CONTENTS Business Rules - Decision Management Solutions · Services replace decision points in...

1 © 2017 Decision Management Solutions

Maximizing the Value of Business Rules Decision Management streamlines and focuses business rules projects for faster, more effective deployment

Business Rules Management Systems deliver on the promise of costs savings,

agility and happy customers. Yet for many organizations, these efforts

remain point solutions. Decision Management is a proven framework to

drive the widespread adoption of business rules and improved business

performance across the company.

You have realized the benefits of adopting a Business Rules Management System or

BRMS. Now, if you could have these results anywhere else in your business, where

would they make the most difference? Standalone project successes confirm that a

BRMS delivers on its promise of costs savings, agility and happy customers. Yet most

business rules efforts remain point solutions.

A typical first BRMS implementation starts by creating what could be a called a “Big

Bucket O’ Rules.” The team has selected a BRMS as part of a project and they start

capturing their rules. Typically, they interview experts, read policy manuals and

reverse engineer code into rules. Almost always, but especially when they reverse

engineer code, they end up with a lot of somewhat low-level rules. In one, big,

bucket.

This big bucket of rules is not usable. The team will often try to add rules to their

very complex process diagrams—placing each individual rule on the process

diagram. Most of the low-level rules cannot be placed in this way and doing so just

contributes to over-complex business processes. It’s also difficult to manage the

By James Taylor CONTENTS

Decision

Management—

Automating and

Improving Decisions

Decision Discovery

and Modeling

Decision Service

Definition and

Implementation

Decision Monitoring

and Improvement

Decision Modeling

Conclusion

Maximizing the Value of Business Rules


rules properly. There’s no organizational structure to the rules so they end up being

grouped by source or by the person doing the rule identification. As policies or

regulations change, or as new business needs are identified, the team often

struggles to update the right business rules.

Typically, the team perseveres and ends up grouping the rules into services that

perform some useful action, generally answering some question or selecting an

action from a list of candidate actions. Groups of rules, rulesets, are deployed as

services or several rulesets are linked together and deployed. These services can be

invoked by existing systems or as part of a new business process.

What the team has done, often without realizing it, is identify the decisions that

their rules support. Not only are these decisions more stable—new decisions within

a business are rare while new rules or changed rules are common—they represent

the connection point that existing systems and new processes need. Connecting

systems and processes to decisions and automating those decisions using business

rules gets them the results they were looking for. They get a positive ROI from

using a BRMS by making these decisions more accurately and more consistently.

They engage business users and empower them to manage the rules. They deliver

agility as it is easier to evolve the rules behind these

decisions as the business changes.

For all the success and enthusiasm coming out of a

BRMS project that takes this “Big Bucket O’ Rules”

approach, companies often stall when trying to expand

adoption of BRMS across the company. Some pigeonhole

the BRMS as a technology only suitable for the initial

project – the BRMS becomes “claims technology” or

“the pricing engine.” New projects in other areas

revert to writing code or using table-driven

parameterization. Some companies try to go

“enterprise-wide” but this is like trying to boil the

ocean as it becomes an effort to find and manage all their business rules.

In both cases the problem is that the decisions being managed using these business

rules are not central to the solution. If the team does not have a way to identify

and classify decisions that are suitable for automation with a BRMS then the BRMS

will be perceived as a solution to the first, specific problem for which it was

purchased. Similarly, without a way to identify high priority decisions and so focus

expansion efforts on the rules needed for them, broad adoption of the BRMS will

often stall.

Decision Management resolves these issues. Business Rules Management Systems

generate an ROI when they improve business decisions – it’s the decisions that

create the value. By focusing you on the decisions that matter to your organization

– the ones that affect your business drivers and measures – Decision Management

simplifies business rules design and implementation while accelerating adoption of

a BRMS where it has the highest impact.



Decision Management—Automating and Improving

Decisions

Decision Management focuses on the decisions that create value in your business,

recognizes these decisions as reusable assets, and makes them widely available via

a Service Oriented Architecture (SOA). The three phases (shown in Figure 1) are:

Decision Discovery and Modeling

The first step in adopting Decision Management is Decision Discovery and Modeling.

