Analytics have grown in importance over the past few decades, and the capabilities available through recent technological innovations are amazing. Business investments in analytical solutions are ever-increasing—denoting the strategic importance placed in these solutions. Yet the most difficult aspect to realizing success with analytics has been, and continues to be, the organizational challenges getting those stakeholders most likely to benefit to embrace an innovative mindset.
People talk about building a culture that enables innovation. However, most people still exhibit ideas and actions that keep them grounded in “how things have always been done.” Conversely, some look to invest, but want to take a completely hands-off approach in how analytical tools will be leveraged. In either case, the real hurdle to succeeding with analytics is not the technology but the culture of the organization.
Build it and They Might Not Come
Early in my career, I was fascinated by the possibilities available by using data and analytic techniques to solve business problems (and still am!). One of the first big problems I tackled involved using predictive capabilities to support and prioritize marketing efforts. Back in 1995, a colleague (John Crites) introduced me to a relatively new analytic technique called “neural network modeling.”
We worked together to develop segmentation plans and predictive targeting capabilities using this and other analytic methods. Having become very enamored with our approach, which was very leading edge in the mid-90s, we presented our findings to our boss, the vice president of marketing.
Armed with a statistically valid and innovative approach to marketing, detailed data to back up our findings, and an abundance of youthful enthusiasm, we made our case. Our boss listened to our pitch, then delivered a line I’ll always remember, “Guys, that math of yours is all fine and good, but me … I market from the gut.” He proceeded to deliver a dissertation on how marketing is something a person feels and is subjective rather than an objective science.
Admittedly deterred, we nevertheless plodded ahead and continued to demonstrate how much more effective our approach was than the current “shotgun” sequential direct marketing tactics. After some time and a lot of convincing, we were given a pilot to test our approach. When the results came in, we were ecstatic to see that we had far exceeded existing campaigns. Even our boss was impressed—so impressed, in fact, that he said, “Let’s continue and use this approach to contact everyone.”
Needless to say, our results diminished as we targeted the remaining candidates—for the exact reason we prioritized contacts in the first place. Despite our attempts, which turned out to be in vain, to explain how predictive targeting works by prioritizing our efforts, we eventually came to understand that a semi-monopoly in a regulated industry has little need to use advanced analytics to prioritize leads. That’s when I realized we would never be successful leveraging our newfound analytic innovations at that company. It’s also when I decided to quit that job and pursue a consulting career that allowed me to work with companies where real analytical opportunities exist.
You Get the Behavior You Reward
What I failed to realize back then, but have never forgotten since, is that you get the behavior you reward. The company expressed interest in applying innovative, analytically-based science to its marketing strategy. It supported a pilot and was genuinely impressed with the results. At the end of the day, however, executives were not incentivized to implement those capabilities. Therefore, as much as they talked about being converts by embracing an analytic mindset, they were never truly interested in supporting an analytic culture.
Unfortunately, this is not an isolated scenario. It’s still common today. The best example is the chasm between most business and IT organizations. These groups have diametrically opposed reward systems. To build and expand a culture of continuous innovation requires them to work together.
Never look at what is working well today and assume that this is going to be the best way to do something for the foreseeable future. #embracechange #practicebeingbest
Neither of these groups are wrong, and the goals they have are all valid. What’s evident, however, is that these goals, on the surface, are incompatible across the business/IT divide. I cannot count how many times I’ve heard business users proclaim, “IT doesn’t understand the business” or “IT is too slow and bureaucratic to support our needs.” Of course, these are the same people who scream if a system shuts down unexpectedly, there’s data inconsistency, or IT didn’t understand some ill-conceived requirement and interpret what business users actually wanted (rather than what they said they wanted).