The Joy of Data-Driven Decision-Making

The boss calls you into her office. She’s asking for your opinion, your gifted insight. What do you do? Although it may not be your first response, a quick read of A Step-by-Step Guide to Data-Driven Decision Making for Federal Employees by Cindi Johnson would be worth your while.

Gifted insight is not born of superpowers; it’s the fruit of data. And, while data analysis may not be what you signed up for, the ability to communicate the stories behind the data is an increasingly valuable skill. Once you understand the data’s purpose, you can start in earnest. Johnson cautions readers against beginning without a clear objective that defines which data to gather and why to avoid engaging in “wasted time and effort working on solutions that do not produce the desired result.”

Gathering Data

Data-Driven Decision-Making (DDDM) starts with data gathering. Quality data from quality sources anchors virtually any argument. If the sources are defensible, the data comes across as rock-solid. It’s largely a matter of knowing what data you want and how it will be used. The all-important question is,

“When all of the data is gathered, what does success look like?”

If you understand the answer to that question, there’s hope that you will identify the right data and have a much clearer understanding of its sources.

Analyzing Data

For some bosses, the data alone is sufficient. For others, a presentation complete with graphics is required. While data may be interpreted in many ways, with the proper presentation, decisions rooted in the data become clear. Choices can prove self-evident. The classic multi-criteria decision analysis matrix is nothing more than a simple weighted table designed to allow for multiple variables. Johnson suggests that using such tables to recommend the best decisions leaves the door to open to influence the ultimate decision-making authorities.

Taking Action

Ultimately, all of the research in the world is useless without action. While data-driven decision-making is powerful, action needs to follow the decisions. Yet there are those data-passionate souls who crave only one thing—more data. In DDDM, these are actually dangerous people. They are largely the souls responsible for “analysis paralysis,” constantly sending you back to the drawing board to gather more data. But you can solve that problem.

Stopping analysis paralysis is done by making the outcomes of the DDDM process so self-evident that while options remain available, the primary option is the only logical choice. Make those outcomes bulletproof by tracking all of the hard work done during each of the process steps.

  • Objective – Being able to go back to a specific, measurable, agreed-on, realistic, and time-limited objective affirms that all parties in the analysis strive for the same goal.
  • Data – Choices need to be based on the nature of the objective. With a clear, shared understanding of why the data sets were chosen, the data take on a higher level of acceptability.
  • Analysis – We parse data every day. We use it to make sound decisions and to help others see the data the way we see it. More data is not inherently better data. Incisive analysis leads to better understanding and acceptance of the data.
  • Presentation – Sometimes, a simple Excel spreadsheet will convey all of the information required. In other situations, a graphic sells the message. As Edward Tufte offered in The Visual Display of Quantitative Information“Of all methods for analyzing and communicating statistical information, well-designed graphics are usually the simplest and at the same time the most powerful.”
  • Call to Action – In all scenarios with DDDM, the analysis should drive a call to action. Once that call is made, the actions (and their potential outcomes) should be self-evident.

Next time someone asks you for a decision or recommendation, start gathering data. Even if the data are sparse, the fact that you’re gathering data speaks volumes. And, if you embark on the entire process as outlined in A Step-by-Step Guide to Data-Driven Decision Making for Federal Employees by Cindi Johnson, all the better. You can create strength in your decisions and ensure management that you’re working in your organization’s best interests. That’s a nice side to be on.

Written by:
Carl Pritchard



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