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DECISIONS, DECISIONS: Using Decision Management to Improve Processes and Operations Decision management involves automating high-volume operational decisions, adding analytical insights and enabling ongoing improvements that deliver genuine business value. This e-book introduces readers to decision management, describing how data-driven decisions can benefit organizations and exploring ways to use new techniques and tools.

Data-Driven Decisions Mean Higher Productivity, Profits

How to Become a ‘Decision-centric’ Organization

Decision Management: A Tool for Adding Agility to Customer-Facing Processes

Closing the ‘Insight-to-Action’ Gap

Identify and Trigger the Best Next Action

The Only Complete & Packaged Business Analytics & Optimization Platform Available Todaywww.starviewinc.com

DATA-DRIVEN DECISIONS

MEAN HIGHER PRODUCTIVITY,

PROFITS

HOW TO BECOME A ‘DECISION-

CENTRIC’ ORGANIZATION

DECISION MANAGEMENT:

A TOOL FOR ADDING AGILITY

TO CUSTOMER- FACING

PROCESSES

CLOSING THE ‘INSIGHT-TO- ACTION’ GAP

USING DECISION MANAGEMENT TO IMPROVE PROCESSES AND OPERATIONS 2

Data-Driven Decisions Mean Higher Productivity, ProfitsBY NICOLE LASKOWSKI, SearchBusinessAnalytics News and Features Editor

RONICALLY FOR A DATA-DRIVEN market, there is almost no comprehensive data showing that implementing business in-telligence and analytics tools

makes a difference to the bottom line. That’s about to change, according to Andrew McAfee, a principal research scientist at the MIT Center for Digital Business.

McAfee and his team recently re-leased the initial findings of a study measuring how companies—from re-tail, manufacturing and beyond—are using technology to make data-driven decisions, and how that technology may impact productivity and profit margins.

“The extent to which a company de-scribes itself as being data-driven is strongly associated with performance,” he says.

In fact, organizations driven most by data-based decision making had 4% higher productivity rates and 6%

higher profits, according to the study.The results may not be surprising,

as anecdotal evidence has existed for years, but the research quantifies the philosophy on a wide scale that cuts across industries.

McAfee and his team, which in-cludes the center’s Director Erik Bryn-jolfsson, examined 330 American companies. Surveys, conducted pri-marily through phone interviews, tapped an organization’s CIO and a second executive or manager, usually a member of the human resources de-partment, about the company’s tech-nical and organizational practices. All businesses surveyed are publicly traded, allowing the researchers to also take advantage of annual reports as a source of information.

“We can look at the actuals, at the profitability and other measurements of performance and health,” McAfee says. “We don’t have to rely on what they tell us about performance.”

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LEADERS AND LAGGARDS ON MAKING DATA-DRIVEN DECISIONSThe MIT survey asked businesses to rate their data-driven decision mak-ing tendencies on a scale of 1 to 5, with 5 being “extremely data-driven.” The results run the gamut, he says, from claiming to be dependent on analytics to just the opposite—relying instead on intuition, experience and exper-tise. Most organizations, according to the data, rated themselves between a 3 and a 4. But many rated themselves below a 3.

Andrew McAfee, a principal re-search scientist at the MIT Center for Digital Business, included additional information about the recent study on his blog, The Business Impact of IT.

These results reflect a gap that ap-pears to exist between purchasing BI technology and deriving business value from it.

Recently, Gartner Inc. released find-ings that the BI software market grew by 13.4% in 2010, reaching $10.5 bil-lion. While McAfee agrees the num-bers show an appetite for BI tools, he says BI projects can go awry at the out-set if good decision-making processes aren’t in place.

“We’ve observed that companies are spending money without a huge amount of great guidance, without knowing how to make the best out of those products,” McAfee says, adding that vendor and consultant promises may not materialize once the product is in place.

But, he adds, the problem is more complicated. Developing a data-driven environment often means a culture change within an organization. Resis-tance to that change can arrest any re-liance on technology altogether, but it can also become a hurdle for adopting and adhering to best practices. Sur-vey results show that most companies feel they struggle with consistent busi-ness practices and, even more so, de-scribe themselves as having poor IT governance.

“Becoming data-driven requires not just an investment in technology, but a lot of training as well,” McAfee says.

‘HEY, DO I NEED A CAR?’McAfee recommends organizations take a more scientific approach to-ward decision making. A perspective that embraces data as a valuable asset can encourage the practice of theory, research and even experimentation, helping to bring analytic capabilities deeper into the organization, he says.

