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Tom Davenport

President's Chair, Information Technology and Management at Babson College

Q: You’ve been writing that the connection between information and decision-making is not as certain as people assume.

A: In loosely-coupled environments that make up the bulk of our BI and analytic decision-making we’ve created a sort of decision playground. We go and get data out of the data warehouse, we use analytical tools, but we don’t look closely at how people use it to make decisions. As a result, they often don’t make decisions effectively.

Q: You point out that too many or too few people might be looking at data, that good information is unused or unsuitable information gets used and there’s no methodology.

A: I don’t think it boils down to one methodology, there will be a lot of tools and frameworks and approaches to become more effective. But my bet is that more and more organizations will become serious about this because it’s kind of the next frontier. We’ve made some really bad decisions over the past several years. We don’t even know the extent of the problem because most organizations don’t identify, assign responsibility or track the results of key decisions. We’ve invested all this money and effort trying to produce information for better decision-making but we rarely link the two.

Q: You studied dozens of companies and found some, like P&G and Citi that have created decision management groups.

A: I found four or five. At P&G it’s mostly a name change but it was intended to be symbolic of a real change. At other places it’s more than that; it’s people who are analytically-oriented saying, ‘it doesn’t really help us that much if we just come up with an answer and nobody uses it in a decision so let’s broaden the idea and call it decision management.’

Q: Could this be an “uh-oh” moment that creates a roadblock where decision-making has to work its way through a group?

A: Yes, but I hope that’s not the usual case. I found, for example at Motorola, there were some people who were thinking that decision-making should be an IEEE officially defined process and I think that would be a big mistake. But other people at organizations I am talking about are coaches and advisers who don’t actually approve anything. The degree to which they are effective results from having a close relationship with the decision-maker and demonstrating better results. This idea of jumping through decision hoops would generally be a bad one.

Q: How does all this relate to data and information governance as we discuss it?

A: I think governance is farther down in the stack. Governance is usually asking whether the data has integrity and if it is being defined the right way. Those are important attributes but don’t ensure that information will be used to make effective decisions.

Q: What are downsides of the loosely-coupled decision model?

A: It’s the most common situation and easy to see why, because it’s quite effective for the information providers who can say, "Here’s everything you need, your data warehouse, your quality data, your tools, be fruitful and multiply," and then those IT providers tend to back away. But how many times have we heard about drilldown and ad hoc query and reporting only to find it never really happens as much as we’d like to believe? There just aren’t enough people who understand the structure of the data and the tools and, the more analytically complex the tools are, the less likely you’ll have people doing the right thing with them.

Q: And at the other extreme you have very automated decision models. What are the pluses and minuses there when it comes to decision-making?

A: With those systems you are often very near the customer and making decisions such as, should I give this customer a loan, though often there is an intermediary between the system and the customer. The nice thing about automated services is that you know the decision is being used because it’s built into the rules base or the algorithm and you know it’s going to be made quickly because computers are doing the work. On the downside, if you have the wrong decision logic or algorithm, you can make a lot of bad decisions really quickly. Just creating automated systems takes time and money and requires a pretty structured decision environment just to be able to pull it off. But it’s clear those systems have and will continue to expand, they’re all over the place.

Q: Are businesses automating the right things or the things they can automate first?

A: This gets back to the need for a better systematic process for saying what we should do with decisions, which really implies some kind of inventory of key decisions that really matter to your organization, what we do with them, how we make them better and in what order we should we go. It is not just about what somebody decides ought to be automated or improved; it’s about what really matters to the success of the business. Even organizations that have created decision management groups haven’t done much to prioritize the decisions that really matter.