The Heart of the “Competing on Analytics” Matter

I confess to a lack of ambition. When Tom Davenport’s article on "Competing on Analytics" came out in the Harvard Business Review in January, Zach and I critiqued Tom’s list of 10 things that are "what it takes to be an analytics competitor" because it offered a good example of condensed misperceptions about what analytics can and should do.

But we didn’t address the heart of the matter; the biggest way analytics will change over the next decade and the reason we’re in business.

Niel Raden does. He offers a critique of "Competing on Analytics" that is focused and deep. I invite you to read it as well as his other publications. This is good thinking by a very experienced analytics consultant.

There are two schools of thought when it comes to the value of BI in general. One is that it is best used by “quantitative" types and other analytical business people, who can spot trends and analyze patterns to assist in the big decisions and set and direct strategy. The other position is that BI is at its best when helping a broad range of people and processes at an operational level, marginally improving performance, repeatedly and often. The former is the commonly held view of management consultants and, previously, BI practitioners a decade ago. The latter position gained currency in the last few years and is now widely seen as borne out in practice. Using BI to form a new strategy for a global financial services firm makes for good marketing collateral, but when it comes to ROI, lots of small improvements are the way to go.

Why is centralizing analytics bad and decentralizing analytics good? Why shouldn’t your organization have a single centralized "brain" that directs the far-flung body to intelligent, purposeful action?

Centralized control of data and analytical expertise may not seem very controversial, but what Davenport is implying is not only centralized control, but also centralized design. This is another naïve assumption, because many organizations are not only decentralized—they’re dysfunctional. Separate units within organizations often need autonomy because they are just so different from the rest of the organization. In addition, as an organization becomes more “agile," which is a definite trend, decision-making, even for the big decisions, will become more decentralized. Imagine how difficult it will be to buy or sell pieces of a company if the “brain," the centralized analytical capability, stays with the parent and there is no local expertise?

In our experience, there are hundreds of decisions that need to be made each day, even in a medium-sized organization. In most cases, those decisions are being made in a vacuum—on faith, trust, gut-feel, and partial information. Statistical significance tests aren’t needed to improve these decisions, just basic, easy-to-use visibility into business processes.

Statistical analytics can be helpful, but perspective and experience are even more useful to find insights in data. Democratizing data in your organization, making it easier to put more eyes, more experience, more brains against your data is the challenge of the next ten years in analytics. The Internet abounds with examples of what people can do when they can get their hands on data.

Incidentally, if you do want to hear Tom Davenport’s side of the argument, you can catch a webcast on Thursday, March 16th at 1:00pm EST. Here’s a link.