Decision Discovery finds the decisions that matter to your business and drive

results. Decisions are modeled using the Decision Model Notation (DMN) standard

ensuring consistency and re-use. See Decision Modeling at the end of this white

paper for more information.

Decision Service Definition and Implementation

The second step is the definition and implementation of Decision Services. Decision

Services replace decision points in processes and systems to make those processes

and systems simpler, smarter and more agile. Defined in terms of the decision

model, these Decision Services are built using Business Rules Management Systems

and can be enhanced with the results of data mining and predictive analytics, now

or in the future.

Decision Measurement and Improvement

The final step is to close the loop with Decision Measurement and Improvement.

Ongoing decision measurement and improvement ensures that decision making is

monitored and constantly improved to deliver increasing value over time.

Figure 1.The Three Phases of Decision Management

Source: Real-World Decision Modeling with DMN, Figure 5-3



Decision Discovery and Modeling

By understanding which decisions matter to your organization – which ones affect

your business drivers and measures – it becomes straightforward to show a strong

ROI. Decision Discovery is thus the first step in applying Decision Management.

Discover Decisions

Decision Discovery identifies the high value decisions that will provide the biggest

pay-off for your business. Decision Discovery externalizes the operational decisions

in your processes and systems. This allows the decisions to be understood and

owned by the business and allows decision-making to be linked explicitly to

performance measures and KPIs. With this done it will be clear what changes to

decision-making will be required to improve any given measure. And the decisions

that have the greatest impact on the most critical measures will be the place to

start.

Model Decisions

Graphical decision models like that in Figure 2 make it easier to communication and

collaborate on requirements and outcomes. Staff can then focus on value-add

activities that require their expertise, adding further value.

Figure 2. Example Decision Requirements Model

Source: DecisionsFirst Modeler



Decision modeling using the industry Decision Model and Notation (DMN) standard

provides a framework that teams across an organization can use. It provides a

common language between business analysts, architects, business owners, IT

professionals and analytic teams. Decisions are more easily tied to performance

measures and to the business goals. This makes it easier to focus teams where they

will have the highest impact and to measure results.

Link to ROI Drivers

Having discovered the decisions that run your business and contribute to your KPIs

the next step is to prioritize them for the application of Decision Management. You

need to know how likely it is to show a strong ROI. Good candidates include:

Manual decisions made by supervisors because automating them will empower

others to make those decisions directly, reducing referrals and increasing first

call resolution.

Manual decisions where more than seven factors must be considered as people

are not good at handling complex trade-offs.

Inconsistent decisions where the website gives one answer while the call center

gives another or where different call center representatives give different

answers are good candidates as the management of those decisions can

eliminate the inconsistency.

Decisions embedded in existing systems can be good candidates too when the

existing system implements regulations, has requirements that change frequently or

has many maintenance projects.

There are several characteristics of a decision that make it likely to show a high ROI

from Decision Management. Any of these characteristics is enough, though decisions

with combinations are more common and will show higher ROI. These

characteristics of high ROI decisions include:

The Decision Model and Notation (DMN) Standard was approved in 2014-2015 by the Object Management

Group. Decision Management Solutions is a submitter of the DMN standard, an open industry standard with

broad vendor and community support.

This continuous manufacturing company automated the process of checking materials masters for its ERP

systems, previously a manual decision, and reduced elapsed time to create a materials master by 95%.

This government agency moved a hard-coded decision into a decision service (calculating the cost of a

license involving some 2,000 rules derived from constantly updated regulations) from its legacy system

and could save 13,000 hours in maintenance work in the first year alone.



Rapid or frequent change required

Multi-channel

Highly dependent on outside factors

A need to demonstrate that the decision is compliant

Risk management

Potential for personalization

Reasonably high volume

B2C

We’ll call this Business-to-Consumer company “B2C”. It has an objective to improve

its customer retention this year and has established several KPIs including

“Percentage of customers who renew when their contract expires” and “Save rate –

the percentage of customers who are persuaded to stay when they call in to

cancel.” These are the Retention KPIs.

