business process transformation with decision …...2017/01/11 · simpler and more agile processes...

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Organizations looking to transform their business can create

simpler and more agile processes, and more flexible business

applications, by externalizing and improving decisions.

Organizations cannot change more quickly than their processes and systems—

when these are hard to change organizations cannot react quickly or effectively to

new opportunities, new regulations or new challenges. Making decisions explicit and

managing them in concert with processes ensures an effective

separation of concerns and a more streamlined business.

Decision modeling results in:

Simpler and more agile processes.

More flexible business applications.

Increased capacity for change.

Improved organizational alignment.

Leading organizations are building an internal

Decision Management capability–modeling

the relevant operational decisions that drive

the results they seek, replacing decision logic

hardcoded within business applications or

modeled in business processes with

independent Decision Services, and applying

advanced analytics to improve these

decisions. And they close the loop, ensuring

that business results continually improve.

Resulting performance improvements are

impressive:

Error-free daily updates to pricing rules.

95% automation of pension fund updates.

98% time reduction to implement regulations.

Companies adopting Decision Management report “game

changing” cultural impacts, driving the process innovation

needed for the adoption of adaptive, agile and analytic technologies

that are essential for leveraging big data and meeting the needs of today's

businesses and the social and mobile consumers they serve.

Business Process Transformation

with Decision Modeling

How Decision Management Simplifies Business

Processes and Improves Results

© 2017 Decision Management Solutions

CONTENTS

Decision-Led Process

Transformation

Building A Decision

Management Capability

Conclusion

Business Process Transformation with Decision Modeling

© 2017 Decision Management Solutions 2

Decision-Led Process Transformation

Simpler and More Agile Processes

An important part of Business Process Management is understanding your “as-is”

processes to see how your business is truly operating. This understanding improves

visibility and allows optimization of the process—the creation of an effective “to-be”

process. Most, if not all, business processes require decisions to be made: claims

must be approved or rejected, cross-sell offers must be selected, and product

discounts must be calculated. Explicitly modeling the decisions that happen in your

business process ensures that the as-is model is closer to reality.

When a business process must handle multiple scenarios, modeling the decision-

making in a process using only gateways and tasks can become very complex.

Decision Management replaces a nest of gateways with a single, explicit decision

task. Decision Management clarifies the behavior of the process, makes it easier to

see if the process or the decision must change, and allows for changes in the

decision-making approach to be independent from process change.

Figures 1 and 2 show a process before and after Decision Management has been

applied. The “before” version shows creeping complexity. As more conditions and

exceptions are added the process becomes increasingly complex. With an explicit

decision-making activity—Determine Applicant Risk—the process is much simpler

and will remain so even as new conditions are added.

Figure 1: Before Decision

Management

Figure 2: After Decision

Management

Decision Management also increases the rate of straight through processing and

reduces the number of process instances that wait while items are put on worklists

or in queues. Decision Management marries explicit decisions and process

management to keep transactions moving with only exceptions ending up on

worklists or in an inbox.

Capturing the know-how of experts in explicit decision logic using decision

modeling, and making it widely available, focuses scarce expert resources on

exceptions and high-value cases and customers. Graphical decision models 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 3 is the Determine

Applicant Risk decision model

for the above example. Decision

modeling 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.

The number of exceptions can also be systematically reduced over time by

developing new rules as process execution is observed—observing process

performance, identifying new rules to handle particular cases, and automating those

rules results in continuous improvement and process optimization.

More Flexible Business Applications

Business applications are rich sources of functionality for new and extended

processes. Modern business applications like ERP and CRM are service-enabled,

using a service-oriented architecture and exposing critical functionality as reusable

services. Business Process Management focuses on rapidly automating or improving

a process by integrating this functionality. When bringing application functionality

into processes, Decision Management ensures that the behavior of these functions is

accessible to business users so they can change it, and so that it can be shared

between multiple processes and applications.