When deciding to acquire new tech-nology, McAfee says there are two broad ways to think about the invest-ment: “Inside-Out” vs. “Outside-In.”

Using the “Outside-In” approach, companies spend time listening to claims of what different products can provide. From there, a company would decide what product to purchase.

“I don’t like that approach,” McAfee says. “None of us would go about buy-



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ing a car by asking ‘Hey, do I need a car?’”

Instead, he recommends the “In-side-Out” approach, or embarking on a technology purchase by first evaluating where needs exist and how technology can help resolve those needs.

He also called for companies to be consistent in their business processes enterprise-wide while at the same time decentralizing data-based decisions.

“People on the front lines can take advantage of what they know by re-sponding to local conditions and mak-ing decisions locally,” he says. “The cool thing about technology is that it allows you to stay on top of those local decisions and see if they’re success-ful or not.” He even recommends the idea of self-organization, pointing to Wikipedia as an example of how creat-ing an environment for people to come together and interact can benefit an organization.

“Self-organization is a scary one to managers because, after all, the way many managers became successful is through orchestration,” he says.

Finally, he says, be externally fo-cused. Stay on top of the market, seek out the latest trends and be proactive when bringing new people into the company.

“Scan the labor market and bring in the best people instead of going through a quick-and-dirty process,” he says. “Spending more time on hir-ing appears to be linked to better performance.”

While an explosion of BI tools have taken hold of the market in the last few years, McAfee predicts more to come with advances in mobile technology, social media and even artificial intel-ligence, all of which he believes can make an impact on the leaders who figure out how to take advantage of them.

Ultimately, the center’s research shows “digitization is not a great equal-izer,” according to McAfee. Instead, be-cause organizations can struggle with management, consistency and imple-mentation of best practices, it is cre-ating a chasm between organizations forging ahead in a data-driven environ-ment and those that are not.

“Technology is separating the lead-ers from the laggards,” he says. “You can opt out, or you can become one of the leaders rather than one of the laggards.” p

NICOLE LASKOWSKI is news and features editor for TechTarget’s SearchBusinessAnalytics.

“Technology is separating the lead ers from the laggards.”— ANDREW McAFEE, principal re search scientist, MIT Center for Digital Business



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How to Become a Decision- centric Organization BY RYAN CLOUTIER, ebizQ Contributor

T’S NO SECRET: COMBINING

automation with decision man-agement can add up to major rewards. But doing the job well requires a “decision-centric”

mindset.By automating and improving opera-

tional business decisions, companies can increase the precision, consistency and agility of those decisions—while saving significant amounts of time and money.

“Operational or ‘micro’ decisions about a single customer or a single transaction are where automation re-ally pays off,” says James Taylor, CEO of Decision Management Solutions. “Even though each decision isn’t worth that much to the organization, the vol-ume of decisions acts as a powerful multiplier. That makes investing in au-tomating these decisions a good idea.” That’s also a good argument for be-coming what Taylor calls “a decision-centric organization,” which he defines

as one that’s moving away “from a fo-cus solely on processes and the func-tional applications that support them to decisions and systems that auto-mate them.”

Of course, decisions have always been critical for businesses. But, in many organizations, they’re ineffec-tive because they’re mired in various functions or processes, says Taylor, co-author of Smart (Enough) Systems: How to Deliver Competitive Advantage by Au-tomating Hidden Decisions (Prentice Hall, 2007). In contrast, organizations that have adopted that decision-cen-tric mindset emphasize streamlining and automating their decisions as well as the use of data and analytics to im-prove them.

AUTOMATION’S BUMPER CROP OF BENEFITSAutomating decision-making can help boost efficiency. But the approach pro-

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vides other benefits as well, Taylor says. Among them are the following:

ppDecreased processing time, lower processing costs. Automating deci-sions allows transactions and other business events to flow smoothly and quickly in a much higher percentage of cases. When necessary, a well-designed system can request manual intervention then quickly return con-trol to the automated system once the issue has been resolved.

ppAbility to create unique processes. Companies want to balance standard processes with taking a customer-centric stance. If the decisions within a process are focused on the right ac-tion for a specific customer, then ev-ery process execution will be unique, even if all the process steps are con-sistent. Each process becomes infi-nitely customizable by making the decisions more specific. By tailoring them to particular customer seg-ments, the processes become more targeted and more customer- centric.

ppIncreasing agility. Decisions are high-change components, and changing decision-making drives many IT projects. Automating deci-sions using business-centric tech-nology such as business rules allows decisions to be changed without re-quiring a full IT lifecycle. That, in turn, enables the business side to make

important changes without dealing with sluggish IT lifecycles. The ap-proach also simplifies the IT struc-ture by removing the most complex aspect—the decision. Instead, it al-lows IT to focus on standardizing processes and developing complex functional components.

