What Business and Analytic Professionals Say About Each Other Should Worry Every CEO

In my high school, kids in the math club didn’t sit with those in sports or student council. By age 15, it was obvious that nerds and class presidents had vastly different interests and opposite personalities. Each group pursued their own type of success, whether in science projects, honor roll, athletics, or social recognition. But they valued different things and, often, didn’t like each other much.

Fast forward through college and early career experiences; some of these same people are now executives and data scientists in corporations, sitting across from each other in conference rooms instead of cafeterias. 

How well do they work together?

Recently, I began to wonder about my perception of how these two professions interact. Is there really a communication gap? Or is there cross collaboration between departments? Perhaps the situations I’ve witnessed—with obvious discord—were unusual. Maybe their collaborations succeed more often than I knew.

So, I decided to ask.

I ran two polls on LinkedIn, one for business professionals who work with analysts, and one for data professionals working in business. The responses were confidential. In each poll, thirty people responded. The results confirm my observations and tell a troubling story.

How business professionals describe their interactions with analytic teams

In the first survey, I asked business professionals to choose a response that best described the quality of their interactions and how often they get and understand the answers they request. Here we see their responses. 

Almost one in five described their interactions as frustrating, where they did not get what the needed. Half categorized them as adequate, sometimes getting what they needed. One-quarter chose good, and only 7% said their interactions are awesome and they always get what they need.

In all, two-thirds described their interactions negatively. 

How analytic professionals describe their interactions with business team members

In the second survey, I asked analysts to choose a response that best described the quality of their interactions with the other team. Further, it included how often the business team gave analysts context for their requests or invited them to provide input. Here we see their responses—which are surprisingly similar in quality to those of business professionals.

Again, one in five described their interactions as frustrating, where they did not get context for the request or have an opportunity to provide input. Almost half categorized interactions as adequate, sometimes getting context, but still not being included. One-quarter chose good, and only 8% said their interactions are awesome and collaborative. Once again, two-thirds described their interactions negatively. 

We’re still miles apart

These results confirm that we have a disconnect. More often than not, effective collaboration is not happening. Admittedly, not all data scientists are nerdy. And not all executives used to be captain of their sport teams. But similar tensions exist. These two groups see the world quite differently and, in my experience, may not appreciate the value brought by or the challenges faced by the other. 

People who work at the business-analytic interface will not be surprised by these numbers. As we see, less than 10% of those on either team feel great about their relationship, and from other reports we know that 80% of analytic projects deliver no business value. 

Regardless of which team you belong to, these findings should alarm you. And leaders should consider the implications. Two sets of highly paid, well-intended, experienced professionals do not successfully collaborate. As we have covered before, there is a high cost to miscommunication between these teams: rework, lost opportunity, low productivity and higher turnover. 

What companies can do

To begin, it is important to acknowledge that we face a reoccurring challenge. Miscommunication is not something that happens once in a while; it occurs every day, repeatedly.  

Next, it helps to understand the dynamic: it happens primarily because we don’t take time to provide each other context or empathize with the needs and priorities of the other team. There are steps we can take organizationally and strategically to reinforce teamwork and create a true alliance. It begins with leadership setting the example of respect for all the people in the organization, no matter their job description and pay grade.

Also, we need to train Analytic Translators who can speak both languages—business and analytics—and decipher in both directions: identify what the business needs in analytic terms and translate analytic findings into business results.  

Without attention, it will only get worse
More than ever, we need these teams to work together.

Several prominent trends foreshadow a relationship that will continue to worsen.

First, because of a shortage of data scientists, spread-thin workers will have less time to explain their work to colleagues.

Second, remote work, while not bad for productivity, results in less communication between teams.

Third, adoption of increasingly complex analytic methods such as machine learning and AI will widen the gap in understanding between analysts who generate the results and business professionals who need to apply them. We will need cross collaboration between these departments.

Leaders who ignore how these teams perceive each other do so at their peril.