Figure 3: Decision Model

Source: DecisionsFirst Modeler

Some process models today are developed using the Business Process Model and

Notation (BPMN) standard published by the Object Management Group. The

Decision Model and Notation (DMN) standard has been designed to work

alongside BPMN, providing a mechanism for modeling the decision-making

represented in a Task within a process model. DMN need not be used with BPMN

but it is highly compatible with BPMN.



For example, a core business application for order processing must be able to price

products accurately. For an organization with lots of options or configurations,

pricing can be very complex. If the pricing component is coded or managed using

database tables, the degree of flexibility and the ability of the business users to define

new pricing models, or new configuration options that require different pricing, will

be limited.

Furthermore, if this component is embedded in a new process such as one designed

to help customers price out and consider various options as part of a move to self-

service, say, then the flexibility and agility of this new process will be compromised.

It won’t matter how easy it is to change the lists of products that a customer sees

or how easy it is to change the process, the pricing model will act as a drag or

limiting factor – no change can be made faster than the pricing model can be

recoded.

The agility and flexibility of the process, and of the underlying business applications,

is constrained by the flexibility of the components being shared. Yet the components

of a business application most useful to business processes are often decision-making

components such as pricing engines, product configurators or eligibility

determinations. More importantly, decision making components change often—they

are among the most dynamic parts of the application. Decision Management ensures

that decision making components are flexible. Because they can be shared service,

this also increases the agility of both the processes that use it and the applications

that include it.

Increased Capacity for Change

Organizations cannot change more quickly than their systems—when systems are

hard to change organizations cannot react quickly or effectively to new

opportunities, new regulations or new challenges. Manual processes are no better as

updating policy manuals and retraining staff is time-consuming and expensive.

Business users like BPM software because it allows them to change their workflow

easily—it increases the capacity for change of the process. Decision Management

further increases this capacity as business changes often involve updates to business

decisions—to pricing, eligibility or risk assessment decisions, for example. These

decisions are often the most dynamic part of a process.

“Decision modeling enables us to model our business by dividing it into concrete parts

that are understandable to business people without being too detailed. It also helps us not

to lose sight of the overall picture of the process while delving deep into the details of

business rules.”

Process Director, Tax Authority



For example, a company’s

pricing rules are likely to change

far more often than its order-

to-cash process as shown in

Figure 4. If business users can

only change the process, then

they will not be able to respond

to the far more numerous

pricing changes without changing

the process, an unnecessary

step.

Adding Decision Management

enables business users to

control processes and the critical decisions within them. This increases the capacity

for change built into a process and allows for a stable process even when decision-

making is constantly changing and evolving.

Explicitly identifying decisions and describing the logic behind them allows this logic

to be managed and updated separately from the process itself, dramatically

increasing the agility of an organization.

Improved Alignment

Given the importance of systems and processes to today’s organizations, business

performance improves when business and IT professionals are aligned. Processes

and systems are aligned when the business and IT have a shared understanding of

the workflow and the logic in a system. They are aligned when the business has an

appropriate level of access and control of their systems. A focus on decisions with

Decision Management enables this alignment.

The Power of Decision Management

Companies adopting Decision Management report “game changing” cultural impacts.

Simpler processes, more flexible business applications, an increased capacity for

change and improved business alignment— Decision Management enhances Business

Process Management to deliver greater value to the business. Decision Management

focuses on the decisions at the heart of your business processes. Decision

Management makes them explicit and gives the business control over how those

decisions are being made. Decision Management drives the process innovation

needed for the adoption of adaptive, agile and analytic technologies that are essential

for leveraging big data and meeting the needs of today's businesses and the social

and mobile consumers they serve.

Figure 4: Repeated Pricing Updates



Building A Decision Management Capability

Companies adopting Decision Management use Decision Discovery to find the

relevant operational decisions that drive the results they seek. They replace decision

logic hardcoded within business applications or modeled in business processes with

independent Decision Services built using a Business Rules Management System

(BRMS). They apply advanced analytics to improve the decisions. And they close the

loop with Decision Analysis, ensuring that business results constantly improve.

