An introduction to telling data stories

Talk transcript

<Michael> Hi Everyone, nearly every day our team of workshop facilitators are engaged in a familiar conversation. A company or team leader is bringing us in to lead a training… and as we do our pre-workshop consultation – trying to learn some of their pain points and training hopes – we hear something to the effect of… “We have very smart and talented people, but their communication to leadership and our external stakeholders lacks clarity and focus. We need them to be concise and actionable.” 

<Kevin> This is important because good ideas, solutions to important problems, opportunities to make our organizations and our world better are languishing in data overload and a lack of clarity and relevance. Just last month I was working with a professional association of physicians….really smart people talking to really smart people. And yet their board of directors are saying, “Too much! Get to the point…quickly please”. In this case, not only is the influence of this organization at stake, but also the opportunity for doctors to offer better medical care to their patients. Many of us struggle to meet the needs of our audience by delivering the data story that empowers them to act. 

<Michael> That’s why telling data stories is a communication skill that can transform your influence as an advisor and leader. Kevin will talk about foundational story principles and I’ll share how to approach the visualization of your story. Together, we’ll talk about the power of telling data stories and how you can move from explore to explain.  

<Kevin> The simple truth is, facts aren’t as memorable as stories. Facts are important and we’re not suggesting this is a creative writing exercise where we just make up data to support a story we want or that our audience wants. But, and we all know this true, facts alone often don’t win the day. And they often lack the sticky-ness required to keep working on our audience… they can be forgettable and therefore their impact is short-lived. 

To begin, let me share a quote with you – from the noted data scientist, Maya Angelou: “People will forget what you said, people will forget what you did, but people will never forget how you made them feel.”

It may seem odd to share this quote in a talk about communicating data, but there is a lesson here. The decisions that you are asking people to make are more than just rational choices. Yes, you need to have outstanding data to support your recommendation, but ultimately you’re asking someone to change their mind, sacrifice resources, or move in a new direction. All of those decisions are emotional at their core. That’s why as data communicators we need to engage both the head and appropriately speak to the heart of stakeholders. 

I was talking to a Sr. VP at Salesforce ahead of training his team on DataStory and he said, “do you know that Maya Angelou quote about people forgetting what you tell them but always remembering how you made them feel”? He nearly jumped through the screen when I told him we open our DataStory workshop with that exact quote, he said, “That’s exactly what  we need. I want my team to make us feel why their data matters. Convince me it’s important.” He continued to plus-one almost every teaching point throughout the training.  

Why is this so important? Well, here’s a breaking news story… We have access to more information than any other time in history. And its just growing – IDC estimates a ten-fold increase by 2025 – around 175 ZB. Rarely do we suffer from the lack of data or information. But business leaders are suffering greatly from the lack of communicators who can quickly deliver transformative insights from the mass amounts of data we possess. 

So we have a lot of data… but why story? 

In the book, Made to Stick, Chip Heath conducted an experiment that tested memorability of facts vs. stories. Students gave a one-minute speech about crime using data he provided. Only one student in ten share the statistic as a story – they connected the stat to the meaning. The rest of the student simply shared the raw data as part of their speech. He then proceeded to distract the students with unrelated material….I believe he actually used Monty Python clips. 

Later, when students were asked to recall the speeches, 63% remember the stories. What would you guess was the percentage that remembered the statistics? Go ahead and throw your guess in the chat window. Only 5% remembered any individual statistic. This is important because statistics are analytical and they often make sense to us, but stories create meaning. Last summer, my wife and I traveled to Slovenia for vacation and we had dinner at Hisa Frankko. A two Michelin Star restaurant where the chef is Ana Ros, the 2017 Number One Female Chef in the World. 

Now, if I were trying to convince you that dinner at this restaurant alone would be reason enough to book a vacation to Slovenia I could share with you the menu of the 23 courses we experienced. You could read all about cauliflower and black truffle, creamy smoked trout roe beignets, and spring salad with lacto-fermented tomato water. And perhaps the foodiest foodie among us might be intrigued, even excited, but no one is making travel plans based on reading a menu. 

Or, I can tell you about walking up to this incredible farm house, that is not only Ana’s restaurant and personal residence, but also a little 10-room B&B so you can stay the night after your dinner and enjoy breakfast in the morning. Our evening began with apertivo in the meadow, overlooking the Alps as the sun was setting. And then we were seated in the dining room and for the next 3 hours, we were hosted to the most incredible culinary experience we’ve ever had. 