BECOMING DECISION-CENTRICSo how do you move toward automa-tion and decision-centricity? Taylor of-fers the following steps:

1. Identify the types of decisions you’re trying to automate. The best candidates are small-scale deci-sions involving a single customer or a single transaction. Also look for decisions that are repeatable, “typically must be made quickly and often must be delivered at the front-line of an organization,” Taylor says. Other types of decisions—such as unique, one-off decisions—are typi-cally too expensive or research-in-tensive to automate.

Automating deci sionsusing business-centrictech nology allows decisions to be changedwithout re quiring a fullIT lifecycle.



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2. Assemble business, IT and analytics teams to build decision services for automating decisions. Once automated, deci-sions can be integrated into the sys-tems, processes and events that use them. Building decision services—or services that make decisions for other services—“involves apply-ing decisioning technology, such as business rules and predictive analytics, in the context of these self-contained, decision-making components,” says Taylor.

3. Monitor, analyze and improve. You can streamline and improve a de-cision-making system only after you’ve seen it work in a real-world situation. That involves establish-ing a monitoring and continuous-

improvement process for decision analysis, Taylor says. “No decision is static, and what makes a decision a good one changes constantly—so an infrastructure for constant evo-lution is required.” Continuously analyzing decision data will further allow you to improve decisions and put your data to work.

Ultimately, effective decision man-agement involves more than just ob-taining new information and insights, Taylor says. “Decisions are a point in time where you have gathered and considered some data and you have a selection to make. You have a set of options you could consider, a set of choices from which you must select,” he says.

Using those options and choices, you can take the right business action, Taylor says. “You can say, ‘Because of what we know, because of the circum-stances in which we find ourselves, be-cause of the rules that apply, we are going to take this action with this cus-tomer or this transaction.’“ p

RYAN CLOUTIER is a contributor to ebizQ and other TechTarget websites.

You can streamline andimprove a decision-making system only afteryou’ve seen it work in areal-world situation.

http://www.ebizq.net/



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Decision Management: A Tool for Adding Agility to Customer-Facing ProcessesBY LYNN HABER, ebizQ Contributor

IN TODAY’S BUSINESS ENVIRON-

ment, two factors are critical for success: insight into what’s happening under the hood of your business and agility for re-

sponding what’s happening both in and around it.

For that reason, a growing number of businesses are beginning to under-stand that effective decision manage-ment can serve as an expressway to improving customer-facing processes.

To many large enterprises, that’s not news. They’ve long had the resources to meet the cost, time commitment and expertise required for making suc-cessful investments in decision man-agement. For smaller organizations, though, that hasn’t typically been the case.

But things are changing. Vendors now offer a wider variety of technolo-gies enabling decision management, making the adoption of such tools more feasible for companies that, un-

til recently, struggled to find affordable solutions. Options now range from decision-management solutions from the market’s big guns to prepackaged, lower-cost, easy-to-use tools from smaller vendors, including those offer-ing business rules, predictive analytics and business intelligence solutions.

Increased access to such tools is especially important now that we’re in what industry experts call an intel-ligent economy, one in which busi-nesses rely more and more on insights gleaned from analytics to keep from falling behind. “There’s growing evi-dence that links performance com-petitiveness with the use of analytics,” says Dan Vesset, program vice presi-dent for business analytics at IDC.

BUSINESS DECISIONS AND CUSTOMER-FACING PROCESSESSuccess in business relies primarily on making the right business decisions,

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and customer-facing processes typi-cally involve hundreds of decisions that need to be made all day long.

But many organizations neglect this type of operational decision-making because they believe or assume that individual front-line decisions have little or no impact, says James Taylor, CEO of Decision Management Solu-tions. In Taylor’s view, such thinking couldn’t be further from the truth. “A company’s brand identity is defined by thousands of these little decisions that ultimately have a cumulative impact that’s huge because decisions of these types occur so often,” he says.

What exactly are “customer-facing processes?”