Decision Discovery

Decision Discovery starts by determining which operational decisions matter most

to your organization. Which decisions are most relevant to the business strategies

your executive team has put at the top of its agenda? Which decisions could have

the strongest impact on the business drivers and measures being used to chart

progress toward those goals? These are the decisions where Decision Management

will deliver the biggest and quickest pay-off for your business. Identifying these

decisions shows you where to focus your efforts and streamlines the project.

Decision Management is a proven approach for reducing implementation time and

costs.

The next step in Decision Discovery is to separate these critical operational

decisions from your business processes and IT systems. Describing and visualizing

previously hardcoded or embedded decisions as separate, discrete decision

processes using decision modeling with the Decision Model and Notation (DMN)

standard helps business stakeholders understand and take ownership of how

decisions are currently being made. It also enables decision-making to be explicitly

linked to key performance indicators and other metrics.

With improved clarity around which decisions drive results, how they’re being made

and their impact on performance, you can now determine what changes to decision-

making will be required to improve any given measure.

“What used to be one week of requirements work was done in a few hours with decision management.”

Lead Business Analyst, North American Insurance Company



The outcome of Decision Discovery is an understanding of the current differences is

our retention decision-making processes and awareness that they are driven by

channel rather than customer value. Our aim is to switch that situation so that

we’re making retention decisions based on customer value consistently across all

channels.

Decision Services

Having identified high-ROI operational decisions and determined what you need to

do to improve them, your next step is to design and build a Decision Service.

The Decision Service replaces the decision logic currently embedded in business

processes and business applications. Decision services are built on a Business Rules

Management System (BRMS) and generally deployed via a Service Oriented

Architecture (SOA) to deliver decisions on-demand to business applications as

shown in Figure 5. Decision Services generally do not update information—they just

answer questions—and thus have minimal runtime impact on operational systems.

EXAMPLE Let’s look at how Decision Discovery works to improve performance

in customer retention. We identify three critical decisions impacting our retention

rate:

Decision of which customers to target for retention programs.

Decision about what retention offer to make.

Decision about how and when to make it.

These decisions are currently embedded in the several different account

management processes and systems used by various channels.

Depicting them as separate decision models enables our customer management

and customer marketing groups to see clearly that these retention decisions are

currently being made using different criteria and data in different channels (and not

in ways that can be justified by channel-specific characteristics).

We also see that within a channel we are treating all customers targeted for

renewal the same way.

Linking decision data to revenue and profit metrics, it’s clear that this “one size fits

all” approach isn’t helping us retain our most valuable customers.

Decision modeling is equally useful for decision support systems such as dashboards. Most dashboards

are driven by user interface and information visualization requirements and by the underlying data

models. A dashboard design based on decision modeling provides a logical structure for going beyond

information presentation to include predictions and recommendations so users can progress from ‘what

happened?’ to ‘what can happen?’ and ‘what action can be taken?’



The building blocks of Decision Services are the business rules you need to drive

and your decisions. Business rules comprise expertise, policies, regulations and even

what might be considered “tribal knowledge” about how your organization does

business. Decision modeling using DMN provides a framework for capturing this

valuable know-how and making it explicit. The detailed decision logic itself can be

included in the model based on business rules mined from software code, found in

regulations and policy manuals or determined by interviewing experts.

Figure 5: Decision Services

Analytics can also be used: rule induction techniques find rules that represent

customer behavior patterns; classification and regression techniques can generate

decision trees capturing the rules being used for population segmentation.

Business rules put decision logic that used to be buried in code into a language that

everyone (analysts, IT, business users, and regulators) can understand. They’re

generally maintained in a common repository, accessible to and updated by both

business and technical users.

The ability to share and repurpose these building blocks substantially reduces the

time and cost involved in development and maintenance. Shared understanding

between business and IT builds organizational alignment and collaboration.

