Better Decisions Faster: Analyst vs. Executive

The problem with objective data is it isn’t always fast. The problem with subjective data is it isn’t always right.

Let’s say you were to ask a few dozen executives how they make decisions. Some will tell you that they look to data; some will tell you that they go with their gut. Some will have an answer that addresses both data and instinct. But throughout your interviews, it will become clear that decision-making is far from an exact science. And yet, the ability to make and follow through with decisions is arguably one of the most important skills an executive develops.

Now let’s say you were to ask a few dozen business intelligence and analytics practitioners, a burgeoning field of increasing importance to business strategy and direction, how decisions ought to be made. Certainly not all, but many will get hung up on objective data, as if it is the only valid input to decision-making.

I am by no means anti-analytics. On the contrary, I built a marketing analytics company and helped steer dialogue on data-driven customer experience over the past five years. Data-rich customer environments are my playground.

It’s just that as both an analyst and an executive, I know that the messier truth is that every decision is informed by some ratio of objective and subjective data. The simple problem with objective data, from an executive viewpoint, is that it isn’t always fast. The problem with subjective data, from an analytics viewpoint, is that it isn’t always right.

A friend who was an officer in the Navy told me that her unit used to do a training exercise where each person ran up a set of stairs on the ship, and at the top of the stairs, they were forced to turn right or left immediately without looking in either direction first. They had no way of knowing what they would face if they turned one way or the other; they simply had to choose and contend with the outcome, whatever it was.

The value in this training for an officer or an executive is where the corollary to decision-making comes in: dealing with change. Change is a constant over which we often have very little control. Cue Darwin: our ability to adapt is the key to our survival.

It is completely possible to be rational about subjective data. Just because your decision is informed by something other than numbers and charts doesn’t mean you’re not informed.

For example, when you dress each morning, more than likely you consider the temperature, which is objective data, and you probably also think about what meetings you have during the day and what kind of an impression you’d like to make on the people you meet with. Your assessment of what impression certain clothes will have on the people you meet with is subjective, but informed by experience.

So how does a data-savvy executive incorporate objective data into a fast-paced decision-making environment?

There must be a rigorous yet adaptable framework for hypothesis-driven leadership that utilizes available knowledge, adapts to change, and assesses the outcome. This must be straightforward enough to be a routine and consistent enough to benefit from iterations that lead to insights. At the very simplest level, this could be depicted as a cycle:

change-outcome-decision-outcome iterative

Gathering and analyzing data is a meaningful part of improving ongoing operations. The more aligned the intelligence-gathering is with the strategy and direction of the business, the more likely there will be relevant objective data available to inform decision-making.

The imperative to executives is: involve your analysts in strategic planning so that they can help model the business in the data they collect and assess, and provide increasingly more value to you with each iteration of the process.

The imperative to analysts is: recognize the limitations of reactive and objective data in timely executive decision-making, and strive to build predictive models that provide at least relevant directional insight about the company’s strategy. This will reinforce your value and the value of business intelligence, and will strengthen the process for future decision-making.

Go forth, collaborate, and be relevant.

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