How to Communicate Data Effectively
Bridge the gap between data and decision-making with clear, actionable communication: A guest post by Thomas Schmidt from Metabase.
Welcome to my Data Analytics Journal, where I write about data science and analytics. In August, paid subscribers learned about:
Predicting LTV with ML - Three case studies on using ML models to predict LTV for freemium. Learn how to choose the right model, incorporate seasonality effects, and address the specifics of LTV modeling in freemium.
The Database of Winning A/B Tests - A curated collection of proven A/B tests, including success rates at different companies and the importance of transparent experimentation.
Handling Missing Data: Should You Drop or Impute? - Exploratory Data Analysis: Techniques and methods for handling NULL values in modeling and analysis.
Analysts come in all forms and types - some are more advanced in statistics, some in data mining, and others - in business analytics - but what unites us all is the art of data storytelling.
It’s okay if you’re not an expert in Python, don’t fully understand data structures, or are slow with dashboarding. Trust me, your career success will depend on your ability to communicate - delivering concise, clear, and actionable insights.
It’s challenging to distill months of work with an ocean of context into a short sentence on a slide and a tiny graph. How can someone achieve it?
While I am in Vancouver this week (and if you’re around and need a reminder of why analytics is awesome - let’s meet!), I turned to a fellow data scientist, Thomas Schmidt, to help us. Thomas, who also gave a talk on improving communication between data experts and stakeholders for the Munich Data Geeks, the largest data community in Germany, shares with us today the best practices of data storytelling that he developed at Metabase, Shopify, and DeepL. He has put together one of the most practical guides on communication in analytics I have ever seen, and I am so excited to publish it in my newsletter!
Thomas is an analytics engineer at Metabase, an open-source BI tool that lets everyone work with data, with or without SQL, for internal and customer-facing embedded analytics. I use Metabase, and I find it intuitive and easy to start with. I also love their community stories - quick one-pagers focused on the fundamentals (I even published the A/B testing Checklist there a few years ago).
Below, Thomas will walk us through strategies and guides for bridging the gap between data and decision-making with clear, actionable communication.
TL;DR: How to Communicate Data Effectively to Executives
Understand the core problem and tailor your message to your audience's needs.
Start with a TL;DR: Summarize key insights upfront to respect executives' time.
Keep it concise: Remove unnecessary details and clutter from presentations.
Use colors intentionally: Highlight key points and create visual connections.
Make bold statements: Provide confident recommendations, using appendices for details.
→ Apply these guides in your next presentation to ensure your data insights drive informed decisions.
Intro
Have you ever been to a foreign country trying to get directions from someone who doesn’t speak your language? That’s how I felt the first time I presented my complex data analysis to an executive team. Their confused looks made me realize that while the data made perfect sense to me, it was like speaking a foreign language to them. Just like a translator helps people understand each other, we need to bridge the gap between our detailed analyses and the decisions executives need to make. Effective communication isn’t just about sharing insights; it’s about making sure those insights are understood and lead to action. In this post, I’ll share lessons I’ve learned at Metabase, Shopify, and DeepL in turning data into clear, compelling messages that resonate with executives and drive informed decision-making.
Identify the real problem and tailor your message to the audience's needs
In our data jobs, we are often driven by curiosity and the joy of solving problems using data. However, it's crucial to understand two key aspects before diving into analytics projects: the core problem and the audience.
Understand the Core Problem
Stakeholders often approach us with a proposed solution in mind (“I need data X”). By digging into the 'why' and understanding the core problem behind the request, we can choose a better approach that serves their needs, leading to better project outcomes.
Know your audience
We don’t want to find ourselves in a situation where our audience feels like we are speaking a foreign language to them. Executives haven't been along for the entire analytical journey that we went through. Thus, we need to translate our findings for them. Before crafting a communication:
Identify what's important to them and their current priorities.
Usually, this means strategic insights and actionable recommendations are preferred over details of the fancy ML algorithm you used for the project.What do we need to explain, and what do they already know?
Executives usually operate on a more abstract level and don’t necessarily know (and care) about each tiny detail of a process. Speak your audiences’ (domain) language! Explain acronyms, or don’t use them at all. Not everyone knows what an “ICP” (Ideal Customer Profile) is, and depending on the domain, it might even mean different things.How do we start our narrative to get folks excited?
Talking to the head of sales? If you start by telling them that this will give them insights on how to beat the competitor, you will have their attention.What is the best presentation format?
Each format has its pros and cons: A written document might be good for async communication, but folks will be “alone” while reading it. You cannot clarify things with your words compared to a live presentation where they can directly ask questions (but it might be hard to find an overlapping time slot with the executives). Be sure to be thoughtful about that.Assess your relationship and level of trust.
At Shopify, we used the concept of a trust battery. Make sure you know “how charged it is” - this will influence how folks perceive and hear you and how you need to adjust your communication.
Don’t try to communicate to too many people at once: If your audience is too broad, narrow it down to the decision-maker and tailor your communication to their needs.
Provide a concise summary (TL;DR) upfront and keep messages clear and direct.
Executives will love you when you start using TL;DRs.
They need quick access to essential insights to make informed decisions promptly. In the fast-paced world, they juggle multiple priorities and have limited time for detailed reports. This is where the concept of TL;DR (Too Long; Didn’t Read) becomes invaluable. I first learned about this concept while working at Shopify, where we used a similar approach to our communication (be it for presentations, reports, or even longer Slack messages).
How to Craft an Effective TL;DR
When crafting a powerful TL;DR, the focus should be on what is most relevant and important to the audience:
Summarize core findings and recommendations in a few sentences.
Use clear, straightforward language, avoiding jargon.