Organizations that are developing their first Decision Services often move on to

testing, simulation and deployment at this point. A best-in-class BRMS will provide

easy tools that enable business users to validate their rules, simulate the impact of

new rules and changes by comparing multiple “What if?” scenarios and, when



satisfied, deploy into virtually any operational environment with almost push-button

ease.

At some point, however, most organizations want to enhance their Decision Service

by incorporating predictive analytics into the decision making. Analytic models that

predict customer behavior (response, revenue, profit, churn) increase precision in

segmentation and targeting. For more on this, see our paper “Putting Predictive

Analytics to Work in Operations”.

Decision Analysis

Once the Decision Service has been deployed it is easy to apply performance

management techniques and technologies to monitor and measure it. This also

allows you to continually improve decisions for increased value over time.

Most companies set up a “closed-loop” system that captures data about decision-

making approaches, decisions and outcomes and makes them available to the

business for ongoing analysis.

Typically there are two levels of analysis. The first is about decision performance.

Decision outcomes are analyzed against the business drivers and metrics originally

identified during the Decision Discovery process. Overall, has the new Decision

EXAMPLE If we pick up our customer retention example again, our task at this

point is to design and build an automated Decision Service that will serve all

channels by delivering decisions to the operational systems already existing in

those channels. These will be decisions about which customers we want to retain

and, for each customer identified, what retention offer to make and how and when

to make it. To do this we need to author the business rules that will drive the

automated decision. The input for rule authoring includes content from policy

manuals, decision logic extracted from our account management systems and

knowledge amassed from interviews with our account management and channel

experts.

Our IT folks do some of the initial authoring, and link up with runtime data

sources. These business rules are linked back to the original decision model so

that impact analysis and the identification of the rules that need to change is

straightforward. Business experts in our account management department do

much of the refinement, however, using the decision model to find the business

rules they need to change and running simulations in the BRMS to see how

tweaking rules this way or that might affect our retention levels. While a

consistent decision will be used by all channels, channel-specific rules will kick in

when appropriate to make adjustments where necessary. The result is a decision-

making approach under business control that is applied consistently every time, in

every channel.

http://www.decisionmanagementsolutions.com/pawork

http://www.decisionmanagementsolutions.com/pawork



Service “moved the needle” and by how much? Looking at each of your population

segments, how have the business-rules-driven decisions affected results?

Leading companies generally also use a process called “champion-challenger”, also

sometimes called A/B testing. This is a systematic method of making changes to

rules, predictive models or other elements of a decision and then testing this

“challenger” alternative on a randomly selected small percentage of the production

population. You then compare the results to those of the existing “champion,”

which has been applied to the bulk of your population. If the “challenger” results are

better, you then promote it to become the new “champion” and roll it out across

the rest of the population—except for another small percentage where you test

another “challenger.” And on and on it goes, incrementally improving value over

time.

The second level of Decision Analysis you need to do is around fine tuning the

Decision Service to operational conditions. This involves collecting data on

throughput, response time, cost (e.g., for external data) and other basic statistics. In

customer acquisition, for instance, how many decisions are being made to approve,

reject or refer applications? Too many rejections will impact revenue. Too many

approvals can raise risk to unacceptable levels. Too many referrals can overwhelm

staff doing manual reviews. A good BRMS will enable business managers to quickly

modify rules, scoring thresholds or other elements to adjust for variable staffing

levels and other operational realities.

EXAMPLE Finishing up with our customer retention example, decision monitoring

and analysis tells us that our Decision Service is having an overall positive impact

on two key metrics: Customer retention has improved by 5%, and annual revenue

per retained customer has jumped by 2%. Looking at these metrics as well as

response rates within each segment, we see that some of our targeted retention

programs are proving more effective than others.

Results in one segment, in particular, are lagging. Using simulation tools, we try

several “What if?” changes to our decision rules. For the best of these scenarios,

the simulation projects a very strong uptick in both response and retention rates.