To say each course was better than the previous would be mistaken. Each course was like viewing a different masterpiece in the Louvre, impossible to rank, just spectacular to partake. When I say beignet, you may think New Orleans, but I promise you will never think that way again after this cottage cheese and smoked salmon roe beignet. By the way, I hate cottage cheese and smoked salmon roe… but this was something amazing. 

Lacto-fermented tomato water? Are you kidding me? This is the water they collected from the tomatoes they canned the previous year, they saved it and put it through a fermentation process that I didn’t understand for a second, but it made a spring salad taste like an imaginary nectar from heaven. I could go on and on about the food, the setting, the after-dinner cheeseboard on the patio, the unbelievably quaint room with the serenade of the quiet countryside, breakfast in the morning and more. 

Now I tell you this story—not only to make your green with envy—but to illustrate the simple truth… Information is not the same as story. There are times that your audience simply needs the information you possess. Give it to them. If someone wants to know what we ate at Hisa Frankko there’s no simpler solution than giving them the menu. Some meetings and conversations are about spreadsheets and system architecture, that’s OK… it’s more than OK, it’s what’s best for that communication need. But often, information alone doesn’t convince or persuade our audience to act. Story is what allows our audience to begin to imagine a different solution, a better situation. You have the information to support a course of action, but story provides the appropriate and necessary emotional context for that information to be persuasive. Story is a core tool that can be used to move from simply exploring the data, to explaining it. 

Many of us aspire to increase our influence and value within our roles and companies. There is a decreasing need for specialists who ONLY explore and mine the available data and then pass that treasure on to someone else who will use it to explain the business situation and recommend a solution to a who leader who then inspires the necessary change. 

In 2018, using their Talent Insights tool, LinkedIn identified the skills gap between the skills job-seekers had and what employers were looking to hire. In our ever increasing data driven world, it is written and oral communication skills that are in most demand. We need great data exploration, and technology will continue to assist and expand the boundaries of data available to us. But the opportunity for increased influence and value belongs to those who can create compelling communication, explaining what has been explored and making clear, actionable recommendations to leadership. 

There is a great chasm between this Explore and Explain skill set. We call it a “communi-chasm”. The ability to bridge this gap is how business communicators increase their value and influence. The challenge is that many of the skills that make us great explorers, often betray us when it comes to explaining. EXPLORE is an analytical process that seeks to prove a point:  

Explaining is a creative process that moves others to action. It takes a different mindset or framework to craft a story from data. We need to learn how to wear both an analytical hat and a creative hat. The CEO of the physicians org from last month said it perfectly at the end of our workshop, he said he needed to unlearn how he’d been trained to communicate as a researcher because it was limiting his ability to drive action. Wow! We fear we might look silly or even too simplistic if we wear both an analytical and creative hat, but the truth is, the new data communication style is just that, an artful blend of analytical/creative thinking. 

In the four years I’ve been teaching this material, two things stand out to me about this process. First, the resonance with execs and senior leaders. I’m not exaggerating, every time one of these key leaders is in the room, they are interrupting to plus-one or double down on a concept I’m teaching. They are longing for succinct, actionable, data-informed recommendations from their team members. 

My second observation is how much fear and hesitancy there is from the team members to adopt this approach. There is a reluctance to have a point of view because it might be wrong. There is a fear of questions or challenges from decision makers, so communicators include all possible data that will address every possible question that might ever emerge. There is an insecurity that reveals itself by wanting to demonstrate how hard I’ve worked and how smart I am, so I’m going to show you the minutia and take you into my trenches so you can be impressed and realize you need me….even if you don’t understand me, you need me. 

Telling great data stories is a skill leaders are clamoring for, and for many team members, traversing that communi-chasm from Explore to Explain is a daunting and threatening journey. It takes courage to move from data to action. So let me give you 2 steps you can do to strengthen your resolve and turn up the heat on these power skills. Let’s start with understanding decision makers—these might be senior leaders, executives or other decision makers with whom you share your recommendations. 

Start with empathy. 

Empathy is imagination for the sake of understanding someone else. Why is this important? Even though you are confident in your recommendation, when it’s time to communicate the recommendation, you need to consider your decision makers. Empathy is the core DNA of everything we do here at Duarte. For 30+ years we’ve been putting the audience front and center of all our communication design. This is especially true in data communication where there is often an underlying temptation to impress, and maybe even overwhelm the audience with the complexity and insight we have from our data.  

