I attended a session bright and early this morning on Adoption of Analytics and OR Methods, and one of the primary topics was barriers to this adoption, the thorniest of which were people problems.

My colleague Gary Cokins from SAS categorized barriers to adoption of optimization and advanced analytics into four groups: technical (e.g. dirty data), perception (e.g. ill-formed assumptions about cost and ease of use), and design deficiencies (e.g. poorly designed models), but spent the majority of his time talking about organizational behavior. It’s these soft skills that can be such a challenge – things like leadership, communication, and change management. And trying new methods requires openness to new ways of thinking and not expecting magic bullets.

Lisa Kart from Gartner sounded a similar theme, scratching her head around why financial services hasn’t adopted optimization at the rate she would expect, since it is an industry with such a wealth of advanced analytic usage. Banks are well-versed in descriptive and predictive analytic techniques for such areas like customer segmentation and credit scoring. They even apply optimization to some areas like branch site selection or credit line optimization. So then why is optimization not pervasive? Lisa agreed with Gary and added concerns about perceived loss of control, misalignment of incentives (e.g. an overall better solution that permits uptick in an area like fraud might be unacceptable to an executive measured on fraud activity), perceived competition, and even skepticism that it will work in “my industry.”

Many of these people problems are general management issues, but areas like skepticism might be lessened if there were more OR practitioners in industry. But is it the chicken or the egg that came first? Adoption rates won’t grow without people, but my experience and that of many I’ve spoken with here is that it is hard to find those people. There is a supply and demand gap, because it is a challenge to find people with strong OR theoretical training and the ability to apply that education to solving business problems.

But as I look around and see the streets of Charlotte crawling with thousands of INFORMS attendees (those conference bags and nametags give us away) I wonder why such a large gap exists. I expect to mostly attend the analytics track over the next few days, and I know at least one of the sessions is on university programs in advanced analytics. I worked with the SAS Academic Program for years, so I know this is a perennial challenge. I’m eager to listen and learn and look out for new ideas and signs of change. Ideas anyone?

NOTE: This blog post was originally published on the Informs Transformation blog.