According to Gartner both CIOs and CFOs list BI or Analytics as their top priority. Despite this focus, organizations have had a difficult time deploying BI successfully. According to the BI Scorecard, BI adoption rates have essentially hovered around the 25% mark since they started surveying companies back in 2005. (That was the year that the first YouTube video was uploaded. And, the iPhone wasn’t even introduced until 2007!)
This discussion is usually phrased as driving a more “analytical culture”: one where there is a general desire and willingness to make decisions based off of factual quantifiable data versus intuition. Usually, I would say that culture is one of the hardest things to change. But this time the likes of Google and Apple have done much of the heavy lifting for us. Rather than rely on gut feel, many of us have become information junkies over this same time period. So why is BI adoption so hard?
Multiple issues are at play of course and a successful BI strategy will need to address each of these. Here are my top three factors contributing to lackluster BI adoption. What would you add to the list?
IT Centric vs. User Centric Models of Delivery
A typical BI report, visualization or view can answer a question which is well understood in advance. However, when business users have a follow-up question (which they will), they typically have to go back to IT. In this IT centric model of BI delivery, users are unable to answer business questions in a timely manner so they become frustrated with the system and with IT.
In a user-centric delivery model, IT is still hugely important. However, instead of asking “What question does my business want to answer?”, we instead focus on “What types of questions does my business want to explore?”. In other words, IT does not focus on delivering a solution but instead a tool.
Lack of Business Partnership
According to a recent study that looks at the changing role of the CIO, one striking finding is that only about half of CEOs felt that CIOs understood their business and the problems that face them. Long gone are the days when monolithic technology solutions are seen as long term investments. On the other hand, evaluating and selecting tools department-by-department doesn’t leverage the economies of scale that large enterprises enjoy.
IT can still invest in stable centralized technology. But rather than a one-size-fits all approach, IT needs to deliver flexible tools at the enterprise level that provide services which can be rapidly adapted to the changing needs of each individual line of business. In this way, IT can deliver stability as well as being seen as responsive.
If we want to grow BI beyond just a deployment of tools for our power users, we need to consider the skills of our entire user community. In the U.S. where I live, this last point recently became painfully highlighted. A study published by the Organization for Economic Cooperation and Development places the United States as #17 out of 19 for numeracy skills.
As we race forward into what many refer to as an ‘information economy’ the ability to understand data and to think in numbers is becoming even more critical. Training our employees on the data and the use of data is just as important (if not more important) than on how to use the tools themselves.
What would you add to the list?
What issues do you think we need to address in order to improve our ability to drive pervasive business intelligence?