Empathy calls us to answer the question, “how simple can I make this?” Not simplistic, but making our insights easily accessible so decision makers can quickly leverage the power of this data to make strategic decisions. This fear of being perceived as simplistic is what prohibits many communicators from crossing the chasm of explore to explain. 

So if we’re trying to meet the needs of key decision-makers, what do these executives need? What drives execs? What keeps them up at night? Go ahead and type in the chat window, what are some of the primary concerns of senior leaders and executives. From asking this question countless times, especially of senior executives themselves, we’ve identified three main areas of focus: Money, market, and exposure. These are the primary three things execs are measured on. They want to drive up revenue and profits, market share, and retention… and by retention I mean retention of market share, retention of talent… anything to avoid churn. 

And they want to drive down costs, time to market, and risk. If you find you are being ignored or dismissed by the key decision makers you are talking to, it’s likely because you’re not talking about something they care about. Too often we’re trying to draw their attention and decision-making focus over to our agenda. It is on us, the data communicator, to frame our conversation about the things that matter to them. Knowing how your idea connects to one of these themes is imperative to empathetic communication. 

In addition to understanding your audience or decision-maker, I want to encourage you to leverage Story Thinking to craft a compelling summary. This idea of Story Thinking can be intimidating to many of us. We don’t see ourselves as a storyteller, at least not a good storyteller. Sure, we love story and we marvel at people who seem to use it masterfully in their business communication, but I don’t have that special gift or creativity. The good news is that there is a structure to story. This is good news because if there is a structure, that means an analytical person can utilize that structure to create a compelling story. 

Aristotle’s poetics stated that stories have a three-act structure. And even our data communication can benefit from this story structure. And those three acts have a clear beginning, middle and end. This is beautifully simple and beautifully profound. What this means is that everything you and I share with our audience belongs somewhere, it has a role to play. 

• Beginning: a situation happens that creates a problem….or an opportunity. 
• Middle: it’s messy to solve and gets complicated (we call this the messy middle). 
• End: ultimately, there’s a resolution. 
  

This structure is powerful because it can expand and contract to be what we need it to be. It can be as simple as 3 sentences and we can craft a story that is only a paragraph… an executive summary. 

It can expand to be a 30-minute meeting, where we take our audience on a journey of transformation. Or it can expand to something much more complex, like the 10+ hours of the unedited Lord of the Rings movies, but at the core we still have a very simple 3-Act Structure:

• Act I – A magical ring is discovered that must be returned to fires of Mordor.  
• Act II – An unlikely fellowship encounters vast trials in the quest to return the ring. 
• Act III – Ultimately Frodo the Hobbit achieves the heroic feat and saves middle earth from destruction. 

This structure is powerful. Let me show you an example of a summary from the hospitality industry. 

• We start off with a problem – Revenue from conferences is down, and the hotel lost $1.2M last quarter. 
• AND it’s complicated – A new hotel opened flexible meetings spaces and was awarded the last six conferences. 
• So, Act III we have our recommendation – We need to invest $120M to upgrade our aging conference center, or out event business will continue to decline. 
  

Act I and II create the context for Act III to make sense. Without the first two acts, our recommendation just stands out there on it’s own. If I come into the board mtg and say, “We need to invest $120M to upgrade our aging conference center”, the board might simply say, this isn’t a capital issue, it’s a Sales problem. Hire better sales people. 

But by framing my summary as a story, I’m providing the context for why this absolutely is a capital issue. The board may still disagree with my recommendation, but they cannot ignore that fact that our aging facility is directly contributing to a loss of revenue. I get asked all the time, “This sounds great, but where does my data come in?” This entire story structure for a recommendation is driven by  your data. Data reveals there is a problem or opportunity. And there is data that reveals why it’s complicated.  

So our recommendation, informed by data, leads to a solution. All three acts are necessary. Each one is informed and supported by data that you have explored. Two common mistake we see are first, just Act I and III….Problem—Solution. What this lacks is the drama of Act II. The fact is that if it really was a simple problem-solution scenario, a story wouldn’t be needed to persuade the audience. The building is on fire. The exit is this way. No story needed. But most of the time it’s much messier than that, and that’s where Act II comes in… it reveals the drama that is already present in the situation. 

The other mistake we often see is just Act II. Basically the presentation is all about the mess and complications and challenges and drama and no real solution is offered, just drama. This is also not helpful. Again, Act I and II create the necessary context for your solution, Act III to land and make sense. Since Act III is what it’s all about let’s make sure you have the killer ending your audience needs. Act III is what we call your Big Idea. A Big Idea has two components. Your POV, which is you recommendation. But we have to make sure we also have… the stakes… what are the consequences of action or inaction on your POV. The stakes is what energizes your ending and puts right in front of your audience why they must consider your recommendation. 

