Over the years I have found analytics and data science author and consultant Neil Raden to be a welcome voice of common sense, including a healthy dislike for buzzwords:

One particular Neil Raden blog article really struck a chord with me. It appears to no longer be available online, unfortunately, but the title speaks for itself: You Cannot Fix a Broken Company by Measuring How Broken it is. Neil’s article went to the heart of what business intelligence is – and what it is not:

The BI industry has sort of casually sent the message that BI makes companies better… But the question is, once you expose something that needs attention, what next? As a consultant and implementer of data warehousing and BI for many years, I never really came up with a good answer…

And here is a especially important comment:

Even when we did everything we set out to do [in our BI/DW consulting engagement], when approaching management about the next phase of the operation, to help the client start addressing the problems with employee morale, high turnover, inventory snafus, poor customer service, etc., the response was usually something like, “Neil, aren’t you the data warehouse guy? Shouldn’t we get McKinsey in here to work on that?”

It’s bad enough that Neil got a condescending “You’re just the techie” brush-off from management. It also raise a much more serious concern: Why would management’s first response to serious business problems be to bring in outside consultants to handle it? Isn’t that their job? Was management basically admitting they’re not up to the job of addressing these issues on their own?

One more quote from Neil’s article:

In short, if you’re involved with BI, you may have as good or even better insight into what is going on in the company, but you clearly lack the portfolio to do anything about it…

To Neil’s point, I see an analogy between BI tools and medical devices: Both can identify serious “illnesses” within companies and patients, respectively, but neither can provide a “cure” on their own. (Of course, as BI can help identify ‘good’ things too, like uncovering positive new business trends, etc.).

Many years ago I spoke with the founder of a start-up medical device company, who told me that in order for a new medical diagnostic system to be successful, a course of treatment must also exist. He told me that several years ago a then-new medical device detecting bone density loss was of limited benefit (and a limited market), because there wasn’t as of yet an effective treatment for the patient to take (today, thankfully, that is no longer the case).

The good news for practitioners and developers of BI/DW technology is there are indeed plenty of “courses of treatment” to reverse the effects of low employee morale, high turnover, inventory snafus, poor customer service, etc. These courses of treatment, however, require strong leadership dedicated to rolling up their sleeves, and actively using BI tools as part of a culture of data-informed decision-making.

In contrast, if management is so hands-off that its default is to halfheartedly “sub out” addressing pervasive business problems to outside consultants – or, even worse, ignore those problems completely – no amount of BI may be enough to effect authentic change. It’s a bit like a doctor showing a chain-smoking patient an x-ray of his damaged lungs, and yet the patient can’t bring himself to actually kick the habit.

I’d like to point to the University of Maryland, Baltimore County (I very much enjoyed working with UMBC, a customer of a former employer of mine; see my case study here) as an excellent example of an organization embracing that essential culture of data-informed decision-making.  This culture is actively advocated from the top, by UMBC President Dr. Freeman Hrabowski. It’s no coincidence that President Hrabowski repeatedly emphasized the importance of a “culture of critical thinking” and the need for a “deliberate effort” to engage in conversations and problem-solving with others.

The bottom line is analytics can serve management as a key diagnostic tool, but management in turn has to believe in the efficacy of the “courses of treatment” and actively commit to a managerial culture of data-informed decision-making that does not regard practicing good business health as somehow being someone else’s responsibility.