While the efficiency of B2C’s process for handling customer renewals and the steps

it takes when someone cancels contribute to these KPIs, it is more helpful to

consider the action taken by a call center representative in each case. Specifically,

the retention offer chosen at that moment is critically important.

In other words, the “Retention Offer Decision” is a key operational decision that

impacts the Retention KPI.

Identifying the retention offer decision enables B2C to discuss how they want to

retain customers, how they might determine the value of retaining different kinds

of customers, which departments should have a say in the retention approach and

more. Making the decision explicit gives a focus for these business discussions.

A typical retention scenario involves making retention offers across multiple

channels each with different applications and platforms. These applications are

optimized for supporting a specific channel – a website or a call center for instance.

This means a high risk of inconsistency – the retention decision B2C makes is likely

to be inconsistent across channels. B2C makes thousands of retention decisions

every day and how effective a retention decision will be is highly dependent on our

competitors. Multi-channel, high-volume and dependent on outside forces – clearly

the retention offer decision is a good candidate for high ROI use of business rules.

Once identified, this decision can now be modeled. The various elements that make

up the decision – the sub-decisions – can be identified to give the decision

structure. How the decision and its sub-decisions use data can be clearly specified

and all the various source of decision-making know-how (policies, regulations,

expertise and analytics) can be identified. A complete model of the decision-

making can be defined.



Decision Service Definition and Implementation

Decision Services are the implementation of a decision – how systems will find out

what the best or most appropriate decision is for a particular customer or

transaction. A decision service also makes the decision reusable and widely

available.

Decision Services are essentially business services in a Service Oriented Architecture

(SOA) that deliver an answer to a specific question. These services generally do not

update information – they just answer questions such as “how should we handle this

claim?” or “what is the right discount for this order?” Because they don’t make any

permanent changes, they can be used to answer questions whenever they come up

without worrying about potential side effects.

The usual SOA infrastructure is used to access a decision service. The decision

Figure 3. Decision Services



service can access enterprise resources and other services (using the same SOA

infrastructure) and can make various business-level interfaces available for other

services to use. Decision Services are built primarily using business rules managed

using a Business Rules Management System or BRMS. While many only need a BRMS,

they also support the integration of predictive analytics now or in the future. Figure

3 shows how these elements come together to provide Decision Services across an

application portfolio.

Business Rules

Having found and modeled high ROI decisions, the next step is to define the

business rules that support them. Business rules represent the expertise, tribal

knowledge, regulations and policies that drive a business. Mining business rules

from software code, reviewing regulations and policy manuals, interviewing experts

and many other techniques can be used to find the rules that support the decisions.

Business rules are the core building block of the decisions in decision services.

Business rules create a language the business and IT can both understand – essential

for effective Decision Management. Business rules are maintained in a repository or

catalog that is updated by both business and technical users.

Decision Models and Business Rules

The decision model is used to scope and bound the decision service by identifying

the decisions that should be included – those inside the automation boundary. The

business rules for each of these decisions are identified and managed in the BRMS.

The decision model acts as a framework for capturing and defining the business

rules, keeping each set of business rules focused on a particular sub-decision. The

knowledge sources identified in the model show where the rules can be found and

the input data show how data is consumed by these business rules in order to make

a decision.

The business rules for a decision are most commonly represented as decision tables

or rule sheets, as shown in Figure 4. These tabular representations allow many rules

to be presented in a compact format while allowing easy verification of the rules

against the decision model and verification of completeness.

Where a tabular layout is inappropriate, business rules can also be controlled by

customizable rule templates that incorporate organization-specific terms to make

them easier for non-technical users to understand and edit. Some BRMS also support

additional business rules representations such as decision trees or decision graphs.

Business rules are also used in workflow, to manage data quality in a database or to control a user

interface. These are effective uses of business rules but are different than the business rules that are

built into a Decision Service. The rules used for a Decision Service are truly about the business and how it

should act. They are independent of a company’s current databases, systems or processes.



These representations further ensure that the decisions can be managed by those

who understand the business context of those decisions.

