procedures.12 Inevitably, the disruption of well-established

operating procedures can feel threatening to individuals who operate them, and

hence it should not be surprising that such innovation is resisted.

In DCs this resistance is compounded by the lack of experience with computers.

The tendency to leave system development to the computer supplier often means

that these organizational issues are downplayed, and technical considerations

dominate in the design and implementation of the project. The result is often a

tendency for over sophistication at the expense of user friendliness. Clearly, there

is a tension in going for state of the art computerization that will protect the

investment against early obsolescence, as opposed to the need for initially

introducing systems that are user friendly with modest achievable goals, but

subsequently capable of enhancement as user skills, familiarity, and confidence

grow. Often the degree of IT sophistication has assumed too steep a learning curve

for DC users.

The failure to undertake parallel reforms required by the FMIS

As argued before, the aim of an FMIS should not be to computerize the present

processes but to improve work practices. The reform of business practices should

be a top priority, but too often there exists a blind belief that computers will solve

all problems. At a minimum, reform requires substantial groundwork to

standardize manual procedures, including documentation used and processing rules

across all users, redesigning and strengthening internal controls, and redesigning

reports and other analytical outputs. However, more substantial reforms will take

more time. For example, a new FMIS is likely to be most productive when it

incorporates major upgrades in accounting. Accordingly, it may be important to

review government accounting standards well in advance, and perhaps to consult

national accounting bodies regarding the consistency of public and private sector

standards in regard to the accounting system.

The neglect to ―sell‖ the system to agencies

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It is crucial for the successful implementation of the new FMIS that agencies

accept the need for the new system and that it will provide useful information to

assist managers in the management of their agencies. If the FMIS is seen as a

centrally imposed tool to further control agencies, then its successful

implementation will be threatened. Any agencies that currently have well-

developed management information systems should be particularly targeted for

selling the advantages of the new system. It is, of course, advisable that those

agencies be included on the previously mentioned steering committee.

Overestimating the information to be included in the system

There is often a tendency to be too ambitious so that the intended scope of the

FMIS is too wide and attempts to service all the requirements of potential users.

The user specification stage discussed earlier should be used to determine what are

the critical requirements for the initial version of the system and what could be left

to later versions or removed from the user requirements, since they are not

regarded as essential for a cross-agency FMIS.

Unrealistically short project timetable

Implementing complex FMIS projects takes time. The steps in the project are well

known: preparatory requirements analysis, system design, development and

testing; procurement and installation; testing of the full system in the user

environment, training and conversion. As indicated, it is also well known that the

time required for the completion of each step is often grossly underestimated,

especially in DCs. In the past, there has been a tendency to tell top management

what they want to hear. This is reinforced by top managers’ short political time

horizon when judging reform payoffs. While this might be one reason for the

underestimation of time required, additionally, the inertia of development agency

bureaucracies, coupled with delays inherent in the implementation of complex IT

systems, is a disastrous combination. Moreover, owing to the human resource

shortages faced by DCs, it will take them much longer to introduce IT systems than

in more advanced countries— experience suggests perhaps two to three times as

long.

The required management input is often underestimated

The experience of advanced countries is that managing complex FMIS projects

requires considerable management skill. However, this is typically in short supply

in DCs. Senior managers in DCs rarely delegate responsibility and frequently are

overloaded with work.

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Moreover, top managers may not be computer literate. The consequence is that

often the binding constraint when introducing FMISs is not the technical capacity

to create them but the capacity to manage them. Nor is it clear that there is always

a good alignment in the incentive structure facing managers.

Bugler and Bretchsneider (1993), from the experience of IT reforms in state and

local governments in the United States, concluded that the reforms were most

likely to succeed if they have the following features: they are easy to use by the

manager; they address an external reporting requirement by the manager; and they

are confined to the manager’s area of concern. These requirements are hard to

attain in an DC, where top managers lack experience in computerized accounting

and are therefore unable to grasp its possibilities for financial management. In DCs

in the absence of computer literacy there is a tendency to leave the system

development to the computer supplier, with minimal user involvement. In such an

environment there is every likelihood that systems will not be user friendly, will

not match the needs of the managers, and will not have a required level of

management ownership.

