How to Measure Analytical Success

By Brian P. Watson  |  Posted 02-10-2010 Print Email

What advice would you offer to CIOs for developing and executing a comprehensive information-driven strategy?

Davenport: There's a positive message and negative message. Positively, you can think about what particular decisions you want to influence. It's rare to have clarity on what the five most strategic and five most tactical decisions the organization needs to make are. You can start to apply the data and technology to where it's really valuable to the organization.

We talk a fair amount of identifying some sources of data that are a little proprietary. It's not the data hygiene-related issues, but also something that's really distinctive.

The negative message: Stop doing stuff that doesn't really affect how decisions are made. If you can't draw a solid line between what the information and technology are, and what decisions will be made from them to benefit the business, you probably shouldn't be building that system in the first place.

Harris: One of the reasons we put in the "targeting" section of the DELTA model was because we found that people were targeting the wrong business problems. They were targeting what they need to do versus what would really make a difference to the business.

And how can they measure the success of the changes they put in place?

Davenport: The good thing about analytics is that the metrics it often leads to are not IT metrics, but business metrics. Take pricing. We talk a little bit about it in the book, and then I wrote a Harvard Business Review article on some work that The Stanley Works had done on pricing. They were very much focused on how they make better pricing decisions. The way you measure their success is in six points of additional gross margin. The way you measure effectiveness of marketing analytics is the average lift you get from a promotion.

Those are very important business metrics, and they're not the usual things that IT people wrestle with, like spending as a percentage of revenue. They're real impact metrics.

Harris: We've been trying to emphasize the concept of analytics not just to make better decisions, but to improve business performance. Too often there's a disconnect between making a decision and taking action, or making a decision and getting any improvement in the business. One of the things we've found in talking to companies around the world is the importance of embedding analytics in the decision-making process, all the way to execution and outcome.

Why do CIOs still struggle to execute on their strategies?

Harris: We've talked to several companies where the analysts were very proud of the analysis they did and the conclusions that could be reached from the analysis. But they had no interest in whether anyone actually read the memo or executed on their conclusions. There are some dysfunctional cultures out there where people are insufficiently engaged in their work and aren't focused on seeing it through to the end.

In a way we see that in IT organizations. Years ago, people created self-help functions. They were more interested in throwing data over the wall and not having to worry about if it met the business needs or not. If we're ever going to move past that, IT needs to have a better understanding of what drives business performance.

If you look at a lot of the recommendations about what skills and capabilities analytical talent needs, you can argue that IT people need those same kinds of expertise. They need to be engaged and able to form a trusted relationship with the people using their data to understand the business objective they're trying to accomplish. They need to be engaged in what the real business problem is, as opposed to, "How quickly can I send this person a report and get them off my back?"

Davenport: Analysts were historically back-office people; you give them the data, and they come back in a month or two with a model. We found that people who are doing this successfully now are much more engaged in the whole process--helping to frame the decision in the first place, helping to deal with stakeholder analysis, and so on. They're very closely engaged with decision makers throughout.

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