The Need for Smart Enough Systems (Part 8) ~ Contributing Value to your ROI Calculation: Revenue Growth

James   Taylor
James Taylor CEO, Decision Management Solutions Read Author Bio || Read All Articles by James Taylor
Neil   Raden
Neil Raden President and Founder, Hired Brains Read Author Bio || Read All Articles by Neil Raden

Last time, we covered the first of the three layers (cost reduction, revenue growth, and strategic control) that can contribute value to your ROI calculation.  In this instalment we explain the second of the three, revenue growth.

When your systems aren't smart enough to cope with current demands, they waste your money and decrease your revenue.  You're throwing away revenue if you target customers poorly, respond too slowly, and fail to deliver a compelling, cross-channel customer experience.  Enterprise decision management can help increase your revenue by addressing these weaknesses.

Better Targeting, More Sales

There's much discussion these days of microsegmentation or 'markets of 1'.  Many organizations find themselves dealing with 'the long tail' (see the sidebar "The Growth of Choice") of finely differentiated, small customer segments.  You need ways to identify which customer or prospect must be in which micro segment, and you need to target your marketing and customer service to those segments precisely. 

You want customer interactions to be based on who they are, how valuable they are to you, what you know about them, and so on.  Improved targeting can result in higher rates of cross-sell and up-sell offer acceptance.  For example, one company used an EDM approach to target existing customers who purchased only from a single product category in an effort to get them to purchase products from additional product categories.  This precise targeting involved more fine-tuned analysis of customers and personalized offer letters based on this microsegment.  This EDM approach generated a 17 percent response rate compared to the less than 1 percent in previous marketing approaches -- a 2,000 percent increase.

[Sidebar 1. The Growth of Choice ]

No Comparison Shopping, More Sales

Besides better targeting, you can also gain revenue at the point of sale simply by pushing decisions to the point of contact and reducing the decision time to zero.  Most people aren't ruthless comparison shoppers; they like instant gratification and are generally in a hurry.  Pushing decisions to the point of contact and reducing the decision time to an acceptable wait can mean closing the transaction at once.  Unlike manual decision making, the automated decision happens fast enough that customers don't need to wait or return later.  This practice avoids the risk that customers will find someone else to offer them what they want while they wait for your response.  For instance, an insurer using an EDM approach to automating underwriting decisions found that more prospects accepted a policy at a given price when it was offered immediately, while they were still on the phone, than if the same price was offered later by e-mail.

More Marketing Opportunities, More Sales

As you learned in "Hidden Decisions" earlier in this chapter, many opportunities to boost revenue through cross-sell and up-sell offers are missed because no one is there to make the offers.  How can you make cross-sell offers for customers who use only your ATMs, the automated check-in terminal, or the Web-based shipping kiosk?  Pushing decisions to the point of contact enables these systems to make cross-sell or up-sell offers.  Taking advantage of every interaction with a customer or prospect, regardless of channel or device, can increase revenue in new ways.

Better Customer Experience, More Sales

Improving the customer experience is a hot topic in many businesses today.  Often it's discussed only in terms of hiring and training staff to act a certain way, but this training isn't enough.  Your customers think any action you take toward them is deliberate and reflects the value you place on them.  Sadly, in many companies, the way the Web site or call center responds and the way marketing generates offer letters are all disconnected from each other.  In addition, customers often get wildly different responses, depending on the channel they use.  They get a good response in a branch and a poor response by e-mail, for instance -- and the responses have nothing to do with how good a customer they are.

[Sidebar 2. $30 Billion Global Retailer:  Drive Basket Size and Cross-Category Sales]

In fact, all your customer interactions should be based on who they are, how valuable they are to you, and what you know about them.  In many ways, customer experience is the sum of customers' perceptions of interactions with your brand.  Interactions are what affect the experience, so you need to achieve better interactions with your customers.  A recent survey[1] identified four steps you can take to improve customers' perception of critical interactions:

  • Offer high-quality goods and services.  Obviously, this issue is critical for a good customer experience.  If you have information-based goods and services, using enterprise decision management to manage critical decisions about configuring and delivering those goods and services can help improve their quality.  Physical goods can be improved by using enterprise decision management to manage quality control and diagnostic checks so that you detect problems more quickly.  Using enterprise decision management allows all your production facilities, no matter how geographically dispersed, to benefit from the expertise of your best staff, thanks to the ability to embed expertise in decision services that check and control production.

