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James Taylor's Decision Management

James Taylor

Some thoughts on rules, decisions, agility and more

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I got an interesting comment on my recent post about the top 4 concerns of CIOs.

Joanne makes a number of points in her comment that I thought should be addressed:

a business rules engine is not nearly enough. What is needed instead is a means to model manage and measure the impact of a decision on desired business outcomes, and to do so not in a silo of a process but in the context of a business activities, a variety of changing market conditions and business scenarios.

Absolutely. This is why I talk about decisions, not just about rules, and why I think it is critical to link decision management and performance management (something I will be discussing at the Business Rules Forum during the alignment symposium).

The notion of making decisions based on either historical data or using predictive analytics or rules engines is contrary to becoming agile.

Nope, disagree completely. The reality of a modern organization is that it makes thousands, millions of decisions that simply cannot be made by a person - there is not the time or money to do so. These must be automated and a rules engine is the only way to ensure some kind of agility. Yes business leaders need to learn and improve decision making, but a rules-based decision management approach gives them the power to actually change the decision making in their systems and so does deliver agility.

Agile implies proactive so these days decision making is not about playing "what if", it's about playing "then what". Enabling a decision maker to measure the value of a decision criterion against other criteria and make the appropriate trade-offs in advance of a market condition creates the still elusive agility companies seek.

Completely agree. This is another benefit of formally modeling and understanding operational decisions. Only then can simulations, scenarios be developed that use the actual transactional behavior of the company and its systems rather than some roll-up or aggregation. Seeking tradeoffs using traditional tools that roll up transactions and make assumptions about how decisions will affect the group is not enough - you need to be able to apply tradeoffs and new approaches customer by customer, transaction by transaction to truly understand their implications.

Automating a decision using a rules engine does not allow an organization to make more informed decisions because the rules are not conditional upon non-included variables - and even if they are, then the exception becomes the norm and norm the exception.

Using a rule engine does not enable more informed decisions, true. But it allows an organization that figures out the best way to make decisions to ensure that this is, in fact, how decisions are made. Too many companies think they make decisions one way but have no way to check/ensure this is what happens at the front line or in their systems. Rules engines can be used to implement bad decision making, of course, but they allow you to see how bad it is, change it rapidly and engage those who understand the decision directly so they are way better than the alternative.

too often its the squeaky wheel that gets the oil. In many cases decisions are based on satisfying one stakeholder group when in fact the agenda touted by that group may be a quick win with long term ramifications that do more to hinder than to help drive the revenue growth or improved effectiveness the organization desires.

Too true. But how will you do this if you don't have some explicit record of how decisions are being made (and if you are not automating a decision with a rules engine then you don't have such a record: people never record their decision making process clearly and traditional IT systems are completely opaque). By automating and managing the decision you create the record of decision making and its implication that would allow you to address this.

Great comment Joanne - appreciate it.

1 Comment

This is a very interesting conversation and quite timely I might add. I certainly agree with you James that "it is critical to link decision management and performance management." As a part of my consulting business, I have added risk management as a third link. I offer this tidbit not as any profound insight but rather to expand upon the point made above regarding how decisions are made and how organizations determine if they are the right ones. Risk is an integral part to this process and this is why risk, performance, and decision management should be fully integrated in our models and business rules. Likewise, the business rules should be based on adaptive controls and predictive analytics which allow us to test and correct "on the fly." This is true agility that we see in some of the event analytical engines on the market today. In Douglas Hubbard's recent book, The Failure of Risk Management, he emphasizes the importance of testing to make sure we know if our models work. James, I think you and Douglas are saying the same thing. In your book, Smart (Enough) Systems, you give the example of National Bank: Controlling Risk While Doubling Customer Base. In this case, the business rules and predictive analytics produced key risk/performance indicators which enabled them to make the right decisions at the right time. As your Figure 2.13 indicates, “the accumulated reduction in provision for loss [was a direct result of] a risk management EDM solution.� That’s what I’m talking about.


James Taylor blogs about decision-management technologies such as predictive analytics and business rules, discussing how they deliver agility, improve business processes and bring intelligent automation to SOA.

James Taylor

James Taylor blogs on decision management for ebizQ, and is an independent consultant on decision management, predictive analytics, business rules, and related topics.

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