Bad News for Analytics and IT Staff
Healthleaders magazine recently surveyed selected members of its readership for its annual Industry Outlook Survey. Three hundred-ten responded.
Among other things, the survey sought perceptions about overall performance for CEOs, senior leadership in general, and various functional departments. CEOs rated very well, with 43% of respondents describing their CEO’s performance as “very strong.” The next highest category was the overall senior leadership team with 30% calling them “very strong.”
What about the other end? Who scored lowest? With only 10% labeled “very strong,” data analytics staff got the lowest vote of confidence. And at 15%, IT staff didn’t fare much better.
How should we interpret these results? Clearly both data analytics and IT staff have work to do. A gap of 33% between CEOs (43%) and data analytics staff (10%) indicates a genuine disparity of performance.
Having “cut my teeth” professionally as a data jock working in a hospital planning department and then moving on to executive leadership roles for the next 25 years and supervising IT, I understand all three of those worlds. Here is what I would say to my data analytics and IT friends.
With your superior systematic thinking and logical abilities, you are to be congratulated for your commitment to detail. Lack of precision can lead to flawed conclusions. However, exploring every subtlety and over-qualifying every statement can create the impression of uncertainty or waffling. Senior executives are charged with making organizational decisions, many of which are binary: yes or no. When analytical types repeatedly qualify each statement out of a legitimate desire for accuracy, they sometimes either create the impression that they are not confident in their positions or appear to be non-supportive of the direction the organization is going in.
Over the years, I have learned to preface “qualifying-type” statements with, “I think we are heading in the right direction, but I would like to offer a ‘Devil’s Advocate’ position. Is that OK?” It’s amazing how this simple approach puts my subsequent comments in context and gets people to consider my point.
So I suggest my analytical friends learn to “bracket” their qualifying comments by a clear summary statement at the beginning followed by whatever nuance they feel is needed and ending with a reiteration of their recommendation. This suggestion applies equally to analytics and IT personnel.
On the other side of the equation, I suspect that part of the poor ratings for data analytics and IT staff stems from senior executives’ inability to appreciate the contributions of disciplines they don’t fully understand and are perhaps intimidated by. “Type A” people sometimes charge through a situation and just want to “get to the point.” They should recognize that nuanced observations can inform strategies and help organizations avoid regrettable decisions.
Another thought. Although the survey report didn’t provide the demographic description of respondents, I suspect a higher percentage of CEOs and senior executives completed the survey than did data analytics and IT people. If this is the case, it’s not surprising that CEOs fared better than did the analytical types.