We test this change on a small percentage of our population before rolling the

changes out to the entire segment.



A Note on Decision Modeling

There is an emerging consensus

that a Decision Requirements

Model is the best way to specify

decision-making. Decision

Requirements Models can and

should be developed in an

industry standard way using the

Object Management Group’s

Decision Model and Notation

standard. Adopting this industry

standard gives users access to a

broad community and a vehicle

for sharing expertise more

widely.

Today business analysts use a variety of techniques to accurately describe the

requirements for an information system. However, current requirements

approaches don’t tackle the decision-making that is increasingly important in

information systems.

A Decision Requirements Model provides the needed structure for the

implementation of a Business Rules Management Systems (BRMS), supporting

iteration and agile development.

Framing data mining and predictive analytics projects with a Decision

Requirements Model links analytics to business results and helps ensure

successful deployment.

Understanding the decisions relevant to a dashboard or decision support

environment structures knowledge and puts a premium on taking action.

Decision Requirements Models are a common language across business, IT and

analytic organizations improving collaboration, increasing reuse, and easing

implementation.

Figure 6: Example Decision Model

Source: DecisionsFirst Modeler

Decision modeling is a technique in the International Institute of Business Analysts (IIBA)

Business Analyst Body of Knowledge (BABOK®) v3.

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/decision-modeling-with-dmn



Conclusion

Decision-led process transformation is a powerful approach to business

performance improvement. But how much improvement are we talking about?

When companies use Decision Management to reduce the complexity of their

business processes and improve agility, the results can be dramatic. For example, a

truck manufacturer had a warranty claims process that took one week thanks to the

complexity of the warranty arrangements with suppliers. Replacing this manual

process with one based on a BPM system, Decision Management and a Business

Rules Management System reduced the time to process a claim from one week to

just 6 hours. Other companies have achieved similarly impressive results:

99% auto adjudication of claims (up from 20%).

50% reductions in managerial oversight.

Error-free daily updates to pricing rules.

95% automation of pension fund update requests.

98% reduction in time to implement regulations.

Organizations can’t change more quickly than their processes and systems—when

these are hard to change organizations cannot react quickly or effectively to new

opportunities, new regulations or new challenges. Making decisions explicit and

managing them in concert with processes ensures an effective separation of

concerns and a more streamlined business.



References

This white paper can be found at decisionmanagementsolutions.com along with links

to other materials and on-demand webinars.

Debevoise, Tom and Taylor, James (2014). The MicroGuide to Process and

Decision Modeling in BPMN/DMN: Building More Effective Processes by

Integrating Process Modeling with Decision Modeling.

International Institute of Business Analysts®. Business Analyst Body of

Knowledge®

Object Management Group. Decision Model and Notation (DMN) Specification

1.0, Current version at http://www.omg.org/spec/DMN/Current

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

Using Business Rules and Predictive Analytics. IBM Press.

Taylor James with Raden N, Smart (Enough) Systems: How to Deliver

Competitive Advantage by Automating Hidden Decisions. (New York: Prentice

Hall: 2007)

About Decision Management Solutions

Decision Management Solutions specializes in helping organizations design, build and

implement decision-centric, action-oriented systems and processes using decision

management. We help clients improve business processes, effectively manage

business rules projects, frame predictive analytics efforts, and ensure decision

support systems and dashboards are action-oriented.

We offer a wide range of resources, training and consulting to help you build your

decision management capability. Our collaborative decision modeling software,

DecisionsFirst Modeler, is based on the Decision Model Notation (DMN) standard.

Contact Us

If you have any questions about Decision Management Solutions or would like to discuss engaging us we

would love to hear from you. Emails works best but feel free to use any of the methods below.

Email : [email protected]

Phone : +1 650 400-3029

Fax : +1 650 352-9247

http://www.decisionmanagementsolutions.com/

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http://www.iiba.org/babok-guide.aspx

http://www.iiba.org/babok-guide.aspx

http://www.omg.org/spec/DMN/Current

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