brandon mathias blog

Lessons Learned: Tips on Communicating Complex Data Analysis

Analytics professionals have superpowers in generalizing. We even describe how well a particular model works by evaluating how well it “generalizes” to new data. Despite that special skill, I won’t make a sweeping generalization about all data analysts. So, I’ll only speak for myself when I say I find presenting results of complex data analysis to be personally challenging and stressful. It has taken a lot of practice to get better and fight the nerves when talking about what I do.

So, I want to use my space here to list some strategies I have found helpful when it comes to sharing complex analyses with interested stakeholders, should other analysts feel the same way.


Start Simple Before Diving Deep 

First, start with the problem and answer before explaining how you got there. I know it sounds simple, but beginning with the answer helps set the context for your audience. It’s what the stakeholder really cares about. Treat the methodology as supporting detail and lend credibility to the answer, but don’t make it the focus of your presentation. 

As analysts, we have spent years learning the tools and metrics, so it’s tempting to want to share the fine details of complex datasets, but sometimes it can distract us from what is actually essential.


Visualize You Complex Data Analysis for Clarity

Second, be a meticulous data visualizer. Data visualization is our greatest tool for communicating results. Spend the time to make every graph’s intent immediately obvious to the audience. Begin with the basics. Label your axes and start at zero. You know the drill. But more than that, step back and ask yourself, can someone look at this graph and understand the information? Clarity must be the first priority.

team working on complex data analysis

Tailor Your Presentation for the Audience

Finally, prepare for the intended audience. Are you sharing your results with other analysts or non-expert stakeholders? If your audience includes other analysts, you may want to go into detail about the methods and models you chose. I’ve gone so far as to share code snippets with other data analysts so they get a better feel of the research process. 

If you are sharing with non-expert stakeholders, focus on the answer and explain through visualization. Lastly, when sharing with executives, put the details in an appendix and delete the appendix.

Reflect, Improve, and Practice

If you, like me, find presenting complex data analysis difficult, know that practice will help, but reflection will help even more. After presenting, take personal notes on what worked and what didn’t and adapt accordingly. Before long, you’ll have a new superpower.

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