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From Operational Business Intelligence to Competing on Decisions

Originally published July 29, 2008

There is a great deal of discussion about operational business intelligence (BI) these days. Operational BI, with its focus on day-to-day operations, has some key differences from what you might call “traditional” or perhaps “tactical” BI. For one thing, operational BI requires low-latency or real-time data to be integrated with historical data. For another, it typically requires integration with operational systems or business processes. This makes it quite a challenge for those accustomed to traditional BI implementations. To make operational BI work, you must get into the details of operational processes and systems, something not usually required for business intelligence. Users are also different, with lower-level managers and analysts having a larger role. Finally, automation (both of generating reports and dashboards and of acting on them) is more widespread.

Where operational BI is not different is in its general mind-set – that the purpose of business intelligence is to turn information into actionable insight and deliver it to people so that they can act more appropriately. Operational BI might be part and parcel of operational processes and systems, but the focus is still on changing how people make decisions in that operational context. Adopting operational BI will help bring the data you have collected, cleaned, aggregated and integrated to more people. It will also change your focus from overall results and summaries to transactions. But there is more to do.

Competing on Decisions is the name of my BeyeNETWORK.com channel for a reason. The behavior of your customers, partners, suppliers and employees is central to your success. They react to the actions you take, and those actions are determined by choices made by you, your staff and your systems. Making these choices requires decisions, and so decisions make the difference. In an always-on, multi-channel world, these decisions must increasingly be made by information systems and not by people. Even when people are available, the growth of outsourcing and complex distribution and delivery networks means that we need more control over how those people make decisions. Recognizing this and using this recognition to compete more effectively is what we mean by competing on decisions.

Competing on decisions requires a number of changes to the way you think about business intelligence and about data more generally. It means going beyond operational BI and into what is called enterprise decision management or EDM. Enterprise decision management is an approach for automating and improving high-volume operational decisions. Focusing on operational decisions, it develops decision services using business rules to automate those decisions, adds analytic insight to these services using predictive analytics and allows for the ongoing improvements of decision-making through adaptive control and optimization. The five areas of change are:

  1. A focus on decisions.

    While operational BI will tend to focus you more closely on the decisions within processes and transactions, competing on decisions requires that you take this to the next level. Finding the decisions that impact your customers, determining the outcome of your processes and controlling the results of your transactions are key focus areas. These little decisions (what price to offer this customer, what cross-sell to use on this call, is this customer eligible for this product) add up; and if you are going to compete on decisions, you need to focus on them.

  2. Organizational integration.

    Like operational BI, EDM requires that organizations long accustomed to working separately must now cooperate more closely. The analytic, IT and business organizations must come together more than ever before. The analytic team must look at the decisions to see what data exists or can be found that would help make better decisions. The IT team must understand how decision making is going to be integrated into high-volume, transactional systems. The various business teams involved (marketing, customer service, legal) must be able to participate in defining how decisions should be made.

  3. Analytic technology change.

    Moving to operational BI from traditional BI does not require much of a change in the kinds of delivery technology being used. EDM, however, does. No longer can analytics be delivered with reports and graphs. If the systems and processes are to use the data to make decisions without human intervention, then analytic insight must be delivered as executable models. Instead of presenting graphs with trend lines, a predictive model is needed. Instead of mining data to produce a visualization of customer segments, data is mined to produce the rules that define the valid segments. Many of the same analytic techniques are used, but new skills and new technology will be required.

  4. Additional technology is required.

    While many of the capabilities for developing analytic models are included in tools used for operational BI, one critical new technology is required for EDM. The use of declarative, business-friendly technology to define, manage and reuse the business rules that drive a decision is key. In operational BI, the rules are applied by operational personnel – based on policy manuals, procedures, their own judgment. In EDM these policies, procedures and judgments must be encoded so they can be executed. This does not mean code, though, because the business logic that drives your decisions is too critical to be hidden away from the business users who understand it. Hence, business rules.

  5. Adaptive control becomes necessary.

    The last area of change is in the adoption of adaptive control – sometimes called A/B testing or Champion/Challenger. In adaptive control, most transactions are decided using the champion approach – the current, default or best-so-far – while a subset of all transactions are decided using one of several challengers. These challengers use different rules and models to see if there are, perhaps, more effective ways to model the decision and so get better results. When dealing with operational decisions, this is really the only way to see how different approaches might work. Adaptive control also constantly tests the way you make decisions to see if the world has changed in a way that favors a different approach. Constant vigilance – constant champion/challenger testing – is the price of good decisions.

To compete on decisions, then, we need to do more than adopt operational BI. We must build on this new operational focus to become even more decision-centric, more focused on the details of these small, high-volume decisions. Adopting EDM is what it takes.

In my next article, I will discuss how to go about moving to and beyond operational BI.

  • James TaylorJames Taylor

    James is the CEO of Decision Management Solutions and works with clients to automate and improve the decisions underpinning their business. James is the leading expert in decision management and a passionate advocate of decisioning technologies business rules, predictive analytics and data mining. James helps companies develop smarter and more agile processes and systems and has more than 20 years of experience developing software and solutions for clients. He has led decision management efforts for leading companies in insurance, banking, health management and telecommunications. James is a regular keynote speaker and trainer and he wrote Smart (Enough) Systems (Prentice Hall, 2007) with Neil Raden. James is a faculty member of the International Institute for Analytics.

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