Lack of incentives for reform

To get FMIS reforms accepted, decision makers must first be sold the idea that the

benefits exceed risk. However, officials tend to be risk averse—introducing

computer technology is an innovation that is perceived as risky. It is complex, it

demands skilled staff, and it needs procedural changes. There is plenty of evidence

of past failure. At the same time, in DCs the

IT is usually introduced by expatriates, so there is room for distrust, even hostility.

Second, decision makers must be convinced it is needed, i.e., that there is a

problem that exists and, therefore, needs to be addressed. Basing a reform on

conditions imposed by donors, as has sometimes been the case in Africa, does not

increase success. Third, decision makers should recognize the urgency of the

reform or the need for prompt implementation—often this perception is lacking at

the top. Fourth, managers may steer away from difficult personnel issues. Almost

inevitably, moving from manual systems to an FMIS allows government to fulfill

the same function with fewer staff. To operate the new system will also typically

require different types of skill. However, in most DCs managers in government

cannot reduce staff and are severely limited in their capacity to change them. In

such situations IT is not necessarily seen as a benefit to management, if anything

from human resource viewpoint it could make their task greater and more complex.

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Prerequisites do not exist

To successfully develop an FMIS, the project must be solidly based on some basic

data on how the present system operates. In the DC context, information on which

to base FMIS project decisions is often inadequate, although a leading cause of this

is more fundamental: the lack of capacity within implementing agencies. Also

there is a low level of computer literacy in the country, which must first be built up

before such projects are truly viable, and sustainable, especially when applied

government-wide. A computerized system’s greater reliance on communications,

which are admittedly poor in many DCs, may be another constraint.

It is also important to ensure that measures are taken for the project to be

sustainable. It should be recognized that there are recurrent costs associated with

the maintenance and operation of major FMISs that must be covered in budgets

and that often are not considered.

However, perhaps a greater constraint on sustainability arises from inadequate

human resources. To overcome this constraint may require a major training

program, which again will take time, but may not necessarily deliver the pay-off

anticipated. In most DCs there is a general shortage of skilled labor, and efforts to

improve skills in government are often frustrated by the migration of labor to the

private sector for higher pay when workers have acquired sufficient skills.

Is it necessary to get the pay structure right before embarking on such a training

program?

This consideration is particularly important for in-house IT capacity, and is a

concern faced by developed and developing countries alike. While most FMIS

tenders specify a requirement for the vendor to maintain the system for an initial

period (usually up to three years), there is also a need for IT capacity in

government. Expertise is required for interacting with vendors, to maintain the

system and to have adequate data management skills to optimize the system once

established. Often this is insufficient to provide the required service to users. Faced

with the poor pay scales mentioned previously, one solution is simply to pay

retention bonuses to IT staff, another to outsource the management of IT to a local

firm, and yet another is to establish a dedicated government unit to provide IT

services to the public sector that allow higher salaries than the average in the

public sector. None of these solutions is without problems, which tend to be

exacerbated in the DC context, where there is often a lack of competition in this

area. Thus, while recognizing FMISs may be the medium-term solution to many

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PEM problems, it is likely to be important to first spend the time in the short run in

creating a solid base for success.

I. The Functions of Different Modules in a Typical FMIS

A. Core Functions

1. General ledger

The general ledger (G/L) module is the foundation of an integrated FMIS. The G/L

should record all financial transactions—starting with the allocation of budget

funds through the commitments to the payment of goods and services. This module

should provide a complete picture of assets and liabilities of the government, as

well as associated financial flows. The system should be highly integrated with all

other modules of the FMIS as well other systems, if any, that process government

financial transactions. The system should facilitate simultaneous posting of all the

transactions in the general ledger accounts and in all appropriate subledgers

following the rules imposed by a chart of accounts. The system must include

facilities for automatic consolidation of accounts of different budget units at

different levels of government. The G/L system must have a strong reporting

facility to produce all types of financial reports, both for use by internal

management and external agencies.