  • Give personal attention.  Not only does enterprise decision management allow automated decisions to be better targeted to smaller segments, some rules in a decision can be owned by customers, which allows them to personalize their interactions.  Systems can also use enterprise decision management to improve interactions with customers by using the customer information you have gathered to change how a call is routed or handled, what offer or price customers get, and so on.

  • Reward loyalty.  Enterprise decision management is perfect for making decisions about loyalty programs.  Using dynamic business rules to manage awards makes your loyalty program more flexible and responsive yet still consistent across channels and employees.  Using analytics to target special bonuses to those who will be positively affected can improve the effectiveness of loyalty programs, too.  For example, you can use analytics to predict which customers will respond to a "travel once more to make Gold" offer.

  • Employ well-trained, friendly, helpful, caring people.  Using an EDM approach to eliminate the need for employees to refer decisions for approval lets them act more readily on behalf of customers and, to some extent, seem more caring as a result.  Nice employees don't matter much if they can't actually do what needs to be done for customers.  Automating data analysis can also help workers who interact with customers focus on the interaction, not on wading through reports on their screen, trying to figure out what a customer might need.

A major challenge in using information effectively in the context of smaller customer segments, more distribution channels, more store formats, and more products is capitalizing on the insight you can gain from all this extra data.  A study published in McKinsey Quarterly[2] introduced the concept of 'cell-level insight', which is insight into the behavior of very specific segments or cells.  Gaining this insight is a complicated problem, but it's just the beginning.  After you have 'cell-level insight', you must turn it into actions in high-volume operational systems -- which is where an EDM approach comes in.

Customer service includes customer self-service, which is increasingly important in today's 24x7 world.  Complex decisions are more common in self-service.  No longer is it enough for a self-service portal to deliver a PDF of the instruction manual; now customers want some kind of guided interaction to help them find the problem.  You need to automate these decisions so that your customers can serve themselves, even when the decision is a complex one.  Using enterprise decision management means automating and managing decisions so that they can be used to provide great customer service or great customer self-service.

Next time, we will explain strategic control, the third of the three layers that can contribute value to your ROI calculation.


[1] -- survey conducted May 2006.  return to article

[2] John Forsythe, Nicolo Galante, and Todd Guild.  "Capitalizing on Customer Insights," McKinsey Quarterly, No.  3 (2006).  return to article

Acknowledgement: This material is from the book, Smart (Enough) Systems, by James Taylor and Neil Raden, published by Prentice Hall (June 2007).  ISBN:  0132347962.

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Standard citation for this article:

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James Taylor and Neil Raden , "The Need for Smart Enough Systems (Part 8) ~ Contributing Value to your ROI Calculation: Revenue Growth" Business Rules Journal Vol. 9, No. 2, (Feb. 2008)

About our Contributor(s):

James   Taylor
James Taylor CEO, Decision Management Solutions

James Taylor is CEO of Decision Management Solutions and one of the leading experts in decision management.

James works with clients to develop effective technology solutions to improve business performance. James was previously a Vice President at Fair Isaac Corporation where he developed and refined the concept of enterprise decision management or EDM. The best known proponent of the approach, James is a passionate advocate of decision management. James has 20 years experience in all aspects of the design, development, marketing and use of advanced technology including CASE tools, project planning and methodology tools as well as platform development in PeopleSoft's R&D team and consulting with Ernst and Young. He develops approaches, tools and platforms that others can use to build more effective information systems. He is an experienced speaker and author, with his columns and articles appearing regularly in industry magazines.

Read All Articles by James Taylor
Neil   Raden
Neil Raden President and Founder, Hired Brains

Neil is the President and founder of Hired Brains, a research and consulting firm and a hands-on practitioner in many areas related to Business Intelligence and Advanced Analytics. He is on the advisory boards of The Data Warehousing Institute and Sandia National Laboratory. The recurrent theme in his work is the transformative effect of rationally devised information systems for people.

Neil is an author and source for journals such as Information Week, Intelligent Enterprise, Business Intelligence Review, DM Review, Computerworld, InfoWorld, eWeek, Business Week, and Forbes, and a contributing author to Planning and Designing the Data Warehouse (Prentice Hall, 1996). He is the author of dozens of sponsored white papers for vendors and other organizations (available at

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