Dan Power, Editor of DSSResources.com, conducted this email interview in late July 2006.
Q1: How did you get interested in decision support and especially decision automation?
Taylor's Response: I have always been interested in how to make developing applications more intuitive and less dependent on large amounts of code. I worked with CASE and other modeling tools, with various 4GLs and on a cool meta-model-driven development environment in PeopleSoft’s R&D group. All of these things are interesting, but fundamentally, they assume that programmers should define how systems work. This is all well and good for many things in a system, but not really for business logic – the decisions within a system. These typically require more business know-how, and that makes it hard for programmers to manage them; programmers, after all, know how to program – not how to run the business. When I saw how business rules make it possible for business people to drive their systems by controlling the decision points within their systems, I was sold.
Q2: How do you define the term decision support system? What is the overlap between your concept of enterprise decision management (EDM) and DSS?
Taylor's Response: Companies face a wide range of decisions on a daily basis. These range from strategic decisions that have broad business scope but occur less frequently, to operational decisions that deal with individual transactions and occur with the highest volume. Strategic decisions might be those such as merger and acquisition decisions, whether or not to enter a new geographic region or add a store location. Operational decisions are going to be decisions like approve/decline this application, identify that this transaction is fraudulent, or decide how much of this claim to pay. In between, you are going to have a range of what you might call tactical decisions that determine how you will manage processes and customers. These might include determining which segments of a customer base will receive which offer, or figuring out what level of risk an enterprise will be allowed in accepting applicants.
In my mind a Decision Support System, or DSS, is something designed to help people make a better decision – something to support (and hopefully improve) an individual’s decision-making capability. A DSS might support any kind of decision – strategic, tactical or operational. In reality, a DSS will most likely be focused on strategic and tactical decisions, as operational ones will need to be automated. With an automated decision, there is no person that can be supported and, hence, no decision support system.
Enterprise Decision Management, in contrast, is focused on automating and improving operational decisions. In a sense, is it is about helping systems make better decisions. It is focused on high-volume operational decisions that must or should be automated. The overlap between DSS and EDM comes in the area of tactical decisions. If I am building a system to help someone make a decision quickly and effectively in a reasonably high-volume situation, then the kind of system I build (for example, one that combines generated suggestions with supporting information) blurs the line between a DSS and an EDM system.
Q3: In general, what should managers know about business rules and decision automation? How can such tools be used to improve organization performance?
Taylor's Response: The key thing managers should know about business rules and decision automation is that the technology works. Companies all over the world and in many industries are using business rules and other decision technologies to make a difference in their business.
There are many ways you can use decision automation and business rules to improve organizational performance. These include:
Improving performance often means making better decisions. Automating decisions with an EDM approach makes it easier and quicker to change decisions and enables better analytic refinement of those decisions.
Q4: In general, what computerized decision support do you think managers need and want?
Taylor's Response: I am not sure these are necessarily the same! Often what they want is more information about what is going on, tools to let them play with it, and Excel to make it easy to show others what they have found out or concluded. What they need are tools to do their job more effectively:
What they need, in other words, is both EDM and DSS.
Q5: Why should managers implement business rules and other decision automation technologies?
Taylor's Response: Business rules deliver a unique benefit at a time when companies need to be increasingly agile in business while continuing to maintain and ensure compliance. They allow rapid and accurate operational implementation of new business strategies (i.e. new customer targets, policy changes, risk thresholds, new solution offerings) and external environmental factors (i.e. business climate, competition, interest rates, regulation). Business rules empower business users to automate and manage complex business rules with unparalleled, real-time control and agility. Predictive analytics – the other key decision automation technology – enables companies to turn their data assets into operational insight.
There are really three main reasons to focus on decision automation technologies:
Precision is a measure of the effectiveness of a decision. Different decisions will require different ways to assess precision, but whatever is used should be focused on effectiveness, not efficiency, or on targeting. You may need to consider various financial outcomes such as profit, Customer Lifetime Value, revenue or losses, as well as the accuracy of predictions, comprehensiveness of factors involved, and the level of granularity achieved. Improving precision is a key reason for adopting decision automation technologies – especially those related to predictive analytics.
Consistency measures how well integrated and coordinated your decisions are across your enterprise. Do you make the same decision, the same way, unless you mean not to? You can measure consistency over time: is today’s price the same as yesterday’s, across channels? Is the offer on the website the same as the offer made by the call center, and within and across product lines? Do I offer the same interest rate for different unsecured credit products? Highly consistent decisions need not be the same for all customers, all channels or over time, but the variations should be deliberate and designed, not incidental. Focusing on decisions as points of automation is vital.
Agility is a measure of how quickly, cheaply, and easily you can change the way you take a decision within your systems and organizational infrastructure. For example, if you want to introduce a new cross-sell strategy or a new pricing structure, how easy is it to change the systems specifications that support those decision strategies? How quickly would someone interacting with your organization notice that you had changed the way you wanted to make a decision? To measure agility, consider the total time and cost involved in moving from the point where you have the data that means you should change your decision process to the point where you have actually effected such a change. The higher this time and cost, the worse your agility. The use of business rules technology is largely driven by the need for agility, especially agility with consistency.