Focusing on the business rules for a specific decision helps avoid a common problem

in business rules implementations. Business rules are everywhere in an

organization. Collecting and managing those rules without an organizing driver can

result in lots of rules being managed for relatively low business impact. Certainly,

everyone understands the rules better and it is easier to find and update them but

the company will not maximize the return from this investment unless business

performance has improved as a result. Focusing on the decisions ensures that this

will be the case. A focus on decisions increases the value of a rule repository and of

an effective system for managing rules.

Business Rules Management Systems

Using a BRMS to encode business rules has several advantages that are critical to

managing decisions, even when the equivalent software code would be simple:

The syntax is clearer to a non-programmer so that decisions built with them can

be managed by non-programmers

The rules can easily be reused across multiple systems that use the decisions

The rules are independent. No sequence is implied making it possible to edit

them, and thus change decisions, to respond to changing business

circumstances, without unintended consequences.

Figure 4. An example Decision Table

Real-World Decision Modeling with DMN, Figure 11-11



The basic components of a BRMS are shown in Figure 5. Technical and non-technical

rule management, a rule repository, verification, impact analysis and testing tools.

Decision Services are generated from these other elements. Designing the

repository, giving business users rule management capability, verification, testing

and deployment will all be simplified by focusing on specific decisions.

B2C, Part 2

Once B2C recognizes that a retention decision is required and makes it explicit they

are ready to automate it consistently across their various channels. They develop a

Decision Service that is used by each channel. For example, instead of the website

making its own retention decision, it will use the Retention Decision Service to

determine the appropriate offer for a specific customer when it is needed and

deliver that through the web channel. The call center, outbound marketing and

other channels will also use the Retention Decision Service.

Figure 5. Components of a Business Rules Management System

Source: Decision Management Systems Platform Technology Report



Having identified and modeled their retention decision, B2C wants to specify it with

business rules to make it flexible, agile and business-centric. A BRMS enables them

to specify the decision in a way that is easy to update, easy to manage and

accessible to the business users who understand retention. This ensures their

retention offers will reflect their business strategy, best practices and the know-

how of their most successful agents.

For this retention decision B2C gathers rules from the customer service

representatives with the best history of cost-effectively retaining customers, from

the head of customer service, from existing policy manuals and from existing

customer service scripts. Collecting, normalizing and reviewing these rules give

them a first cut rule set for retention decisions.

Predictive Analytics

Although many rules are written based on judgment, tribal knowledge, regulations

and policies, this information can be augmented by using data mining and analytics

to find or refine business rules. Increasingly common, this approach can be an

important complement to business rules for some decisions. Decision Management

is the framework that links business rules to analytical and data mining insights and

uses those insights to improve operational decisions.

Many BRMS support a Decision Tree metaphor and many data mining techniques

create decision trees to divide populations as, for

instance, in customer segmentation. Representing these

models in a BRMS allows them to be seen, managed and

potentially updated by business users. Business rule

management systems can also use decision tables to

implement the models that result from data mining and

analytics techniques as score cards. These represent a

collection of rules that “score” a particular customer or

transaction depending on the value of specific attributes.

In the Figure 6, the scorecard shows that spending two or

more years at your current employer adds 50 to your risk

score. The total score can easily be calculated from the

various elements of the score card. BRMSs execute these

score cards quickly and effectively while the data mining

and analytic tools and techniques find out which

attributes make a difference and what values for those

attributes predict behavior. Implemented as a score card,

the predictive model is easily used in any decision based

on rules.

Figure 6. A Predictive Scorecard Table

Source: Smart (Enough) Systems



B2C, Part 3

B2C could do a better job of making retention offers if it knew who was a retention

risk. This would allow them to spend on retention offers for customers who are at

risk not those that will stay anyway. But to be effective they must make retention

offers before a customer decides to leave.

Using data mining techniques B2C uses historical data about which customers left to

estimate the probability of a particular customer failing to renew (their retention

risk). This results in a scorecard that weights and totals these predictors into a risk

score. Implementing this scorecard in the rule technology means the score is used

by rules to target customers who are a risk more precisely. This allows B2C to write

rules that focus their most expensive offers on profitable customers who are at high

risk of leaving.

