What Does it Take to Implement a Data-Driven Approach?

Having data and tools is enough, right? Not exactly. There is a lot more that goes into being data-driven.

Part one of a series.

In the data and analytics business, we often hear that organizations should be data-driven.

After all, we want our processes to be built on facts and we want to use facts to make better decisions. Given the incredible advancements in technology over the past several years, one might think organizations are more innovative than ever before.

However, according to an MIT/Sloan Management report published in May 2014, approximately 34 percent of organizations who responded still consider themselves “analytically challenged.” Only 12 percent of the organizations rated themselves as data innovators.

This information suggests that very few organizations leverage data and technology in ways that impact business. In the effort to become more data-driven, a lot of organizations have become lost. But why?

Drowning in Data and Tools

Let’s consider a few success criteria. First, organizations need data.

Ten years ago, this was a real problem. But, technology and IT have improved data access through faster processing and a broader range of tools. Data warehouses have been created to provide “one version of the truth.” Hadoop and NoSQL technologies allow for analysis of web data, images, text and other “multi-structured” data.

Today, when I talk to the leadership teams in many organizations, getting data isn’t a problem. In fact, it’s quite the opposite. Organizations seem to be drowning in data.

Since data isn’t the problem, let’s consider the next piece of the equation – the tools and the skills to analyze data.

If you’re like me, you have probably dabbled in a number of tools to drive your own decisions, whether business or personal. You may use Excel, Tableau, or a variety of Open Source tools to view data.

Our clients are similar, and most also have a number of tools. These tools include the ability to deliver reports, create dashboards and different visualizations, and develop complex predictive models. Similar to the current challenge with data, some would argue that organizations are drowning in tools.

What it Takes to Truly Be Data-Driven

If organizations have data and tools, shouldn’t being “data-driven” be easy? Why isn’t it working?

We see a lot of different challenges with our clients. For one, understanding data, especially having a consistent understanding of data, is hard.

Organizations tend to have isolated applications that define data differently, depending on the functional area. Results may make sense in one area, but not in another where an executive’s gut tells them something different.

Doing the work to bring everyone together to define terminology, determine and share objectives, and then act on the data, is hard and often difficult to justify.

Overcoming people’s aversion to change requires more than just data and tools. To really change how organizations make decisions and become data-driven, we need to think about how to drive change and reward teams for making better data-driven decisions.

Before you wonder why analytics may not be making a difference for your client, do a little more investigation. If your client seems to be drowning in data and tools, perhaps the problem isn’t technology. Perhaps it’s confronting change.