This week, we are spicing things up a bit with this two-part article on data and our role in presenting it effectively. Natalia Kmieć-Braun was kind enough to lend her expertise as a co-author. Natalia is a Learning and Development Consultant and a Storyteller who spends her days working on training and communications for corporate clients at Accenture.
When it comes to classic box office hits, disaster movies are among the top of the list, even if they can be a bit predictable and formulaic. Typically, at the very beginning, we meet an expert — a scientist or an experienced worker — who presents the other characters with hard evidence predicting a future catastrophe. As a rule, the expert is universally ignored (hello, obvious plot device), and the consequences are, well, disastrous.
Unfortunately, this cliché of ignoring experts is not just a big screen trope, it happens in real life. Some of us have even experienced similar interactions in our workplaces. So why can’t numbers speak for themselves and, more importantly, what can we do to make sure our information is not only heard but also understood and taken seriously? The answer is twofold. The first part revolves around verifying and demonstrating the credibility of the data itself.
Before you present your data to anyone, make sure it’s solid. While verifying credibility is always a priority, if your data might have dramatic consequences, whether accepted or ignored, be sure it is reviewed with a fine-toothed comb and with fresh eyes.
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Question the source
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Firstly, if you’re not the author or primary researcher, do a deep dive into the source. Is it reputable? Are the numbers up to date? Do other sources back it up? Also, when it comes to the actual researcher/author, are there any factors that can be skewing the data? One example of this could be if the research was funded by someone with a vested interest in certain results? These days, we’re bombarded with information. Without constant vigilance, we are at risk of accepting data that is outdated or based on a bias. This can immediately negate any trust and interest garnered during the presentation.
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Broaden your perspective
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Once you are satisfied that you have reviewed the data to the best of your ability, have a trusted colleague take a look at it for you. Fresh eyes are the opportunity to catch a myriad of errors. It’s only natural that, after reading the results 10 times, we practically learn them by heart and our brain stops paying attention to details. But we don’t want to alarm anyone because of a simple mistake that we made when we were tired. Or the new perspective could provide new questions. By looking at things from a fresh angle we can get a broader scope on the problem. It is much more effective than sticking with our own tunnel vision and only reading what we expect to see.
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Question your analysis
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Once we have good, reliable data, it is time to think about the conclusions that we are drawing from it. By taking time to question ourselves, we can avoid falling prey to common analysis mistakes. Watch out for confirmation bias, confusing correlation with causation, overfitting and other traps.
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Prepare your presentation
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Once the results, integrity and extrapolations of the data are confirmed, the final step is to prepare to disseminate this information. It might sound obvious, but the crux of this is to be honest about the results. It can be very tempting to slightly embellish the numbers, round them up, or omit the data that doesn’t support our hypothesis entirely. It can even be done with the best of intentions. Experts have wanted to make the conclusions clearer to non-expert audiences. However, this approach runs the risk of backfiring quite dramatically. As soon as someone asks that one unfortunate question, all of the data and results can fall apart based on our credibility’s doubt. We do not need to take that risk when preparing to share our data.
In the end, solid data that has been double-checked and effectively prepared (without embellishment or omission) is very hard to dismiss and is the gateway to getting people to listen. However, that data might only get the meeting booked. Since data cannot speak for itself, check back for the next part of this two-piece series to find out how we can effectively lend our voices to that data.
Jacquelyn Adams is a storyteller and an award-winning CEO. She lives in a world of constant exploration, whether it’s summiting Mount Kilimanjaro, vlogging about the future of work… or discovering how she’d do in a chocolate eating contest (answer: last place). Find more of her Lessons on Leadership articles here or connect with her on LinkedIn here.