Use formatting to highlight key points with bullet points and bold text.
End with an actionable recommendation or provocative question.
Always position the TL;DR at the very beginning to capture the audience’s attention immediately.
Pro Tip: Add links to specific slides or sections with detailed data for those who want to dive deeper.
Example of a Well-Crafted TL;DR
Example: Improving Customer Service Response Times
Faster response times lead to higher customer satisfaction.
Implementing the new ticketing system reduced average response time by 50%.
Customer satisfaction scores increased by 20% after the change.
→ Recommendation: Expand the system to all customer service teams.
If you want to read more about TL;DRs, find some additional instructions in this article.
Time is Everything, and Less is More
As we learned in the TL;DR section, attention is a limited resource in our day-to-day world, and we need to fight for it. Here are some tips that have worked well for me in the past, along with good and bad examples.
1. Respect your Colleague's Time
Apart from using TL;DRs, make sure to use concise and direct communication. Avoid “bullshit” and unnecessary information (here is a good book on that topic), and aim to place your main message in the headline of your messages, slides, or report sections.
Use concise and direct communication. Avoid unnecessary information and place your main message in the headline.
Example: Slack Message
The 2nd message lets you parse the information quicker and decide whether it is relevant and you want to dig deeper (i.e., continue reading in the thread). There are a lot of great additional examples in the book “writing without bullshit” in case you want to read further.
2. Simplify slides and reports by reducing text and eliminating non-essential elements.
The above tips connect well with the next topic we are going to cover: Clutter.
In the Slack message example above, you saw a lot of additional information that did not support the message:
“I listened [...] on my Podcast Addict app […] I made 40km that day” → Your target audience will not care! Make a post in the #biking channel or tell your friends instead if you need to.
“It is like an hour long but I can totally recommend it to you” → If someone decides to check out the link, they will figure that out.
These are extreme examples, but we tend to add “clutter” to our presentations or reports as well. When was the last time you listened to a presentation and started thinking about something else since you could not follow all the information on that single slide? In those cases, the presenter lost your attention because of cognitive overload. Decluttering can help reduce the cognitive load for your audience and make it easier to parse your presentation or report.
Things you can start doing today:
Reduce the amount of text: When you give a presentation, your slides don’t necessarily need a lot of text. You can guide and explain verbally.
Challenge each element in your chart: Look at each of your axes, labels, data points, grid lines, etc., and ask yourself: Would eliminating this element change anything? If the answer is no, get rid of it.
Avoid gifs or animations: If they are not helpful for your message, avoid them. Our brains get distracted by such content very quickly. Only use it if there is a very good reason.
Here is an example of 2 charts that visualize the exact same data using different amounts of clutter:
I have no doubt that you will notice how much heavier the first chart feels. How long would it have taken you to extract the message? No executive will have time for that!
If you use a BI tool, you will usually find options to reduce clutter there.
Here is another example that uses Metabase. It mostly comes with reasonable defaults, but we can still tweak it a bit:
Labeling the bars directly and removing the y-axis ticks, makes the chart easier to process. Readers can directly compare the numbers for the jump in AOV (Average Order Value) without needing to jump back and forth between the axis and the bars. We also intentionally rounded the values to remove decimal precision since it is not needed for our message.
3. Apply colors consistently to create visual connections and highlight key points.
Colors are very powerful in our communication toolbox - if used wisely and consistently.
Make sure to be intentional about your use of color. One of my favorite examples is to use it for visual connections between slide titles and my charts, where I try to color a category I mention in the same way it would appear in the chart. Additionally, you can use black vs. gray color and bold vs. normal text to create a visual hierarchy. This helps guide the consumer through the content. Here is an example:
You see how the blue and orange colors connect to “increase” or “decrease” respectively. The hue makes the important parts stand out while we push other things to the background for context. This helps to reduce the cognitive load and allows your colleagues to process the content in a shorter time while increasing the chance that they perceive your message. This can also help across slides: If you stay with your color palette, your audience will quickly realize it, and it can be powerful to connect the dots with your previous story.
Let’s apply this to our Metabase example from above:
Adding a clear indication of when the Shop redesign happened, which led to the increased AOV, can help us make our story stand out.
4. Give clear, confident recommendations and use appendices for details
“Don’t caveat everything”
Once, an executive at Shopify told me that data scientists tend to caveat everything, and he often wished that folks were bolder about their recommendations. While it is natural for data professionals to want to highlight the nuances and limitations of our analysis, it is important to remember that executives are looking for clear, actionable insights. They prefer confident recommendations to make strategic decisions quickly over being walked through the details of your analysis.
Some examples:
Caveated Statement: "If the proposed customer retention strategy is implemented and the market response is favorable, we might see a potential decrease in customer churn by up to 5%."
Bold Statement: "Implementing the proposed customer retention strategy will decrease customer churn by 5%."
Caveated Statement: "While there are multiple factors to consider, and it’s possible that some variables might change, we believe that the new feature could potentially improve user engagement."
Bold Statement: "The new feature will improve user engagement."
You might argue that there are cases where it is important to add caveats. A good approach in those cases is to have an appendix and refer to it. This might give you more confidence, and executives will have the chance to dig deeper if needed.
Recap
Effective communication with executives requires thoughtful consideration of their time and needs. By understanding the problem and your audience, starting with a TL;DR, removing clutter, using colors wisely, and making bold statements, you can ensure your insights are understood and lead to actionable decisions.
Thanks, Thomas!
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Thanks for reading, everyone!
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Great article! And it mostly holds true in science papers and presentations as well. Caveats are a necessary evil in the scientific community, but the presentation of data is something that really is an art.