BI End to End Summary - 13Mar13
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Business Intelligence
IT solutions and businesspractices used for transforming
data into information through
the integration of sales,
marketing, ops, and other
business data sources
Analytics
A way of thinking and acting inthe breaking of problems into
parts and using inferences
based on data to drive
decisions
-
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Business Intelligence
IT solutions and business practices
used for transforming data into
information through the
integration of sales, marketing, ops,
and other business data sources
Analytics
A way of thinking and acting in the
breaking of problems into parts and
using inferences based on data to
drive decisions
Data Warehouse Warehouses
Data Marts
Subject Areas
Data
Data Integrity
Single Source of
Authority
Governance
Metrics
Terms/Definitions
Metric Definitions
Source Systems
Configuration
Governance
Dashboards &Reports
Modeling
Dash-Boarding
Enterprise and
Functional
Support
Business Objectives
Desired Results
Answering the
Whys
Measurement
Leading In-Progress
Lagging
Analysis
Trending Forecasting
Decision-Making
Progress Measurement
Innovation & Continuous Improvement
Business Practices Org Structure
End-to-End
Consistent
Managed Change
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Level 1Initial: Processes unpredictable, poorly controlled, reactive;
zero to 20% work complete.Level 2Managed: Projects of organization ensure requirements are
managed and, processes are planned, performed, measured, and
controlled; 21% - 40% work is complete.
Level 3Defined: Processes are well characterized and understood,
and are described in standards, procedures, tools, and methods; 41% -60% work is complete.
Level 4QuantitativelyManaged: Sub-processes are selected that
significantly contribute to overall process performance. These sub-
processes are controlled using statistical and other quantitative
techniques; 61% - 80% work is complete.
Level 5Optimizing: Processes are continually improved based on a
quantitative understanding of the common causes of variation
inherent in processes; 81 100% work is completeDerived / Source:
http://www.tutorialspoint.com/cmmi/cmmi-maturity-levels.htm
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TechnologyBusiness
Practice
Analytics Decision-Making
Data
Data W-
House Metrics Analysis Goals Base-Line Trends/FC
Academic
Finance /
HR
Mkt / Sales
Operations
Foundation
Business Intelligence
IT solutions and business practices
used for transforming data into
information through the integration of
sales, marketing, ops, and other
business data sources
Analytics
A way of thinking and acting in the
breaking of problems into parts
and using inferences based on data
to drive decisions
-
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BUSINESSTECHNOLOGY
DATA AND GOVERNANCE
OUTPUTSDECISIONS & INNOVATIONS
BI Pieces & Parts
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BI: Pieces & Parts
Business
Policy
Terms & Definitions
Measures & Metrics
Business Process &
Practice
Technology
Application
Configuration &Setup
Security
BI Platform
Data & Gov.
Security
Config. & Setup
Policy
Changes
Outputs
Dashboards &Reports
Trends,Forecasts
Decisions &Innovations
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BI: Pieces & PartsTodays Focus Areas
Business
Policy
Terms & Definitions
Measures & Metrics
Business Process &
Practice
Technology
Application
Configuration &Setup
Security
BI PlatformData & Gov.
Security
Config. & Setup
Policy
Changes
Outputs
Dashboards &Reports
Trends,Forecasts
Decisions &Innovations
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BUSINESSTECHNOLOGY
DATA AND GOVERNANCE
OUTPUTSDECISIONS & INNOVATIONS
BI Pieces & Parts
Business
Policy
Terms & Definitions
Measures & Metrics
Business Process &Practice
Technology
Application
Configuration & Setup
Security
BI Platform
Data & Gov.
Security
Config. & Setup
Policy
Changes
Outputs
Dashboards &Reports
Trends, Forecasts
Decisions &Innovations
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Terms &Definitions
Metrics
Coding Structure
SystemCoding &
GapAnalysis
SystemConfiguration &
Set-Up
BusinessProcess
Alignment
Operations Marketing Product Executive
Outputs
Data &Reports
Trends &Forecasts
BI Pieces & Parts: Business
General Approach
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Terms & Definitions
Term: a word or group of words designatingsomething in a particular field, as atom in physic,quietism in theology, adze in carpentry, or districtleaderin politics.
Source: http://dictionary.reference.com/browse/term
Definition: the act of making definite, distinct, orclear; a defining: We need a better definition ofher responsibilities.