Looking at our hospitality example, the POV is we need to invest $120M to upgrade our aging conference center… That is what we’re recommending to the Board. And the stakes are reversing the decline of our event business. The stakes are what make your recommendation un-ignorable… it’s the reason your decision maker has to consider your recommendation. 

The executive summary is your first interaction with your audience. The leader’s decision to continue reading your recommendation or engaging with your presentation depends on the impression your executive summary gives. A great summary solicits the response, “prove it” or “show me”. And that’s exactly what you do with the rest of your story, but now you do so with their full attention. 

You rarely win the day with the exec summary alone, but I often call it the 30 seconds that buys you the 30-minute meeting. That’s why crafting the summary with story thinking is so important, it makes your recommendation un-ignorable to your audience.  

So I’ve just cracked open the door on how to be a compelling communicator of data rich content. Empathy for your audience and Story Thinking are essential building blocks. Michael is going to unpack a bit more in the rest of this session with some focus on how to be visually compelling with data. Let me leave you with this statement by Clive Benford from Jaguar Land Rover. “The value of data is existential, it’s the existence of your business. If you don’t become a data driven business, I don’t think you’ll be here in 20 years time.” The skill development around data communication has already moved from “a nice to have” to one of the most sought after skills in the marketplace. Benford believes it will continue to evolve into an existential capability. Are you ready to thrive moving forward? Thank you. 

<Michael> Kevin just provided the foundation for you to craft your data story—with that, you’re off to a great start. But a common question we hear is, How do I even find the story in the data? For many, this isn’t intuitive. After all, data is logical. It’s analytical. And while it’s structured, Story is creative. To become a storyteller for your data, it’s helpful to understand what your data wishes you knew. Let’s take a look at the day in the life of a data slide. 

You may have heard people say “the data speaks for itself.” Perhaps you’ve said that. This is typically said in support of putting L O A D S of data on slides. Let’s be clear. All of that data has a voice. It has something to say, BUT… it doesn’t speak for itself. Remember, it needs storyteller. It needs you. And as you heard, we are inundated with data to the tune of 175ZB of projected worldwide data by the year 2025. New sources of data emerge, new data streams spring up, and new reports come out every moment. 

There is so much data available that it’s hard to hear the voice of the data above the noise of the data. It’s being overwhelmed by exponential growth. As communicators, it’s easy for us to feel overwhelmed as well. This ever-growing sea of data threatens to drown us in analysis. Each new data point demands that we both understand it and use it to drive strategy.  

Our credibility seems to be on-the-line so we feel compelled to not only show the complexity of our data, but to also show the depth of our analysis. We hide behind our data. We’ve become numb to the very goal we set out to achieve—to solve a business problem through exploration. To tell an effective data story, you need to tune into the voice of your data. Data may seem cold—after all, it’s logical.  

We use it to “make sense” but your data yearns to “make meaning.” 

You need to learn to speak for your data. To become a story whisperer for your data. It may seem impossible, but with the help of a few pointers, you can continue the process of moving from explore to explain. And it starts at the most intuitive place. You analyze the data and make observations. It is through observations, that the narrative is revealed. 

Listen to your data, it will reveal what it wants to say. As you explore your data, seek the insights. This is a critical transition from analysis to communication. From analyzing the data, to explaining the insights. Making observations is a normal behavior. As you experience something—you react… and you note your reactions. I’m willing to be that many of you already make data observations without even realizing you are doing so… Let me give you an example. Rather than simply gulping down a glass of fine wine, you take a moment and appreciate the wine’s color—maybe it’s a dark ruby or almost purple color. That’s an observation. 

Then you’ll appreciate its aroma. And with each aspect of the fragrance, associated memories come forth—you may get hints of black cherry, vanilla, cinnamon and other spices. Those are observations.  Then you take a sip and experience the palate as tastes explode on your tongue. You might still get that black cherry, but now its joined by oak notes and baking spices, savory autumn leaf, cedar and even leather. This is data analysis.  

