IT's Analytical Problems
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Why is that? Have CIOs been too bogged down by the technologies themselves?
Davenport: I always say that CIOs have been pretty preoccupied with the plumbing as opposed to the water. But you have to admit it's been a few decades where the plumbing was changing at a very rapid rate--new valves and faucets coming out every year. It was a natural tendency to focus on getting the plumbing in place.
One of the reasons P&G is freer to focus on decision-related activities is because they've outsourced all their infrastructure to Hewlett-Packard. And with software as a service and utility computing, there's not much left really but thinking about how the stuff affects the business and how people make decisions.
Harris: I look at it from the business perspective. What are the benefits of outsourcing your infrastructure? It finally--at long last--frees you up to look at the important stuff, which is using the information from those systems to add value to your business.
It's easy to complain that IT has been too focused on the plumbing. It's certainly true, at times. But as Tom said, it's really hard to think about the temperature of the water people want to drink when there are holes in the plumbing spraying water all over the place and flooding the basement. It's only recently that we've reached a level of maturity in IT that [means] we can take that next step--to go back and focus on the fundamental mission of the CIO, which is to focus on how information helps the business.
Years ago, Tom and I wrote a report called "The Director's Cut." The idea was that people built systems, but it became such a huge effort to implement them. After a while, even though they knew better, they just focused on keeping the darn thing in. It was such an exhausting process. One client referred to it [as being] like a python swallowing a pig--afterwards, you just want to climb up on a rock and digest for a while before you do anything else.
I think that's true of IT as well. We have to master these basic processes and infrastructure and have a digestive period before we're ready to do anything with the data. It's like a director going back to movies they weren't completely satisfied with. It's about going back and doing it right this time.
You have a methodology, DELTA. What are the key takeaways on how CIOs and businesses can use it to succeed?
Davenport: When Jeanne and I did the first study of how companies can succeed at analytics, back in 1998 or 1999, we found that data and leadership were the two prerequisites. If you didn't have those, you couldn't get very far. So those are two of the DELTA principles.
That's Analytics 101. Analytics 202 is, we need some analysts who can really manipulate that data effectively, and we need a target to focus on, because we can't be analytical about every aspect of our business. And we need to think about an enterprise approach to unite all these little silos that have gone up.
Harris: In Competing on Analytics, we talked a lot about CEOs and how important they are to being an analytical competitor. But we recognize not everyone has a Ph.D. CEO who's going to be that passionate. Many people at many different levels in the organization can play leadership roles; it's just naturally going to affect the scope of the analytical projects you'll be able to do. In the new book we try to talk about those different kinds of leaders.
Davenport: At different levels.
But are all those different people in sync, strategically, or do they have varied priorities?
Davenport: There's still a fair amount of frustration with IT that it takes too long to make the data available. While we write about taking an enterprise approach and connecting the different silos, there's still not that much that would stop an enterprising marketing manager or supply chain manager from developing their own approach to business intelligence. So it really becomes an issue of governance, in many cases, to bring the whole organization up, and not just the particular functions.
Harris: The other frustration is IT is much more of this notion of data "push" as opposed to analytical decision-making "pull." I hear from business executives that IT wants to give them whatever data is a by-product of whatever system they've just developed, as opposed to sitting down and partnering with us to understand what information we really need and helping us go and get it. It's an age-old issue; it's been around since the dawn of computing.
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