Source: http://dictionary.reference.com/browse/term
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Terms &Definitions
Metrics
Coding Structure
SystemCoding &
GapAnalysis
SystemConfiguration &
Set-Up
BusinessProcess
Alignment
Outputs
Data &Reports
Trends &Forecasts
http://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/term -
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Terms & DefinitionsOf course, when considering the question from
business and business intelligenceperspectives, the important questions include
What are the terms used in communicating
and explaining your business?
What regulatory, industry, and legal terms and
definitions are important for your business?
Is the organization aligned on the terms and
their respective meanings?
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Terms & Definitions - Examples
Re
f#
Reporting
Dime
nsion
(Opsvs.
Mktg)
Future State
Dimension
Business Definition for Data
Dictionary Definition Notes
7 OPSRequirements of
Completion
% Complete as calculated by the degree
audit (including # of applicable credits)
Future State - Level 3 Dimensions (another
sub-set of requirements of completion
dimensions) e.g., What percentage of core vs.
non-core have been completed?
16c OPS "Other" Course(s) Placeholder for future innovationWould include non-credit training to be
developed.
18b OPS Non Credit Unit(s)Indicates participation in a class that
does not accrue credit hours
Would include non-credit training to be
developed.
System needs to house the number of non-
credit units for financial conversion (e.g. non-
credit course "A" is worth 2 non-credit units)
35b OPS Enhanced CourseA course offered in class with optional
online components
From our dimensions visio document: 0-25% of
class activity is offered in a virtual environment.
35c OPS Blended CourseAn online course with in-class
components
From our dimensions visio document: 75% or
more of class activity is offered in a virtual
environment.
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Metrics
Parameters or measures of
quantitative assessment used
for measurement, comparisonor to track performance or
production.Source:
http://www.investopedia.com/terms/m/metrics.asp#ixzz2MKH0oB7Z
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Terms &Definitions
Metrics
CodingStructure
SystemCoding &
GapAnalysis
SystemConfiguration& Set-Up
BusinessProcess
Alignment
Outputs
Data &Reports
Trends &Forecasts
http://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asp -
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Metrics: Getting to Metrics
In support of organizational,
department, or team goals,what are the areas ofperformancethat need to
be measured?
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Metrics: Definitions
Is there a consistent understanding?
PersistenceMeasured by initial term
student enrolls and
remains enrolled in
subsequent terms.
RetentionMeasured annually for
student enrollment in
initial term in initial year,
and subsequent year(s)thru completion.
Graduation RateMeasure at 6 year mark for
IPEDS, 6-9 years for CSRDE
and, 2-11 years for BU.
Student completes programrequirements and is
conferred.
EnrollmentEnrollment count (head
count, hours, revenue.
Drop / WithdrawalMeasured by Term and by
Course.Student dropping from
courses.
Time sensitive.
Student CountsComparison between
previous term/year countsand variances.
Show growth/decline trends
over time.
Identify trends and forecast.
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Metrics: Outline desired outputs
PersistenceMeasured by initial term
student enrolls and
remains enrolled in
subsequent terms.
RetentionMeasured annually for
student enrollment in initial
term in initial year, and
subsequent year(s) thru
completion.
Graduation RateMeasure at 6 year mark for
IPEDS, 6-9 years for CSRDE
and, 2-11 years for BU.
Student completes program
requirements and is
conferred.
EnrollmentEnrollment count (head
count, hours, revenue.
Drop / WithdrawalMeasured by Term and by
Course.
Student dropping from
courses.
Time sensitive.
Student CountsComparison between
previous term/year counts
and variances.
Show growth/decline trends
over time.
Identify trends and forecast.
Show and measure growth/decline rates over time.
Identify trends and forecasts.
