Partner Management

Want to persuade people with data? Start with emotion.

Part 3 in the ongoing series on using Theory of Mind to increase your impact. For an overview of Theory of Mind, check out Part 1. To learn more about finding the right audience for your work, see Part 2.

I once led a research project to define the future of a major tech product. After months of extensive international research and analysis, I had a wealth of data that all pointed in the same direction. I also had a sleek presentation deck that brought that data together into a tight package supporting my recommendations. I was completely set up for success — I had strong stakeholder buy-in for the project and an opportunity to present to leadership. I walked into that room of 12 leaders with my head held high and presented my heart out. I was pretty sure I had nailed it. And then a week passed. And another. And another. And nothing came of it. The data went nowhere and nothing changed.

I later found out that, while I had technically done everything correctly, the recommendations simply hadn’t landed. The direction I had proposed was too similar to a direction that had been tried in the past and failed. And, while there was new evidence to suggest it was worth pursuing again, no one in the room was willing to take the risk. And no one understood why the direction I was proposing was different.

While I had been busy focusing on the perfect research presentation, I had forgotten what really mattered: the people who were going to use my data.

A key part of any data analysis is deciding what information to include in the final report (and what to leave out). The goal of this process is to distill all of the knowledge collected during the course of an investigation into a clear, concise package of takeaways and recommendations. When going through this process, my mind should have been on one thing: what did I need to convey to convince the leaders in the room? I needed to think like they did. I needed Theory of Mind.

Theory of Mind is the cognitive skill that allows us to attribute mental states to others.

If you want someone to use your data to make a decision, you have to put yourself in their shoes. What do they know, believe, desire, and feel? Based on this, what do they need to see from the findings to make their decision? Your job is to build your findings around conveying this information.


To put yourself in the shoes of your decision-maker, start with the fundamentals. What does this person already know? And, perhaps more importantly, what don’t they? Frame your findings in a way that adds to their existing understanding of the space. Make sure you aren’t answering a question they already have a solution for.  If your findings are similar to past work, make sure it’s clear how you are building on that work or challenging it. Identify any critical gaps in their knowledge. Is there past or current work that they might not be aware of? Summarize that as clearly as possible.

Equally important is to ask what this person knows about you and your project. Do they know why you did this work? Do they understand the process behind it? Be sure to include any relevant details about how and why you approached the work the way you did. If they aren’t familiar with the problem space or your methodologies, have additional explanation prepared to share (i.e. in an appendix).


This is the area most data folks are likely to skip over: what does your decision-maker already believe about the world? Beliefs are distinct from knowledge. Knowledge relates to the information your decision-maker has about you and your problem space. Beliefs are the conclusions this person has already come to. Entrenched beliefs can sink even the most compelling data work before it begins. And, unlike knowledge, beliefs can be hidden (even to the person who holds them).

Look for sacred cows (beliefs that run so deep they can’t be challenged) and land mines (touchy subjects that are likely to blow up in your face). If you can’t talk to the decision-maker directly beforehand, talk to someone who works closely with them to identify these beliefs in advance. Make sure to avoid these topics if they aren’t core to your work. If challenging them is central to your work, be sure to have a rock-solid argument prepared in advance.

Don’t stop at the problem space, make sure you know where you stand with this decision-maker. What has their past experience been like working with you or others in your role? Are they likely to trust you? Will they see you as a subject matter expert? Before trying to persuade them based on the data, make sure you first cultivate credibility with them.


We’re all human – we want to be seen as competent and good at our jobs. Company leaders are no different. The best way to have impact with your work is to align it to the goals of the people who will use it. What is your decision-maker trying to accomplish? Are they trying to make a name for themselves in a specific area? Do they need a quick win? Do they have a passion for a particular type of work? Shape the narrative of your work to fit with their needs.

I want to be clear: you should never ever compromise the integrity of your data. There are some cases where your findings simply won’t align with leaders’ goals or beliefs. You should never water down or twist your findings to try to match a leader’s agenda. But in most cases, your findings will naturally fit with at least some of your leadership’s goals. Help them connect the dots to see how your work will help them get to where they want to go.


Like beliefs, emotions are a sneaky part of the equation that can easily be overlooked. But understanding them can be key to unblocking important decisions. What does your decision-maker fear? Have they been burned in the past by data? Are they under pressure to deliver? Do they have something to prove? Make sure to address these concerns when you present to them so they don’t distract from your overall narrative.

In my case, I failed to understand the fears of my stakeholders. No one in that room wanted to be responsible for repeating a mistake from the past. To make matters worse, I had named the product solution similarly to that past failed idea. Knowing this, I would have worked harder to differentiate my recommendation from the previous iteration and called it something completely unique.

By now you’ve identified the right decision-makers and crafted a compelling case to recommend a course of action to them. But you’re not quite done. Now it’s time to think through how your decision-maker will act on the data… and what you need to do to integrate your findings into that process. Stay tuned for part 4 where I’ll explain how to build your insights into your decision-maker’s workflow.

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) or on LinkedIn.

Photo by Josh Calabrese on Unsplash

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