Data analysis has an image problem. Despite the fact that data collection is priority one, regardless of how common “big data” buzzwords have gotten, and setting aside all the calls for data-centric decision making… The boots on the ground, those of us who manage this analysis daily, have a problem.


Too many analysts are viewed as tactical cogs in a machine. We aren’t brought in to own and manage projects. We aren’t consulted on big ticket company objectives beyond the reports we’re asked to push out. Why? Because we aren’t doing enough to show value. 

If we want to grow and improve, for the good of our own careers as well as for the benefit of the companies we work for, we need to figure out how to turn this around. So, how do we do it? By graduating from tactical resources to strategic powerhouses.

The DIKW Pyramid

The first step on the way to graduation is to reevaluate the DIKW pyramid. We’re all familiar with it, yet too many of us focus on the lower levels and never make it to the top. The top is, unquestionably, where we need to be.

As a brief refresher, here’s a quick example:

2019.12.17 Image

Too many of us focus on wrangling data, and “polish it up” by adding a little information-based context. Many of our reports don’t make it beyond the Information stage above. But widget-producing organizations don’t live or die based on how much they can talk about past widget sale activity. They survive by selling more widgets. 

If data analysts want to elevate their position and perceived value, they need to align their deliverables to this business directive. Don’t focus solely on the D/I past; spend your time worrying about the K/W future. Beyond what our historic view shows, how can your company leverage it moving forward?

Presentation is Key

Now that we understand what we should be talking about, we need to address how we talk about it. Data analysts often earn the reputation of being all but indecipherable when talking to team members who aren’t steeped in facts and figures. Improving how we communicate will go a long way in graduating to strategic powerhouse.

Prioritizing your Work

Our widget example is obviously oversimplified. In this case, there was a clear call to action and few variables to consider. Real life doesn’t work that way. As such, we need to consider how to spend our limited time. We need to prioritize projects that will give us the biggest bang for our buck.

The Future of Analytics

To be incredibly blunt – there isn’t a future in straight data processing. Machine learning is getting too good. Your boss won’t need you to manage the tactical elements of data stewardship moving forward. In fact, they can likely already take raw data, plop it in a prepackaged BI platform, and have simple analyses generated for them in a matter of minutes. 

What your boss needs from you (now, and increasingly in the future) is to step up and move beyond conducting the analysis to show what needs to be done as a result of that tactical work. Don’t just support change incrementally from behind your reports – be the catalyst for big ticket change.