Establish root cause(s).3/13/2013 By Ed Jarecki 16
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MetricsMetrics
Understanding requires analyzing from many
perspectives
Academic Level
Freshman
SophomoreJunior
Senior
5+ Senior
Student AttributeActive
Inactive
Degree Awarded
Student State
New
Continuing
Instructional
Format
Retail
Custom
Delivery Format
Traditional
Cohort
Other
Student Type
Degree Seeking
Non-degree Seeking
TransferFirst-time Freshman
Visiting
Vertical MarketInternational
Corporate
ComCollege
Military
Other
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** OverallRetention
Rate
Metrics: Planning and Organizing
Retention* Measure
revenue
earned from
increased
retention
Grad
Under-grad
Online
In-class
Part-Time
Full-Time
Current:
75%; $XX
Goal:80%; $XX
Note**: Sample data only
Traditiona
l
Cohort
Note*: Define; 1% retention rate improvement = $XX revenue
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** OverallRetention
Rate
Retention* Measure
revenue
earned from
increased
retention
Grad
Under-grad
Online
In-class
Part-Time
Full-Time
Current:
75%; $XX
Goal:80%; $XX
Traditiona
l
Cohort
Of course, there is still much to do
Note: Sample data only
Key Questions & Actions
Is the revenue recognition
method in alignment with?
How are drops to be
considered? Need to align
How is student value
calculated?3/13/2013 By Ed Jarecki 20
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And
3/13/2013 By Ed Jarecki 21
Key Questions & Actions
Are system configurationsappropriately setup?
Terms &Definitions
Metrics
Coding Structure
SystemCoding &
Gap
Analysis
SystemConfiguration
& Set-Up
BusinessProcessAlignment
Outputs
Data &Reports
Trends &Forecasts
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Coding Structure: BU Example
Current State Coding Analysis
Analyze SIS (Student Information System) codes currently in use Define standard parameters and definitions of each code type
Analyze codes in scope against SIS parameters/definitions to
identify coding inconsistencies, etc.
Complete a detailed analysis of non-optimized/exception basedcoding to capture specific business requirements
Conduct research to increase understanding of system functionality
Future State Coding Analysis
Complete detailed mapping for all future state coding metrics,formulas, and dimensions to understand system equivalents
Develop recommendations to support identified gaps and coding
requirements
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Coding Structure
BU Summary Results
Currentstate analysis 355 total codes analyzed
49 of 133 service indicators were categorized as exceptions
98% of student groups manually maintained increasing risk
of errors
Future state analysis 84 future state dimensions
and eight operational reports analyzed
67 of these codes tied to existing fields in the database
Seven dimensions tied to an existing student code
10 dimensions identified as current gaps in coding set up
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Coding Structure
BU Summary Recommendations
Establish standard governance processes and practices to
maintain consistency among student coding
Establish project team to complete all process, coding, and
system configuration changes to support the student
operations Future State metrics and dimensions
Optimize current state codes leveraging system functionality
for automation while completing maintenance and clean upof inactive codes
Defer long-term opportunities and align with project priorities
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Business Process & BI
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Terms &Definitions
Metrics
Coding Structure
SystemCoding &
GapAnalysis
SystemConfiguration &
Set-Up
Business
ProcessAlignment
Outputs
Data &Reports
Trends &
Forecasts
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Business Process & BI
Often missed in the evaluation and
selection of a Business Intelligence solution
is the need for alignmentbetween desiredoutputs and the data generated from
business processes and practices
Business Intelligence
IT solutions and business practices
used for transforming data into
information through the integration
of sales, marketing, ops, and other
business data sources
3/13/2013By Ed Jarecki
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Business Process & BI
As organizations evolve from leveraging
available data to developing management
reports, scorecards, dashboards and real-time BI, the need to align and optimize
business practices is essential
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Business Intelligence
IT solutions and business practices
used for transforming data into
information through the integration
of sales, marketing, ops, and other
business data sources
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Outputs
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Key Questions & Actions
What are the questions to beanswered?
What trends and forecasts are
required?
What are the drill-down
requirements?
Terms &Definitions
Metrics
CodingStructure
SystemCoding &
GapAnalysis
SystemConfiguration
& Set-Up
BusinessProcess
Alignment
Outputs
Data &Reports
Trends &Forecasts
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What actions are necessary to grow overall enrollments by
10% year-over-year?
What is the enrollment (FTE and hours) trend over
the past 10 years?
What programs have grown and shrank by
>10% year-over-year over the past 5 years?
What is the profile for students in the
top 5 growth programs? Top 5
declining programs?3/13/2013 By Ed Jarecki 29
Outputs: ExampleWhat questions need to be answered?
GettingTo
Action
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OutputsEXAMPLE REPORT DEFINITION
Student Retention
Report Description: Measured annually for student enrollment in initial term in initial year and subsequent year(s)
thru completion.