2. Budgetary accounting

This module should assist in accurate recording of the approved budget, as well as

revisions to the approved budget authorized by the legislature. The system should

follow the full classification of the budget, with a facility to incorporate further

enhancements to classifications. In the case where the approved budget is not

available at the beginning of the year, the system should allow recording of interim

budget appropriations per subhead and allow for its replacement in due course by

the approved budget appropriations. The system should record the transfers

between appropriations and reallocations/virements between different subheads as

approved by the MOF during the course of the year. A historic record of the

original budget, transfers, and virements should also be maintained. The system

should facilitate maintenance of cash flow forecasts, prepared on the basis of the

approved budget and updated through the year based on the revisions, budget

transfers, and virements. The system should link the budget classification with the

standard functional and economic classifications for economic analysis purposes.

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In many systems the above functions are performed by the G/L module itself, and

the separate budget module is more comprehensive, dealing more with the

development of budget estimates rather than merely recording the budget

estimates.

3. Accounts payable

The main function of accounts payable (A/P) module is to process invoices and

vouchers for government expenditure, authorize payments, and maintain a record

of liabilities. The module must have necessary features to monitor and manage

payments efficiently to utilize discounts and avoid arrears, interest payments, and

penalties. In some systems the A/P ledger is the subledger of the G/L and

interfaces with all relevant systems, such as procurement. The payment processing

should be controlled by the approved commitments and the satisfactory delivery of

goods and services.

4. Accounts receivable

This module must be able to handle all types of inflows that are received by budget

units, including nontax revenues such as sales of goods and services, as well as

fees and commissions. The module should be able to produce bills, process and

record receipts, and record payments.

Noncore/other modules have the following functionality:

5. Payroll system

Some personnel and payroll systems are integrated modules of an FMIS. Another

option is to keep the payroll system as a separate system with an interface with the

FMIS. The minimum requirements are that the payroll systems must contain the

information needed to process payments of the payroll through the FMIS. All

payments and receipts should be captured in the IFMIS. Some of the data needed

are:

• Benefit items for each employee: basic salary, professional or family allowances,

and deductions such as for income tax, health insurance, pensions;

• Budget information: expected increases, budget salaries for next year, overtime

rates;

• Bank accounts information on employees, bank code, branch code, accounts

number, etc.

6. Cash management

The system should assist in maintaining an up-to-date picture of the government's

liquidity position and cash requirements. The system could reside in the Budget

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Department of the MOF, and collect data from revenue agencies on revenue

collections, and debt from the debt management system. These could be

supplemented by information flows from external sources like the central bank for

consolidation and preparation of cash management plans. In view of the different

information flows required for cash management at a central level, some of the

information flows will be interfaced with the information retrieved from the

IFMIS.

7. Budget planning

The FMIS should include functionality for preparation of annual budgets. This

module should be able to exchange data with separate applications for macro-

economic analysis and projections, and facilitate the top-down and bottom-up

approach for the formulation of budget estimates. Hence, a separate budget

preparation system with an interface to the FMIS should assist in the evaluation of

the budget proposals. This system should be able to access and generate data from

the previous years. While time-series and compatibility of codes and classifications

are vital features, the budget planning system should also be supplemented with

tools for assessing the actual performance of ongoing projects, evaluations, and

cost benefit analysis for new proposals.

8. Debt management

A separate debt management system maintaining information on public domestic

and external borrowings is required. This includes information on loan documents

and transactions and issues of government securities. Some of the financial

information from the FMIS is vital for debt management. In addition to accounting

information, these systems also provide information required in the formulation of

fiscal policy, such as forecasts of drawdown and debt-servicing liabilities.

Payments related to government borrowings are carried out in the central debt

management system. Loan receipts recorded in government accounts are processed

by the central FMIS and central treasury general ledger, and are subsequently used

to update the debt database.

9. Revenue administration

Revenue administration is generally supported by a system that has two main

objectives:

• The formulation of tax and tariff policies and the subsequent collection of tax and

nontax revenue; and

• The assurance that the system should assist in capturing all sources of revenue

and ensuring that they are properly accounted for.

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The system should interface with the G/L for updating the ledger accounts, and

should also provide input data to cash management system for preparation of cash

flow forecasts. The system should facilitate the monitoring and evaluation of the

revenue performance against the projections and set targets for future.

10. Purchase or procurement

The system allows the input of commitment approval levels, records the full or

partial discharge of commitments, and shows outstanding commitments at any

given time. (The discharge of commitments would be controlled by the A/P

module). This module should have the ability to generate local payment orders

(LPOs) after the necessary checks and balances have been met. In particular, an

essential feature is that the system must have the capacity to reject procurements

(at the LPO issuance stage) when funds are unavailable—that is, where

commitment and cash controls would be breached should the purchase proceed.

