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First Steps To and Beyond Operational Business Intelligence

Originally published September 30, 2008

First, let me recap my July article. Operational business intelligence (BI) has a focus on day-to-day operations and so requires low-latency or real-time data to be integrated with historical data. It also requires BI systems that are integrated with operational business processes. However, while operational BI might be part and parcel of operational processes and systems, the focus is still on changing how people make decisions in an operational context. To compete on decisions, however, you must recognize that your customers react to the choices made by you, your staff and your systems, and that you must manage all the decisions you (or your systems) make – even the very small ones. This is the basis for enterprise decision management or EDM. Five main areas of difference exist between operational BI and EDM – a focus on decisions (especially operational ones), organizational integration, analytic technology change, adoption of additional technology and adaptive control.

In this article, I want to outline some steps organizations can take as they move from “traditional” BI towards operational BI and enterprise decision management. Some of these steps would be a good idea if operational BI was your goal. But hopefully you are more ambitious than that and want to really begin to compete on decisions.

Start Small

Despite the dreaded “E” word (enterprise), EDM is ideally suited for starting small and growing over time. It is enterprise decision management because decisions must be managed as an enterprise asset. Like most new things, starting small is a good idea when moving to competing on decisions. You need to pick an operational problem (some limitation in a day-to-day process), but it should not be something super-important. You also want it to be a well understood process, perhaps one already being managed using a business process management system, and one where there are one or two clear decisions to make.

Begin With the Decision in Mind

This brings us to the second point – begin with the decision in mind. EDM is completely decision-centric, so it is vital that you identify and understand the decisions in the process on which you are working. How are the decisions made and who makes them? Who decides how they should be made and how they are regulated? How long do they take now and what is the business value of making them faster? Without a good understanding of the decisions that matter to your target operational process, you won’t get very far.

Understand the Difference between Decision Support and Decision Management

Decision support means delivering the information and insight someone needs to make a better decision – supporting a person when that person is the right person to make the decision. Decision management means automating the decision and giving control of how the decision is made to business owners. If it makes sense to your organization that the current decision makers are the right ones, then you are going to be looking at decision support – something like most people’s definition of operational BI. If, on the other hand, the decision is being made by someone who really should not make it so much as pass it on, or if the decision is highly constrained and the person making it is not applying any real judgment or expertise, then you are looking at automating it and, therefore, at decision management.

Bring People Together

Decision management and operational BI require three groups to work closely together – in some organizations four. You need:

  • Businesspeople who understand the decision being made, the regulations concerned, measures and objectives.

  • IT people who understand the operational systems through which the information flows and into which decision support or management must be integrated.

  • Information management people who know what’s in the data warehouse, how it is aggregated, which systems feed which data to whom, etc.

  • Analytic people who know how to mine the available data and derive new predictive insight from it. These may be the same folks who are managing the information, but in many organizations, they are their own group and not necessarily accustomed to working with information management or IT.

Assess Aggregation

One of the critical issues when moving to operational decision making, both in decision support and in decision management, is that of data aggregation. If your data warehouse or data mart, or your ETL processes, focus on aggregated data, you may well have to reassess them. For instance, if you store daily usage totals for reporting, they won’t be much help when you start trying to improve an intra-day operational process. Aggregation is, by and large, the enemy of both operational BI and of EDM.

Consider Performance and Workload

Operational systems, whether embedding decisions with EDM or adding reporting and dashboards with operational BI, will require you to reassess acceptable performance. Real-time, or near real-time, is likely to become a requirement. Rapid responses to events and low latency in high speed processes will be the order of the day. In addition, the workload for your data infrastructure will become much more mixed and more demanding. This will affect your data warehouse, ETL infrastructure, etc.

Plan for Adaptive Control

The consequences of decisions often take time to play out. To find out what works and what does not, you must constantly try new approaches, test them and learn what works. Creating an environment in which you can constantly test and learn, what we call adaptive control or champion/challenger, is going to be critical if you are to focus on improving operational decision making. You must understand how you can try new challenger strategies on a small subset of your transactions and compare their results with your champion strategy. This means building some decision-centric performance management capability and building suitable infrastructure for splitting off some transactions and processing them differently. It also means managing a change in mind-set away from just one “right” way to many possible ways so that you keep learning.

Evaluate Business Rules Technology

Finally, you need to evaluate business rules and business rules technology, especially business rules management systems. As you move from a mind-set of presenting information to people and hoping they make the right decision to one in which all or part of the decision-making is handled by the system, you need a way to represent the regulations, policies and best practices that should be applied to these decisions. Business rules in a business rules management system are the best way to approach this today. While this is a new technology for BI people, it is important to understand it if you are to move beyond passive operational BI and into more active decision management.

Hopefully you can see that this list overlaps with the kind of recommendations you are hearing for moving to operational BI. Even if operational BI is the next step on your journey, I hope you will aim at EDM so that moving to operational BI is the next step, not the last one.

  • 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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Posted April 7, 2009 by barbara von Halle bvonhalle@kpiusa.com

James' article is outstanding because it provides definitions that distinguish EDM from BI and decision support.  But, it also provides a practical approach to getting started.

A critical revelation in this article is that decision support is about providing data to people for making decisions whereby decision management is about automating those decisions so that people don't need to have analytical skills for making the decisions (not to mention the inconsistency in the results that would occur).

 

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