Purpose: Measures how students persist year-over-year
Assumption Report will allow defined comparison of same point in time for previous periods of time (multiple)
Primary Reports: N/A
Attributes:
How a student persists year-to-yeara. Can start any time within Academic Year
If student attends at least one term each year, will be part of retention reportb. Final check is run 21 days (class start +21 days)
i. 14 days to account for Drop/Add period and Attendance Verificationii. 7 days for business processing
c. Spot checks are done w/in current year
Report Frequency:
Monthly
As necessary / on demand
Policy Items: Do not change Students original cohort start date unless the level of degree changes. The
cohort start date remains the same. Students can transfer between active and inactive statusuntil they reach status of Awarded. Non-degree seeking students will be excluded.
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Outputs: ANALYTICS COMPETENCY
What is analytics competency?
Knowledge of what tools are available and how to use them Knowledge of data
Where the data is located
What the data source of authority is
Critical thinking The best data, models and tools will notproduce results without the right people supporting analytics
efforts
People: People generate insights from models. The same people are
also critical in gaining leadership support for analytics-based outcomes
driving organizational change
Modeling: Beyond the creation and purchase of analytic models,
analytics capabilities will evolve, environmental conditions will change,
and integration challenges will intensify resulting in a need to change
data, models, and outputs
Level of data integrity
Access to data
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Business Practice: Key Lessons
Culture analytical vs. intuitive decision-
making, broad vs. focused strategy Analytic Mindset breadth of business
users understanding; often limited to
current duties
Terms &Definitions
Metrics
CodingStructure
SystemCoding &
GapAnalysis
SystemConfiguration
& Set-Up
BusinessProcess
Alignment
OutputsData &Reports
Trends &Forecasts
Varying Skills range
and limit of end-userunderstanding
relative to best/most
proper use of source
applications (e.g.,
campus solutions) Roles & Responsibilities fundamentally
important to understand, define, and establish at
project start
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Business Checklist Are terms used in communicating and explaining your business defined?
Are regulatory, industry, and legal terms and definitions important for your business
defined?
Is the organization aligned on the terms and their respective meanings?
In support of organizational, department, or team goals, are areas of performance that
need to be measured defined?
Are goals defined in alignment with each of area of performance?
Have measurement dimensions been defined?
Are metric formulas aligned? Are system configurations setup in alignment with metrics, formulas, and desired
outputs?
Are business processes in alignment with data needs and desired outputs?
Have business questions to be answered been defined?
Have trends and forecasts requirements been defined?
Are report and dashboard drill-down requirements been defined?
Are resources available and accessible that have the necessary dataknowledge?
Are resources available and accessible that have the necessary toolknowledge?
Are resources available and accessible with necessary problem solving and critical
thinking skills?
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BUSINESSTECHNOLOGY
DATA AND GOVERNANCE
OUTPUTSDECISIONS & INNOVATIONS
BI Pieces & Parts
Business
Policy
Terms & Definitions
Measures & Metrics
Business Process &Practice
Technology
Application
Configuration & Setup
Security
BI Platform
Data & Gov. Security
Config. & Setup
Policy
Changes
Outputs
Dashboards &Reports
Trends, Forecasts
Decisions &Innovations
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BI S C
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BI System ComponentsMetrics, Baselines,
& Goals,
Business
Process Inputs
Data Sources, System Configuration, Data
Management and Governance
Data Architecture, Data Models, Dashboards &
Reports
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BI System: Getting to Value
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Data Warehouse: Basic Structure
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SubjectArea
Student Information System
(Campus Solutions)
Campus Community
StudentTab
le
2
Stude
ntTable
3
Student Table 1
StudentTable 4
Student Table 5
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Campus Solutions
Data Warehouse: Basic Structure
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SubjectArea
Campus Community
Student
Table
2Student
Table 3
Student Table 1
Student
Table 4
Student Table 5
Student Financials
SF Table 5
SFTable
2SF
Table
3
SF Table 1
FMS
General Ledger
GL Table 1
GL Table
4
GL Table 5
Accounts
Payable
AP Table 5
AP Table
3
AP
Table
4
G
LTable
2
SF Table
4
AP Table
1
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Data Warehouse: Setup & Configuration
Ensure there is appropriate time to provision
Roles and responsibilities clearly defined (business andtechnology)
Create and execute a plan to fill skill gap areas
Define organizations initial questions to be answered
Sponsor needs to clearly define the requirements of a
successful implementation
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Plan, plan, plan Create a planthat outlines clearly defined goals,
architecture, sources of data,tasks, delivery timelines, etc.