The category, admittedly broad, en-compasses a variety of processes that fall into the sales, marketing and cus-tomer service functions. Examples of marketing processes include pricing, promotions and product positioning; examples of customer service pro-cesses include ways that call-center representatives can provide callers with product information or resolve complaints. To consider the category another way, think in terms of inter-nal and external activities such as customer acquisition, sales, service, support, development and retention.

Next question: What exactly is deci-sion management and how can it im-prove customer-facing processes?

Decision management is a growing practice of combining software and expertise to automate and improve

decision-making in critical business systems, says Cheryl Wilson, IBM De-mand Program Manager. The approach involves both being able to make the best possible decision right now based on data and situational context and be-ing able to use the data to discover in-sights that can continually improve and automate decisions over time. Exam-ples of decision management applica-tions include product and promotional offers, case and customer prioritiza-tions and determination of fraudulent activity.

Wilson says such decisions may be fully automated, for instance, through an online application or a self-ser-vice point-of-sale system. Or they may be used to provide decision sup-port to people, for example, through a customer relationship management (CRM) system used at a call center, branch or store location, or in the back office.

Perhaps the biggest driver reshap-ing decision management is the on-going shift in how customers interact with companies: They’re increasingly mobile, they rely on the Internet and they want 24/7 service. “Compa-nies are deluding themselves if they think that their staff can handle deci-sions [quickly enough] as customers get more mobile and rely more on the Web,” says Taylor. “And they can’t al-ways refer things up to a supervisor.”

What to do? Automate those deci-sions. Build self-service and mobile ap-plications enabling customers to do



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the things they want to do. Use busi-ness rules management to automate best practices that drive decision im-provement and consistence. Use ad-vanced analytics and data mining to improve decision quality.

Trends in customer Internet usage, mobility and demand for anywhere-anytime service, combined with the explosive growth of data and the devel-opment of more systems for capturing and mining that data—all these factors are combining to help drive decision management into the mainstream.

NEW DIRECTIONS FOR DECISION MANAGEMENTDecision management rolls up into what Hub Vandervoort, CTO for en-terprise infrastructure at Progress Software, calls “responsive process management”—providing better vis-ibility into data or being able to turn decisions into action in the moment. “It’s the ability to be responsive opera-tionally” whether addressing internal or external customer-facing processes, he says.

Up to this point, it’s been up to IT professionals to develop decision man-agement. But now some solutions al-low non-technical business users to express business rules in a cogent way. (Among them is Corticon, a business rules management company that Prog-ress purchased in December 2011.)

Predictive analytics vendors Zemen-tis and Predixion are also reshaping decision management with cloud offer-ings. Zementis’s Adapa Software as a Service (SaaS) solution, is a standards-based decision engine that works with models created in any data-mining package that outputs the standard Predictive Model Markup Language (PMML). Predixion offers self-service predictive analytics that fully integrate with Microsoft’s business intelligence platform, including SharePoint and Ex-cel 2010.

According to user surveys from Gartner Inc., the need for better deci-sion-making is a key driver of BI pur-chases. Meanwhile, BI capabilities are increasingly being embedded in busi-ness and analytic processes and pack-aged analytic applications. You can expect BI to become increasingly more actionable at the point of decision, which will drive both the value and adoption of BI/analytic tools.

Finally, collaborative aspects of BI tools also make them more acces-sible to small and midsized organi-zations via popular products such as Microsoft SharePoint. As a result, says Taylor, “We’re seeing more companies catch up with the potential of the technology.” p

LYNN HABER is a freelance business and technol-ogy journalist who frequently contributes to ebizQ and other TechTarget sites.



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Closing the ‘Insight-to-Action’ Gap with Decision Management and Analytics BY ANNE STUART, ebizQ Site Editor

OR JAMES TAYLOR, CEO of Decision Management Solutions, improving operational intelligence starts by contrasting

two familiar concepts: efficiency and effectiveness.

“There’s a famous definition of effec-tiveness versus efficiency: Efficiency is doing things right, and effectiveness is doing the right thing,” Taylor says, quoting famed management expert Pe-ter F. Drucker.

Taylor drills down into that definition in the context of business processes: “If we think about efficiency—doing the thing right—we get a lot of things that are typically measures of success-ful BPM projects: time to complete a process, cost to serve a customer, cost to process an order,” which are the kinds of things in which a good BPM project can really help eliminate pro-cess inefficiencies.