It is also the case that speed–how quickly you can execute a decision – can drive the adoption of decision automation, as can cost reduction. By and large, automated decisions are cheaper and faster. If the volume of decisions is such that they are too costly to make by hand, or if the response time required is too hard to meet with manual decisions, then automation will add real value.
Q6: How can automating and managing decisions make enterprise applications more effective?
Taylor's Response: To quote the Butler Group, "Enterprise Applications tend to be pretty dumb. They collect data, store it and produce reports on it.” So, if your enterprise application(s) is/are dumb, what can you do about it?
There's more, but you get the gist. Automating and managing decisions can make your Enterprise Applications much less dumb.
Q7: What is the potential for decision services, business rules and predictive analytics? Also, please explain these concepts.
Taylor's Response: Decision services, built with business rules and predictive analytics, have the potential to bring the power of business intelligence to bear on operational processes. They can greatly reduce the maintenance tail and, hence, the Total Cost of Ownership (TCO) of complex information systems by making the business logic easy to modify. They can empower customers to self-serve and enhance the effectiveness of customer-facing staff by dramatically reducing the need to refer decisions to managers. They can make managers more effective by letting them focus on the overall business rather than the mechanics of day-to-day decisions.
Decision services are services within your Service Oriented Architecture (SOA) that automate and manage highly targeted operational decisions. A Decision Service isolates the logic behind operational business decisions, separating it from procedural application code. Decision Services also eliminate the time, cost, and technical risk of trying to simultaneously reprogram multiple individual systems to keep up with changing business requirements and make it much easier to improve a decision using analytics. By isolating the changes and improvements to decision-making inside a single component, you can increase your return on investment by leveraging the best decision you know how to make everywhere.
Business rules management systems enable the design, deployment, and maintenance of business rules and policies. These systems—also known as business rule engines and decision engines—put control into the hands of business users, allowing them to build and revise rules without IT support. Typically, a business rules management system is invoked as part of the total processing involved in an interaction with a customer. The system accesses and processes relevant transactional and historical data, uses predictive models and other analytics to segment customer populations for targeted action, executes business rules appropriate for the specifics of the customer and transaction at hand, and returns decisions to the production system or business staff.
Using these systems gives business managers increased control and visibility over the factors used in each business decision. A business rule is defined, reviewed, modified, and reused as a corporate asset. The ability to manage these control points independent of the computer programming code that runs the automated applications allows for faster and more accurate review of business operations and implementation of changes as quickly and as often as necessary. Business rules management systems enable businesses to make highly consistent, strategy-driven decisions, and to change them with greater agility.
Predictive AnalyticsPredictive analytics is a proven technology that’s been used successfully for decades. It encompasses a variety of mathematical techniques that derive insight from data with one clear-cut goal: find the best action for a given situation.
Predictive analytics simplifies data to amplify its value, finding patterns that can guide decisions. When considering hundreds – or even thousands – of factors, and a universe of thousands or millions of customers, people just can't "connect the dots" to make the ideal decision. Predictive analytics connects the dots scientifically, guiding each decision to greater success. Simply put, predictive analytics is the science that makes decisions smarter.
Predictive analytics applies diverse disciplines such as probability and statistics, machine learning, artificial intelligence, and computer science to business problems.
Q8: How can decision automation and decision support systems improve agility in organizations? You've noted in your blog that Gartner defines agility as "the ability of an organization to sense environmental change and to respond efficiently and effectively to that change".
Taylor's Response: Gartner’s perspective shows exactly why both decision automation and decision support systems are required. In order to “sense” environmental change you need decision support systems. Ideally, you would automate some of the sensing, with Complex Event Processing or Business Activity Monitoring systems. But even then, you are likely to have a set of situations that will require a person to do some analysis. That’s where the DSS comes in – helping them understand what change has happened.
In order to respond effectively, you will often need decision automation, as decisions are often the key element of change. For instance, especially in your core business, your process is unlikely to change in response to anything but the most tectonic shifts in your market. The more typical environmental change is not going to change your business, but it is going to make you want to refine pricing, re-target offers, segment customers slightly differently, etc. These decisions might change constantly in response to variations in response rates, competitors, market conditions, the weather, and so on. Decision automation and management are key to being able to change these decisions quickly:
Agility will require DSS and EDM – the one to sense the need for change, the other to make the change effective across your applications in a timely manner.
Q9: What do you see as major trends in computerized decision support? Where are we headed?
Taylor's Response:I think we will see more and more automation of decisions and more sophisticated support of decision-making. I think we will move away from thinking that decision support means reports or eye-candy, and towards thinking about the decisions being taken and what information technology can do to improve them. In particular:
About James Taylor
James Taylor is vice president of product marketing for Fair Isaac’s Enterprise Decision Management Technologies, where he is responsible for working with clients to identify and bring to market advanced decision management solutions that will better solve their business needs. Taylor is widely considered as one of the leading experts and visionaries in enterprise decision management and he authors a blog on related subjects at edmblog.com.
Power, D., "James Taylor Interview: Automating Decision Making", DSSResources.COM, 10/6/2006.