Consider turnoverOrganizational and vendor (whenapplicable)
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Data Warehouse: Data Structure
ETL Translation of relational model to Star schema.
Star Schema Normalized with each dimension represented by a single
table
Facts/related facts in center
Star points are different dimensions in which, to filter and analyze data
Snowflake schema Logical arrangement of tables in a
multidimensional database. Centralized fact table connected withmultiple dimensions.
Trade-offs: Performance (driven by additional joins ETLs more complicated
versus Star Schema)
Changing Dimensions Necessary for point-in-time analysis and
trending Rapid Change: Snapshot (daily event/change capture)
Easier to apply supporting need for rapid change
Slow Change: CDC (Change Data Capture effective date driven table)
Saves space3/13/2013 By Ed Jarecki 40
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Data Warehouse: Security
Security: Keep structure as simple as possible Will naturally become more complicated over time
Start with Report-levelof security (i.e., restrictions based on report
access rules)
Move to Columnar-levelof security (i.e., who has access to what facts
and dimensions)
Row-levelsecurity is the limits access based on content of data being
analyzed (e.g., ability to access drops for College of Business but, not for
College of Science and Technology)
Governance: Must control what gets published
Similar to other reporting methods, free sharing of data and reportswithout controls, can easily result in unmanageable list of reports
Without appropriate controls, ability to consistently produce one version
of the truth is reduced dramatically over time
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Data Warehouse: Key Lessons
ETL, ETL, ETL expertise, maintenance and,
resource requirements, constancy of change,etc.
Performance right sizing for performance
Security Complexity security of source
apps needs to be in correct state
Education relative to data available, dataneeded, business practices, and sources of
data, etc.
ReportingDoes not initially ever? Replace
other operational reporting solutions?
SaaS vs. In-House lessons learned inhosting vs. in-house (e.g., reliance on
provider to provide correct competencies in
environment set up)
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T h l Ch kli t
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Technology Checklist
Are BI roles and responsibilities, technology and business, clearly defined
and understood?
Has the organization defined the questions to be answered? (at least the
initial set of questions to be answered)
Has senior leadership / sponsor outlined requirements for success?
Has a comprehensive plan been established and aligned with senior
leadership / sponsor expectations
Has the data schema been selected that is in alignment with planned use anddemand?
Has a data warehouse data and report/dashboard security plan been
established?
Has governance been established that ensures/delivers to the required level
of data integrity? Do senior leadership and other key stakeholders understand all of the BI
Pieces and Parts?
Is there appropriate understanding of the role and mission of BI versus
operational reports?
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BUSINESSTECHNOLOGY
DATA AND GOVERNANCE
OUTPUTSDECISIONS & INNOVATIONS
BI Pieces & Parts
Business
Policy
Terms & Definitions
Measures & Metrics
Business Process &Practice
Technology
Application
Configuration & Setup
Security
BI Platform
Data & Gov. Security
Config. & Setup
Policy
Changes
Outputs
Dashboards &Reports
Trends, Forecasts
Decisions &Innovations
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Data What Is Data?...
Items of information Bing Dictionary
Individual facts, statistics, or items of information Dictionary.com
Factual information used as a basis for reasoning, discussion, or
calculation Merriam-Webster.com
The correct question?What business questions are we trying to answer?
Of course, this leads to the data questions
What data is needed?
What data is available?
Where is it located?
What is the integrity level of the data?
and, many more
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Getting to Answers
Business
Question
or
Problem
Statement
Modeling
Evaluation
Data
Preparation
Information,Knowledge,
Decision-
making
Data
Understanding
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What data is needed?...
Business Question or Problem Statement Understand and define the business problem
Data Understanding Collect, describe, and explore the data
Identify quality problems of the data
Data Preparation Develop data models
Collect, cleanse, and format data
Prepare data for modeling tool by selecting
tables, records, and attributes ensuring meaningof data is notchanged
Create new derived attributes (e.g., average,
range, minimum, maximum, etc.)