But thinking about effectiveness generates a slightly different set of measures: “We get things like cus-tomer profitability or customer reten-tion,” among others, he says. Those types of measures are less likely to be obviously linked to business-process initiatives.

Taylor cites an insurance company as an example. “If we have completely innovated and improved our claims-processing process, but we’re paying the wrong claims, then it doesn’t re-ally matter how efficient our processes are—we’re going to have a very poor claim ratio. So our effectiveness mea-sures cannot be improved simply by au-tomating and streamlining our business processes. We must do more,” he says.

In Taylor’s view, doing more boils down to analytics. “I believe the use of analytics—particularly the use of ana-lytics in the context of an operational business process—is key to driving this

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kind of effectiveness improvement,” he says.

Effectiveness is especially impor-tant today, when organizations find themselves capturing and struggling to manage tremendous amounts of operational data, Taylor says. Analyt-ics help businesses simplify data so that they can apply it, learn from it and make better decisions as a result.

DEFINING ANALYTICSAnalytics is a powerful term—one that’s currently generating plenty of buzz and some confusion to boot. “It has a tremendously wide range of meanings. It could mean everything from reporting to data warehousing to BI-like technologies to data mining and even out to optimization and simula-tion,” Taylor says. “All of those different techniques are fundamentally analytic techniques. They are about simplify-ing your data so that you can get more value out of it.”

And simplification can lead to pow-erful gains in operational effectiveness, as some companies are already learn-ing. “They talk about dramatically im-proving customer retention or online conversion rates,” Taylor says. “They talk about boosting the effectiveness of their marketing campaigns and driv-ing up acquisition and driving up cam-paign response. You even hear stories of people reducing crime or driving down the overall risk of their customer portfolios.”

ADDING DECISIONS TO THE MIXDecisions have a central role in the ap-plication of analytics to business pro-cesses, Taylor says. “Decisions matter because, for many organizations, there is an ‘insight-to-action’ gap,” he says, referring to a phrase he and co-author Neil Raden coined in their book Smart (Enough) Systems: How to Deliver Com-petitive Advantage by Automating Hid-den Decisions (Prentice Hall, 2007).

Essentially, companies run analyt-ics techniques against data to come up with insights. “But there are two gaps that prevent this insight from ac-tually being applied,” Taylor says. The first gap is that managers don’t really understand what decisions they are about to make—and make differently—because of that analytic insight. For that reason, he says, they have a hard time applying the analytics insight ef-fectively. Second, once a decision is made, they can’t change the behavior of their operational systems or pro-cesses. “If you’re going to apply insight, you have to be able to take an action as a consequence.”

Taylor illustrates that imperative with a story involving a former client company whose business manage-ment hired an analytics team to build a sophisticated customer segmentation model. “The IT guys said, ‘OK, show us the model because we need to imple-ment it in the CRM system and the website,’“ Taylor says. “So the business people gave them a PowerPoint pre-sentation,” which wasn’t really a model



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that could be used in the information systems, according to the IT team.

“They had great insight into their customer base, but it didn’t present them with an opportunity to change the way they ran their business be-cause it didn’t help them impact the operational processes that affected their customers,” he says. “To do that, they needed to find a way to apply those insights at a particular point in an operational process—a decision point. They had to know and have ac-cess to a decision point in an opera-tional process where that insight would result in different behavior—different actions being taken.”

The bottom line: “Decisions are more than just about finding out new information,” Taylor says. “Decisions are a point in time where you have gathered and considered some data and you have a selection to make. You have a set of options you could con-sider or a set of choices from which you must select.”

Once you’ve made that decision, you’ve also made a commitment to ac-tion—for instance, a transaction or a customer response. “It’s that commit-ment to action that is crucial if you’re really going to drive analytics and an-alytic effectiveness into your opera-tional processes.” p

ANNE STUART is the site editor for ebizQ, a TechTarget website focusing on BPM, decision management and related topics. Contact her at [email protected].

Decisions, Decisions: Using Decision Management to

Improve Processes and Operations is an ebizQ e-publication.

Michael BolducPublisher

Ron PowellAssociate Publisher

Linda KouryDirector of Online Design

Wayne EckersonDirector of Research

Hannah SmalltreeEditorial Director

Jan StaffordExecutive Editor

Anne StuartebizQ Site Editor

Stephanie MannebizQ Assistant Site Editor

Michael NadeauDirector of Sales

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