11. Project ledger

This is an optional module that records the listing of projects approved, the total

cost of the budget allocation for the current year, previous years’ cumulative

expenditures, and the balance remaining to project completion. There would need

to be provision to deal with price increases and approved contract variations. This

module would need to agree with the expenditure records of the cashbooks, as well

as have an interface with the budget preparation module.

12. Assets module

This is an optional module and should record all assets purchased or built by the

government, as well as their disposal when this occurs. Information in this module

would come from both the cashbook and the projects modules. Government

holdings in public enterprises would also be recorded here.

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References

ERPCentral

http://www.erpcentral.com/ This portal to ERP issues links to trade

publication articles as well as B2B, CRM, Wireless and e-Business

information.

ERP Fan Club

http://www.erpfans.com Yes, ERP does have its own fan-club site on the

Web, with links to news, vendor information and the like.

The IT Industry Portal – ERP

http://www.erphub.com Even though this site is a subsection of EarthWeb,

another IT industry portal, non-IT executives will still find useful feature

articles and case studies on topics like ERP implementation strategies,

infrastructure and system performance.

IT Toolbox – ERP

http://www.erpassist.com At this Yahoo-style portal, extensive links to ERP

books, white papers, articles and other resources are organized by vendor and by

broad topic themes.

Association of Information Technology Professionals, 401

North Michigan Ave., Suite 2400, Chicago, IL 60611.

Internet: http://www.aitp.org

DSS in accounting by Dr. SAM Vaknin

http://samvak.tripod.com/nm046.html

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Module 6

Allan, W. and A. Hashim, 1994, ―Core Functional Requirements for Fiscal

Management Systems,‖ International Monetary Fund.

Asselin, L., 1994, Integrated Financial Management Systems: Experiences in Latin

America, World Bank (mimeo) pp. 1–82.

Bugler, D.T. and S. Bretschneider, 1993, ―Technology Push or Program Pull:

Interest in new Information Technologies within Public Organizations‖ in Public

Management: the State of the Art (San Francisco: Jossey-Bass).

GAO, 1987, ―Critical Factors in Developing Automated Accounting and Financial

Management Systems,‖ U.S. Printing Office.

Gibson, C.F. and R.L. Nolan, 1974, Managing the Four Stages of EDP Growth,

Harvard Business Review, Vol. 52 No. 1 pp. 76–88.

Hopelain, D.G., 1984, ―The Structure of Information Systems Design: Five

Axioms for the Management of Systems Development,‖ in T. M. A. Bemelmans

(ed) Beyond productivity: Information Systems Development for organizational

Effectiveness, Amsterdam: Eslevier Science Publishers B.V., pp. 147–56

Miranda, R. and T. Keefe, 1998, ―Integrated Financial Management Systems:

Assessing the State of the Art,‖ Government Finance Review, pp. 9–13.

Moussa, A. and R. Schware, 1992, ―Informatics in Africa: Lessons from World

Bank Experience‖ World Development, Vol. 20, pp.1737–52.

Murphy, P., 2002, ―Road Map for Implementation of an Integrated Financial

Management (Accrual Based ) System in a Developing Country Environment,‖

(mimeo).

Peterson, S.B., 1993, Making it Work: Implementing Effective Financial

Information Systems in Bureaucracies in Developing Countries,‖ Development

Discussion Paper No. 447, HIID, pp. 1–26.

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Peterson, S., C. Kinyeki, J. Mutai, and C. Ngungu, 1996, ―Computering

Accounting Systems in Developing Bureaucracies: Lessons from Kenya,‖ Public

Budgeting and Finance, Vol. 16(4) Winter, pp. 45–58.

Strassmann, P.A., 1985, Information Payoff: The Transformation of Work in the

Electronic Age, New York Free Press.

Sundh, P.O., 1989, ―Future of EDP Systems in Government Financial

Management,‖ in ―Seminar on Budgeting and Expenditure Control—Session

Papers,‖ Washington, D.C., November 27-December 6, pp. 78–96.