Decision Monitoring and Improvement

Decision Morning and Improvement involves the application of performance

management techniques and technologies to the monitoring of decisions. With a

Decision Management approach, the business understands how specific decisions

create value. These decisions are linked to the business and individual performance

metrics being tracked. To continuously improve business performance, Decision

Management monitors decision performance, throughput and basic statistics. How

many decisions are made to approve, reject or refer is a measure of decision

effectiveness. Too many referrals will increase the burden on staff doing manual

reviews. Too many rejections, thanks to false positives for instance, will impact

customer service or sales. Similarly, decisions that take too long or that cost too

much (because they use data that must be purchased, for instance) may have a

negative overall impact. Tracking and reporting on this information will help the

business owners understand and thus manage their decisions more effectively.

B2C, Part 4

B2C manages the performance of its retention decision by tracking which customers

are, in fact retained as well as the offer made and its cost. Business users see what

specific offers cost relative to their effectiveness so they can improve the cost-

effectiveness of the decision.

B2C tests out new ideas for renewal rules to see how a particular approach –say a

more expensive and aggressive one – would affect results. If the additional

customers retained would be worth the additional cost they can deploy the new

approach, improving the decision. The monitoring and analysis of the decision,

along with its mapping to key company KPIs, allows them to continuously improve

it.



Decision Modeling

Decision modeling is fast becoming a best practice for business rules projects,

replacing traditional rules analysis approaches that were created before modern

BRMS capabilities.

Decision modeling is specified using the Object Management Group’s Decision Model

and Notation (DMN) standard. This industry standard gives users access to a broad

community and a vehicle for sharing expertise more widely. It is also a technique in

the International Institute of Business Analysts (IIBA) Business Analyst Body of

Knowledge or BABOK®, giving business analysts an industry standard approach to

accurately describe decision requirements that are

essential for today’s data-driven projects focused on

improving decision making.

The example model in Figure 7 uses the Decision

Model and Notation (DMN) standard notation. It

shows a marketing offer decision (a rectangle) along

with its sub-decisions (and sub-sub decisions), the

input data entities (ovals) that are required by each

of these decisions and sub-decisions, and the

knowledge sources (document share) that constrain

or guide the decisions.

Decisions First

The rules-first, natural language rulebook

approaches used historically tend to capture many

individual rules in a rush to detail. This results in

large numbers of low-level rules, often with multiple

versions, that quickly become hard to change and maintain.

Often written in natural language and phrased as constraints, these rules must be

converted to the executable rules and rule metaphors that will work in a BRMS. This

is an additional step and creates situations where multiple versions of a rule are

being maintained. This step is no longer needed given the capabilities of a modern

BRMS. The creation of an independent fact model and vocabulary that must be

mapped to the implementation data model can exacerbate this severely,

sometimes resulting in yet more versions of each rule.

The rules-first approaches can seem fine for the initial project, but quickly the

rules can become complex and hard to manage. Teams will often try to add rules to

their business process diagrams, placing each individual rule on the process

diagram. Most of the low-level rules cannot be placed in this way and doing so

contribute to over-complex business processes. There’s also no organizational

structure to the rules so they end up being grouped by source or by the person

Figure 7. Example Decision Model

Source: DecisionsFirst Modeler



doing the rule identification. As policies or regulations change, or as new business

needs are identified, the team often struggles to update the right business rules.

The decisions-first decision management approach begins with the higher-level

concept of the decision. This provides:

A higher, overarching principle to impose some business oriented structure on

this complexity.

The separation of a declarative definition of these rules from the sequence-

oriented business process – improving both.

A structure that can be expanded in a series of iterations, allowing progress to

be made in a more agile and less waterfall approach.

Specifying a graphical decision requirements model based on the Decision Model

and Notation (DMN) standard provides a repeatable, scalable approach to

scoping and managing decision-making requirements, making it easier to:

Draw the automation boundaries.

Re-use, evolve, and manage rules beyond the first business rules project.

Consolidate business rules across multiple implementations and platforms.

