As more organizations embrace the use of analytics to drive business initiatives forward, one buzzword you’re likely to hear quite often in the months ahead is collaboration. Conventional wisdom tells us that collaboration is a key ingredient in any successful analytics project.
Conventional wisdom is absolutely right. Without question, as the level of collaboration grows, so too does likelihood of an analytics initiative succeeding.
It all seems simple enough, and yet, despite widespread agreement on its importance, too many analytics projects still fail for lack of collaboration.
It’s not the need for better technology or the lack of a data scientist, but the inability of stakeholders in the organization to truly collaborate. Clearly, there’s a significant disconnect between our understanding of the need for collaboration and our failure to actually do it. The question is why -- and just as importantly -- what can be done about it?
Sharing Alone Does Not Equal Collaboration
Let’s address the why question first. Why is it that organizational stakeholders, despite fully understanding the importance of collaboration to an analytics project, so often fail to successfully collaborate?
The answer lies in a misguided understanding of what it means to collaborate. Within the context of analytics, collaboration is too often understood as being synonymous with sharing: sharing of data, sharing of reports, sharing of dashboards. I’ve shared my findings, the thinking goes, and therefore, I have collaborated.
Unfortunately, sharing is just one piece of the puzzle. True collaboration requires more than just a willingness to share. It also requires team members to acknowledge that what they share is inherently biased by the personal lens through which they see the world.
This is where some might say that anyone involved in an analytics initiative needs to check their biases at the door. Good luck with that.
Our biases are a part of the fabric of who we are as people. We can’t simply remove the lens through which we see the world. The world of a marketing exec is different than that of a sales manager, whose world is different than that of an HR specialist, and so on down the line.
The marketing exec looks at a shared report through the lens of the company’s competitive positioning. The sales manager looks at it through the lens of that quarter’s sales cycle. The HR person looks at it through the lens of its impact on hiring.
All valid viewpoints, but all are biased. And if they’re stuck to unconditionally, then no matter how openly you share data and reports, true analytic collaboration will never be achieved.
The Need for Empathy
So what can be done?
If our analytics efforts' success relies on collaboration, and our irremovable biases stand in the way of our achieving it, what can we do to move forward? The answer, quite simply, is empathy.
This may seem counterintuitive. After all, we expect analytics to remove emotion from the decision-making process. But setting emotion aside in order to let data drive decision making does not preclude team members from being empathetic to the viewpoints and concerns of others in the organization.
Too often today, that empathy is lacking. In its absence, the use of analytics ceases to be a tool through which we can achieve better outcomes for the organization at large, and instead becomes just another means through which individuals advance personal agendas.
Think of how often you hear someone say they don’t use a certain BI or analytics tool because they can’t get it to do exactly what they want it to do. These are not the words of an individual that’s empathic to how a given decision might impact other parts of the organization. Without empathy, analytics, which should minimize the impact of our biases, become another weapon to further them.
Driving Cultural Change
There’s a reason analytics represents one of the fastest growing areas of investment in all of IT -- and it has nothing to do with sharing fancy diagrams as means to advancing personal agendas. What it has everything to do with is driving cultural change, not only in the way decisions are made, but more importantly, in the way team members across the organization collaborate on those decisions.
As with anything else, change starts at the top. Company leaders need to make it clear that they expect analytics discussions to be conducted with empathy toward the viewpoints of others. There’s nothing wrong with seeing things through your own lens, but there needs to be a non-negotiable expectation that team members will consider the greater good and work hard to understand the lens through which others see the world.
More importantly, it needs to be clear that using analytics to bully others or drive a personal agenda is an unacceptable part of the company’s culture.
As for analysts, being empathetic means acknowledging that yes, you too are biased. While you can’t check your biases at the door, you can make it a priority to connect with cross-functional team members in order to understand the impact a given action will have on their area of the business. When you consider the impact of a decision on others -- when you empathize -- you open the door to true collaboration and to outcomes that are truly mutually beneficial.
IT vendors also have a role to play here. We warn organizations against operating in silos, and rightfully so, but then we build single-lens analytic tools that further facilitate those silos. We need to deliver tools that enable organizations to create multi-lens analyses and develop common metrics that account for how a given decision will impact the entire organization.
Done right, analytics can be the great equalizer. We can replace in-fighting, arguing and the propagation of silos with collaboration, communication and true cultural change. None of that happens without empathy. Empathy is what makes sharing valuable and collaboration possible. Empathy -- crazy as it sounds -- is what makes analytics work.