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This article is the final installment in using Theory of Mind to increase your impact with data. By now you know who to tailor your findings to and what information to include when influencing a decision. There’s just one more piece to this puzzle: how do you share your findings to maximize your impact?
Let me ask you a question. How often have you seen data presented (or presented data yourself) in one of the following formats: slide deck, presentation, document. Did you answer, “pretty much every time?” If so, you are not alone.
There are so many ways that data can be shared. And yet, results are almost always presented in one of these three formats. Don’t get me wrong, I love a good slide deck. Presentations are my jam. And documents are just so darn efficient for writing up results. But how often do these deliverables end up living on a shelf, collecting dust and going nowhere?
Here’s the problem: we tend to present data in ways that make the most sense to us. But that ignores the fact that people, most notably our stakeholders, think differently than we do. We can’t expect them to eagerly read through hundreds of slides, carefully scrutinizing each graph and chart along the way. If we want to have impact with our data, we need to present it in a way that fits our stakeholders’ decision-making process.
What do I mean by “decision-making process?” Imagine you’re shopping for a watch online. How do you decide which watch to buy? Maybe you pick the watch with the highest average customer rating. Or perhaps you might be persuaded by a particularly well-written review. Are you the type of person who just trusts your gut? Or maybe you need to try on all the watches in person before making a decision.
Like all human beings, the leaders at your company rely on a variety of mental heuristics to arrive at conclusions about the world. They may not even be conscious of these shortcuts. But if you want to be able to consistently convince them with your data, you need to be able to understand how they incorporate information into their thinking. What kind of information do they find most compelling? If you know this, you can match how you share your findings to how your leaders make decisions.
While there are many ways to make decisions, a few common decision-making types tend to crop up over and over in tech. Think of these as a starting place for understanding how your individual leaders make decisions.
- Data Purist – These technical thinkers need to see detailed data (and the accompanying analysis) to be convinced. Make sure to include quantitative backing where appropriate, break down your analysis in detail, and invest in data visualization techniques.
- Storyteller – These creative thinkers want a compelling narrative that crescendos into a big takeaway. Invest heavily in a presentation format that builds clearly and cleanly to your key points.
- See-it-to-believe-it – These product leaders want to experience everything themselves. Invest in a research process and deliverables that allow them to experience the problems and opportunities firsthand.
- Hands-on-learner – These developers are the people most likely to be in charge of implementing the changes recommended by your work. They want to be part of the solution. Invest in workshops that allow them to get their hands dirty and contribute to the final outcomes.
Data purists often come from a technical background. They may have been engineers or academics in a former life. They believe in the power of statistics and tend to make decisions based on numerical evidence. This experience with data can work strongly in your favor – you won’t need to convince them that they should use data or explain basic stats concepts. However, their knowledge can be a double-edged sword. Data purists often have a strong bias towards quantitative data and know just enough about your area of expertise to make them dangerous. Expect a lot of questions about how you performed your analysis and to defend your choices against how they would have done it.
For these decision-makers, it will be important to include quantitative support for your findings, even if your approach was primarily qualitative. Findings should be kept factual, so avoid narrativizing the data and ensure the logic between your findings and recommendations are crystal clear. Don’t skimp on the details when it comes to your analysis. Annotate everything. Keep the outputs of your analyses on hand so you can quickly prove a point if challenged.
It can be tempting with this group to rely on the old faithfuls: a deck, document, or presentation chalk full of graphs and tables. But most high-impact decision-makers aren’t going to have time to comb through all that data (even if they want to!) nor will they have the bandwidth to remember it once you leave the room. Data visualization is your greatest weapon for this group. Invest your time in creating a few representations of your data that clearly make your key points. This is where it pays to be familiar with a wide range of visualization techniques. Some of my personal favorites include the heat map, 2×2 matrix, alluvial diagram, and radial line graph. If you’re doing it right, you should be able to tell a compelling story with just one or two visualizations.
Storytellers are common in creative industries. They tend to make decisions based on their intuition, creative taste, or vision for the product. Convincing them requires a keen understanding of their product narrative – and ensuring that your work plays into it. Presentations for this audience should have a strong story that builds cleanly and clearly to the overall takeaway. For instance, you might start by demonstrating that you understand and share their vision. Then introduce whatever obstacles you’ve uncovered in your investigation that are preventing them from reaching that vision. Finally, reveal the solution that your data supports.
It’s easy to go overboard with this group and try to cram all of your findings into the story. You’ll need to have a keen sense of what findings are important (and which ones aren’t!) Take care not to over-complicate your findings. Yes, you may have found 20 different issues with the product but are they all critical for your decision-maker to hear about right now? Stick with the findings that are going to have the most impact at this moment. You can always follow up with additional findings in the future.
For this group, video or highly visual presentations are often most compelling. At minimum consider investing in a highlight reel of your findings. If you have the resources, a well-produced user story (that is representative of your broader findings) can be highly persuasive. Alternatively, a highly visual presentation (think more Ted Talk and less college lecture) can help you sell your story.
Some stakeholders simply have to experience something themselves to believe it. I once worked tirelessly for months to try and convince a set of stakeholders that we needed to invest in research for our rapidly growing user-base in another country. I shared multiple presentations packed with tidbits of research we had already conducted that showed the unique opportunities and challenges we faced in that market. However, it wasn’t until a few months later when that leader visited the country himself that we ended up getting any traction on the idea.
See-it-to-believe-it leaders tend to make decisions based on their personal and professional experience with the product. They need to see or do something firsthand before they can fully incorporate it into their thinking. Note that this group might require some additional investment (or creativity) on your part to convince. Think through how you can get them to feel and understand the findings for themselves. For some ideas on how to implement this with your own work, check out these articles on mini-museums and cultural immersion trips.
These leaders are a distant cousin of the see-it-to-believe-it types. Unlike the former group, they don’t need to experience the issues firsthand. They generally trust the data you and your colleagues have produced, even if their personal experiences differ. However, they may be skeptical of your recommendations. They want to be in there with you, taking your findings and turning them into a product reality.
Hands-on-learners are often the people closest to the product: ground-level product managers, designers, and engineers. They don’t want to hear abstract findings and recommendations. They want specific, actionable next steps. And they want to be a part of the process that generates them.
To satisfy this group, invest in workshops that allow your decision-makers to get their hands dirty working with the data. Creating a workshop can be a lot of work but the results are almost always worth it. For one, you have guaranteed buy-in from the people who are going to implement the solutions. Additionally, you can leverage the expertise of the people who know the most about the product. While I won’t go into a ton of detail on how to create a successful workshop here (maybe an article for next time?), examples of workshop structures might include persona generation, journey mapping, or filling out a strategy canvas.
Genevieve Conley Gambill is an insights and data strategist on a mission to do good with data. You can find her online on Twitter (@tiny_data_tech), LinkedIn or Facebook.