You consume the data (your experience as you taste the wine) and you make observations (your description of the experience). And if you are curious, I just shared an excerpt of the tasting notes for a 2018 Justin Isosceles. I’ll have to make some of my own observations on that wine, but I’m pretty sure I’ll enjoy the analysis. Like wine tasting has a vocabulary, you need to develop your own vocabulary around data observations. Be critical of the data for sure. But also be curious. Does the data affirm or challenge your assumptions? As you capture your insights do new questions emerge? Having a POV about the data is essential to having the data play a role in your story. That POV emerges from observations. 

This is a chart from an early version of a report we published back in 2021. In this case its survey results for “Preferred Presentation Lengths.” For me, I like to make observations by first looking at the extremes—the largest and smallest data points. Here, I’ve circled the largest values in each bar. You can start to see a shift in preferred lengths depending on the level of interaction. And here, I’ve circled the smallest values in each bar. This is mostly as expected. But look at this value down here. There is a flip of preferred presentation length when you increase interaction. For highly interactive presentations, the least preferred length is between 0-15 minutes. We actually like to be in presentations that are engaging and are OK with them being longer. 

Now from those highlights, larger observations emerge presentations with little to no interactions should be kept short! Under 30 minutes. And, presentations with high interaction and collaboration can be longer to account for the needed time to connect. About 60 minutes or less. While this interesting… for me, new questions start to emerge… like “how long is a standard online meeting?” I’ll come back to this in a moment. 

Making observations allows your data to shine and that brings me to me next point. Stars will emerge. These are the data points that absolutely must be known to your audience. And you need to let them shine—to be seen by your audience. Remember, your data doesn’t speak for itself, and the stars need more than just your voice. They need to be on display for all to see. Data, along with insights provides guidance on what must be on display… And a guiding principle in our courses is to “highlight what’s important” this is even more critical when it comes to data. 

Remember that study Kevin sighted earlier? People tend to only remember 5% of the stats you share. But when you make meaning, that jumps to 63%! We can support and even emphasize the meaning, by highlighting the data. Here’s a simple chart and title—“Annual Sales.” By only plotting the data,  I’m leaving analysis up to the audience. And while this is not a complex chart, I’m essentially asking you to do some work to process this data. It’s empathetic to your audience to guide them to the key insights and observations. It makes it easier for them to follow your line of thinking. 

To highlight what’s important, the first step is to minimize the noise. For this chart, we’ve…  

• Removed the grid lines. 
• Removed the Y-axis since the values are associated with each bar. 
• And we are using a neutral color for the text and other elements – a lighter gray on our white background. 
  

With the chart noise minimized, we can focus on our insight. To show that our Q3 marketing campaign was successful. Highlighting your primary information and keeping your secondary information in a neutral shade draws attention to the most important point. In this example, it’s clear we are focused on sales in Q4. We even annotated the chart by adding a label that calculated additional math. This makes the point easy to understand. Sales increased 140% from Q3 to Q4. And now, the chart and annotation fully support the insight that our Q3 marketing campaign was successful. 

Let’s return to our Preferred Presentation Lengths data… I’ll focus on just the right two bars. In its current format, it takes some effort to make sense of this chart. There is a lot going on here. One thing we CAN do… is to choose a different format for the data display. In this case, we’ve used a variation of a bar chart—a fancy Histogram to show preferences for presentation length. The fatter the “bar” the greater the preferences within those time frames. 

Here is an observation from the data: “An engaged audience will give you more of their time.” And to add to the understanding, we’ve annotated the data as well. This allows you to clearly see our sweet spot—between 31-60 minutes. That’s the power of letting the stars emerge. And that brings me to my third tip… Data reveals data. I’m sure you’ve experienced this when conducting your own research… 

Analysis often highlights the need for more data. Either data that already exists in some form, or data that needs to be mined. 

A single, compelling stat is fantastic… but when accompanied by additional supporting stats, it can become substantial. As you continue to listen to your data, what holes do you find in your analysis? Those holes are often a cry for additional analysis. Having a greater context for your data can help drive your thought process. This can lead to a better understanding of the problem and a greater chance of overcoming that problem. It’s OK to admit that you don’t have enough data to make a 100% confident recommendation. 

In this simple example, the story hasn’t emerged yet. The bar chart highlights customers who range from satisfied to very satisfied within these five categories. Based on the existing data, I don’t know if this observation is accurate. Looking at the final two bars, I don’t see a positive story. The key word in the observation is “Improved”—it indicates a change, a transformation for our customer satisfaction numbers. But, the chart only shows one data point for each category. It’s a snapshot of the current results and doesn‘t show change. We need historical data to support the observation. Adding the previous year, provides comparison data and now visually supports the observation. We can see that, while low, our satisfaction rating for credit approval has indeed improved. 