Assign ownership, governance and sources appropriately.

The Role of Decision Modeling

Decision Modeling has a role in all of the Decision Management phases. As shown in

Figure 8, Decision Modeling:

Builds a transparent and unambiguous

definition of the decision at the beginning

of the project, before rules are gathered,

providing a decisions first, top-down view.

Scopes and specifies the interface and

content of Decision Services. The decision

model structures the internals of the

decision service and provides a business-

focused structure for the rules in the

service.

Finally it establishes meaningful and

business-centric measurement criteria and

structures the monitoring and improvement

activities, closing the loop back to the

original decision.

Figure 8. Decision Modeling Supports All Phases



Decision Model - BRMS Integration

Integrating a Decision Requirements Model with a BRMS implementation allows

decision requirements models to be linked directly to the business rules that

implement them. Decision Management Solutions’ DecisionsFirst Modeler offers

integration with leading BRMS’s.

The integration automatically generates links between the BRMS and DecisionsFirst

Modeler as a project progresses and are updated automatically. The integration

provides:

Full traceability from business objectives through decision requirements models

to the business rules running in production.

Full access to all the rule editing, validation, testing and deployment

capabilities of the BRMS

Standard security of the BRMS to ensure only authorized users can access the

rules.

DecisionsFirst Modeler does not

capture implementation details

such as business rules or decision

tables in our models as this results

in duplication—there would be one

version in the model and another in

your implementation environment.

Instead it links Decisions to

Implementation Components

representing the business rules,

decision tables or decision trees in

the BRMS. Because the relationship

between Decisions and

Implementation Components is

many:many, reuse of logic between

Decisions is supported.

For example, in Figure 9, the

decision table in IBM Operational

Decision Manager containing the

rules for the Rental Agreement

Surcharge is directly linked to that

decision in the model.

Figure 9. Decision Model in DecisionsFirst Modeler link to BRMSs

A detailed description of how to do decision modeling is described in our free white paper, Decision

Modeling with DMN, available in the white paper section of our website.

http://www.decisionmanagementsolutions.com/whitepaper/decision-modeling-with-dmn/



Conclusion

Decision Management is the framework you need to ensure the success of your first

business rules project or expand your adoption of business rules. Decision

Management is focused on business drivers and on the decisions that impact them,

so you can apply your BRMS where it will make the most difference for a clear ROI.

Decision Management systematically works through identifying and modeling these

decisions and mapping these decisions to your business objectives. Decision Services

are designed and implemented using your BRMS to ensure accurate decision-making

and business agility. The effectiveness of decisions is constantly monitored so that

the decisions can be continuously improved.

Decision Management delivers clear priorities for applying business rules and a BRMS

for maximum ROI, give each project a clear objective and delivers a robust

monitoring and improvement framework to keep you competitive over time.

Decision Management is a proven framework that ties business rules to business

objectives. A Decision Management approach to business rules begins by looking at

business performance drivers and focusing on the decisions that have the biggest

return. Decision Management streamlines BRMS implementation, ensures business

ownership of the business rules, and delivers agility and continuous improvement.

For More Information

Taylor, James and Purchase, Jan (2016). Real-World Decision Modeling with

DMN. Meghan-Kiffer Press.

Taylor, James (2011). Decision Management Systems – A Practical Guide to

Using Business Rules and Predictive Analytics. IBM Press.

Decision Management Solutions (2013-2015), Decision Management Systems

Platform Technology Report.

Decision Management Solutions (2017), Decision Modeling with DMN.

Taylor, James and Raden, Neil (2007). Smart (Enough) Systems. Prentice Hall.

CONTACT US

Decision Management Solutions specializes in helping organizations build decision-centric, action-

oriented systems and processes using decision management, business rules and advanced analytic

technologies.

www.decisionmanagementsolutions.com Email: [email protected]

http://www.mkpress.com/DMN/

http://www.mkpress.com/DMN/

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http://decisionmanagementsolutions.com/decision-management-technology

http://decisionmanagementsolutions.com/decision-management-technology


http://www.decisionmanagementsolutions.com/

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https://twitter.com/decisionmgt

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