Partnership
between IT
and business
is critical
Business
Questionor
ProblemStatement
Modeling
Evaluation
DataPreparation
Information,
Knowledge,
Decision-making
DataUnderstanding
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DataMap Example
CS CRM
stdnt
_enrl
class
_tbl
crse
_offe
r
scc_priorw
ork
bv_ea_
bellu
_tbl
scc_pe
rdata_
qvw
srvc_ind
_data
stdnt
_car
_term
instr_
class
_vw
stdnt
_grps_his
t
acad
_plan
acad
_plan
_tbl
rq_grp
_tbl
a
System Table (Record) CSSystem Table (Record) CS
l
ad_plan
_vw
FieldPe
rsist
ance
(8)
Reten
tion(8)
GraduationR
ate(9)
Enrollm
ent(2)
Add/
Drop/
With
draw
al(2)
StudentC
ount
(
Comp
leti
Cl
Metrics Metrics
Student Characteristics / x x x x
Active
x x x x
Inactive
x x x x
eturning Students, etc) -
Degree Completed x x
Degreee Awarded
x x
Degree Approved x x
-
Derived
Derived
-
completion_term
degr_chkout_stat
degr_chkout_stat
x x x x x
x8 x8 x2
x8 x8 x2
x9 x9 x9 x
x x x x
x x x x
Academic Structure x x x x x x x
uirements of Completionx x x
Other Dimensions (TBD) -
Section x x
Course x x x
Major x x
College x x x
Session x x
-
Derived
-
class_section
Derived
Derived
acad_group
session_code
x x x x x
x
x1 x1 x1
x2 x2 x2 x4
x9 x9 x9 x9
x2 x2 x2 x4
x2 x2
Business
Question
orProblem
Statement
Modeling
Evaluation
Data
Preparation
Information,Knowledge,
Decision-making
DataUnderstanding
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Modeling Data selected
Modeling and evaluation activities loop
until desired outcome is achieved
Evaluation Models evaluated Does model achieve business objective?
Have all business issues been considered?
Business owners decide how to use results
Deployment Reports and dashboards created
Outputs leveraged for decision-making
Generating results...
Partnership
between IT
and business
is critical
Business
Question
orProblem
Statement
Modeling
Evaluation
Data
Preparation
Information,Knowledge,
Decision-making
DataUnderstanding
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Data: Key Lessons
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Data: Key Lessons Data Needs
How willing/flexible is your organization to change practices to support data /
solution needs?
Is there process consistency / standardization?
What does your institution want to know?
Business
Question
or
Problem
Statement
Modeling
Evaluation
Data
Preparation
Information,
Knowledge,
Decision-
making
Data
Understanding
Data RefreshHow real-timedoes the data need to be?
Data GovernanceWhat are
your data integrity & securitycontrols? Are they enough?
Data Source
Where is the source data?
Is there support for
integrating / pulling data
from non-owned sources? Data Speed
Processes and utilities/tools for warehouse integration
Skill and tools for setting up / modifying data marts and subject areas
Data KnowledgeHow it is used? Where it is at?
ResourcesCosts (e.g., hosting, fte, consulting, etc.) for adding data marts, etc.?3/13/2013 By Ed Jarecki 50
Data The foundation for
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Data The foundation for
knowledge for understanding
Business
Questionor
Problem
Statement
Modeling
Evaluation
Data
Preparation
Information,
Knowledge,
Decision-making
Data
Understanding
for decision-making3/13/2013 By Ed Jarecki 51
G
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Governance What is Governance?...
Governance is about promoting organizational fairness,transparency and accountability. The governance structure
specifies the distribution of rights and responsibilities of
organization executives, managers, and other stakeholders,
and spells out the rules and procedures for making decisions.Definition derived from: KnowledgeLeaderSM provided by Protivity
The real question?
Why is Governance so important?
Personal information is valuable and private
Data and information are important organization
assets
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G S Att ib t
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Governance Success Attributes
Governance structures will vary; however, there are
characteristics necessary for success Participation:Appropriate participants; constructive participation
Policy: Clearly defined; enforced impartially
Transparency:
Processes & information directly accessible to those concerned
Enough information is provided to understand and monitor
Responsiveness: Institution and processes try to serve all stakeholders
Consensus Orientation: Mediate differing interests to reach a broadconsensus on what is in the best interests of the organization
Equity: All have opportunities to improve or maintain their well-being
Derived From / Source: UNDP (1997) Governance for Sustainable Human Development. United Nations
Development Program
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b
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Governance Success Attributes
Governance structures will vary; however, there are
characteristics necessary for success cont.