Let’s look at our Preferred Presentation Length slide one more time… You may recall that during my original analysis, a question came up—How long is a typical online meeting? It turns out that in 2021, the average Zoom meeting was 54 minutes long. My guess is that this would be the same for other platforms as well. Adding this bit of information, it helps us better understand the challenges we face with virtual presentations. It’s safe to say, that most of those 54-minute long meetings weren’t highly interactive. 

While seeking more data can helpful, it’s also OK to be brave. To be willing to take a stand. There is always the possibility to do further research and analysis, it’s just not always beneficial. If you are like me, this obstacle happens all the time when I am deciding on which “thing” to purchase—like a laptop, new camera, a car, which software to buy, etc. I don’t want to make a bad choice, so I’ll sometimes spend hours watching videos, reading reviews, and looking for testimonials. While there is wisdom in doing the research, it often drags on and on and on… 

At times, you need to take a stand and trust your recommendation to avoid getting stuck in analysis paralysis. How many times have you been stuck analyzing data because your data set wasn’t 100% complete? Maybe you weren’t 100% confident in your answer? Those are the times to be bold and trust your data. Let it take center stage and then speak to the insights it reveals. It’s easy to get stuck on this… and it’s why I love this quote from John Tukey—an American mathematician credited with coining the term ‘bit’ and the first published use of the word software. There’s a little trivia nugget for you. 

He said, “An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.”  

It’s OK to live in the “unknown” and to trust that we have enough information to make a good decision. And it’s a great reminder to be attentive to the business need… are we solving the right problem? Finally, remember that to be truly impactful, your data needs to be memorable. You need to make it sticky. Having well-crafted data slides that showcase your data “stars” is important for your story— that is empathetic after all—but it’s not the only way to tell the story of your data. There are times when you need to break out of the chart. And highlight those important data points. Help your audience “marvel at the magnitude” of your data. 

This is particularly important when you are sharing very large numbers or incredibly small numbers. For instance, I just read an interesting bit of trivia in the book Making Numbers Count. Did you know that you need to walk up two flights of stairs to burn the calories from a single M&M? Taking this further, there are about 20 m&ms in a fun size pack, the kind you might pass around on Halloween. If you ate those 20 M&Ms, it would require walking up 40 flights of stairs to burn those calories, or nearly half way up the Empire State Building.  

Let me share another example. This time for something larger than an M&M… There are certain numbers that are thrown around because they are simply enormous despite the fact that very few of us can fathom the size of those numbers. One example is around federal budgets. It’s common to hear leaders talk about budgets and deficits. They may throw around numbers in the trillions of dollars. It sounds impressively large, but have you ever stopped to think just how big ONE TRILLION dollars is?  

To help you understand, let me compare $1T to this – a football.  <holds up football to camera>

If you watched the Super Bowl this past weekend, you have a sense for the size of a standard American football field. Counting the end zones, it’s 360 feet long by 160 feet wide -or- for audience members from outside of the US, about 109.7 meters by 48.7 meters. It’s a big space. Using this as a reference, let’s see how big $1T really is… We worked with a client several years ago who needed to visually convey the size of $1T to help their audience understand the conversation around federal budgets. To help, we started by creating a “unit” for measuring the size of $1M. 

If you take a standard 4×4 shipping pallet, something you might find behind a store or office building, and then stack it about 4’ high with $1 bills, that gets you to one million dollars. So we have our unit of measurement. What would a billion dollars on pallets look like? To answer that question, let’s go back to our football field, you’d have to cover about a quarter of that field in shipping pallets to get to $1B. That’s a lot of pallets. How many football fields do you think you have to completely cover in pallets to get to one trillion dollars? You would have to completely cover 217 football fields in pallets to equal $1T. 

Just by translating a massive, incomprehensible number like one trillion into terms we can comprehend, like pallets and football fields, we get a better sense of just how huge a trillion is. That’s the power of making data sticky. As we wrap up our time, it’s easy to get lost in the amount of information shared just over the last 20 minutes, let alone all the data you need for your work. Just remember that data has a voice, but it doesn’t speak for itself. 

However, if you are willing to be courageous and listen to your data… the observations will reveal the narrative, your data stars will emerge, you’ll know when more data is necessary and when you need to take a stand. You’ll even be able to make your data memorable. And you’ll come to realize that you are that storyteller your data so desperately needs. 

Give the data its voice and let it play a powerful role in transforming the people and companies you lead. 

Thank you.