Effectiveness and Efficiency: Processes produce results that meetneeds while making the best use of resources
Accountability: Decision-makers are accountable to the organization,students, and stakeholders of the organization
Strategic vision: Leaders and the public have a broad and long-termperspective on good governance and human development, along with a
sense of what is needed for such development. There is also an
understanding of the historical, cultural and social complexities in which
that perspective is grounded.
Derived From / Source: UNDP (1997) Governance for Sustainable Human Development. United
Nations Development Program
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Governance: Example
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Governance: Example
Policy & Decision-Making Actions
Review policy relative to inactive, recycled, and/or
reactivating codes
Define ownership for codes shared across
departments (e.g., first time freshman) Review recommendation and policy for effective-
dating practices
Provide feedback & decisions required to support
development of future state reporting criteria
Review future coding parameter changes/updates to
identify process and reporting impacts
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G D i i ki
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Automate Student Groups Eliminate 23 manual student
groups
Conduct Fit-Gap: Leverage PeopleSoft Graduation Process
Complete end-to-end process analysis to developunderstanding of requirements and implement a
delivered and automated solution to replace manual
graduation process by Nov 2012
Based on findings develop configuration & set-up plan tosupport implementation for January 2013
System Maintenance & Clean Up Inactivate 54 unutilized
codes
Governance Decision-making
Bellevue University Examples
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Governance: Model Example
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Governance: Model ExampleStudent Coding Governance Committee Structure
StudentCoding
AnalysisTeam
Policy
Committee
Governance
Committee
Con
figuration&
SetUp
Committee
VPCommittee
Project Phase Ops & Maintenance Phase
Develop, integrate, &
management of
practices aligned with
Policy Committees
vision
Communication roll-out
to staff & faculty
Milestone:
Current state
Analysis
complete
Mapping of future state
reqts to current state
code
High Level Analysis of CS
& CRM data
More detailed analysis
of BUs exception coding
Recommendation
for pending policies
to VP committee
Direction & Vision
for governance
process & set up
Milestone:
Policies Defined
Milestone:
Governance Set-
up
Milestone:
Student Coding
Recommendation
Conduct system &
best practice research
for functionality
Complete formal
Recommendation
Configuration team
set-up
Understanding of
governance process
& defined policies
Implementation of
student codingrecommendation
Milestone:
CS & CRM
System Set-up
Continued
maintenance of
ongoing policy
recommendations &
continuous
improvement
Evaluation &
decisions of new
code requests
Continued
enforcement of
practices aligned
with policies
Ongoing maintenance
& configuration of
systems & continuous
improvement
PROJECT TEAM 1
AVPS
DIRECTORS
Initial policy
decisions
Initial policy
decisions to kick-off
the project & create
context for
governance set-up
Ongoing review of
Policy commiitee
recommendations &
final decisions
VPs
PROJECT TEAM 2
Pending Policies
Policy
Recommendations
Policy Decisions
Milestone:
Governance
Vision
completed
Policy
Recommendations
Final Policy
Decisions
New Policies
New codes & practices
per policy
Policy Decisions
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Governance: Key Lessons
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Leadership Is there
leadership buy-in?
Change Management
Day-to-day: What is the
impact of changes in
one function on
activities in another?
Data Maintenance
How will data integritybe maintained or,
improved?
Change Management
Organizational: How do
you plan to handlechanges in strategy and
business needs
Governance: Key Lessons
Student Coding Governance Committee Structure
Stud
entCoding
Ana
lysisTeam
Policy
Committee
Governance
Committee
Configuration&
SetUp
Committee
VPCommittee
Project Phase Ops & Maintenance Phase
Develop,integrate, &
management of
practices alignedwith
Policy Committees
vision
Communication roll-out
to staff& faculty
Milestone:
Current state
Analysis
complete
Mapping offuture state
reqts to current state
code
HighLevel Analysis ofCS
& CRM data
Moredetailed analysis
ofBUs exception coding
Recommendation
for pending policies
to VPcommittee
Direction& Vision
for governance
process & set up
Milestone:
Policies Defined
Milestone:
GovernanceSet-
up
Milestone:
Student Coding
Recommendation
Conduct system&
best practiceresearch
for functionality
CompleteformalRecommendation
Configurationteam
set-up
Understanding of
governanceprocess
& definedpolicies
Implementationof
student coding
recommendation
Milestone:
CS& CRM
SystemSet-up
Continued
maintenanceof
ongoing policy
recommendations &
continuous
improvement
Evaluation&
decisions ofnew
coderequests
Continued
enforcement of
practices aligned
withpolicies
Ongoing maintenance
& configurationof
systems & continuous
improvement
PROJECT TEAM 1
AVPS
DIRECTORS
Initial policy
decisions
Initial policy
decisions to kick-off
theproject & create
context for
governanceset-up
Ongoing reviewof
Policy commiitee
recommendations &
final decisions
VPs
PROJECT TEAM 2
Pending Policies
Policy
Recommendations
Policy Decisions
Milestone:
Governance
Vision
completed
Policy
Recommendations
Final Policy
Decisions
NewPolicies
Newcodes & practices
per policy
Policy Decisions
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Data & Governance Checklist
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Data & Governance Checklist
3/13/2013 By Ed Jarecki 59
What business questions is your organization trying to answer?
What data is needed?
What data is available?
Where is the data located?
What is the integrity level requirement for the data?
How real-time does the data need to be?
Is there process consistency / standardization?
What are your data integrity & security controls? Are they enough?
Is there support for integrating / pulling data from non-owned sources?
Data Knowledge Is it available?
Are all costs (e.g., hosting, FTE, consulting, etc.) understood for adding
data marts, ETL management, etc.?
Has data ownership been defined (i.e., edit, read, no access)?
Has data and system Governance been established?
Have data and security policies and practice guidelines been reviewed and
updated?
Has a change management plan been established to handle changes in
strategy and business needs?
BI and Analytics
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BI and Analytics
Are You Ready?Exercise 20 minutes
Considering the BI inputs discussed today, on the chart
on page 84, rate your organizations readiness in the
area(s) in which BI is focused or planned. (5-10 minutes)
In teams of three to five,discuss your
organizations readiness
for success? (10 15
minutes) Note what actions you
will you take to improve
readiness?
3/13/2013 By Ed Jarecki 60
Business Intelligence
IT solutions and business practices used
for transforming data into information
through the integration of sales,
marketing, ops, and other business data
sources
Analytics
A way of thinking and acting in the
breaking of problems into parts and using
inferences based on data to drive
decisions
Data Warehouse Warehouses
Data Marts Subject Areas
Data
Data Integrity Single Source
of Authority
Governance
Metrics
Terms/Definition
s
Metric
Definitions
Source Systems Configuration Governance
Dashboards & Reports
Modeling Dash-
Boarding
Enterpriseand
Functional
Support
Business Objectives
Desired Results
Answering the
Whys
Measurement
Leading
In-Progress
Lagging
Analysis Trending Forecasting
Decision-Making Progress Measurement
Innovation & Continuous Improvement
Business Practices Org
Structure
End-to-End Consistent
ManagedChange
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Business Intelligence
IT solutions and business practicesused for transforming data into
information through the integration of
sales, marketing, ops, and other
business data sources
Analytics
A way of thinking and acting in thebreaking of problems into parts
and using inferences based on data
to drive decisions
TechnologyBusiness
Practice
Analytics Decision-Making
Data Data W-House
Metrics Analysis Goals Base-Line Trends/FC
Academic
Finance /
HR
Mkt /Sales
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Level 1Initial: Processes unpredictable, poorly controlled, reactive;
zero to 20% work complete.
Level 2Managed: Projects of organization ensure requirements are
managed and, processes are planned, performed, measured, and
controlled; 21% - 40% work is complete.
Level 3Defined: Processes are well characterized and understood,
and are described in standards, procedures, tools, and methods; 41% -60% work is complete.
Level 4QuantitativelyManaged: Sub-processes are selected that
significantly contribute to overall process performance. These sub-
processes are controlled using statistical and other quantitative
techniques; 61% - 80% work is complete.Level 5Optimizing: Processes are continually improved based on a
quantitative understanding of the common causes of variation
inherent in processes; 81 100% work is completeDerived / Source: