what’s the story behind my KPIs?

Through virtual and in-person workshops around the globe, we have taught tens of thousands of people how to communicate effectively with data. This series captures some of the noteworthy questions we hear during those sessions—and our answers.

I’m designing a dashboard that will contain key performance indicators (KPIs). How do I know what the story will be behind them? 

This question piqued my interest, as I have an extensive background in reporting. Key Performance Indicators (usually shortened to “KPIs”) are an essential part of any business, but they don’t appear fully-formed from thin air. There is a process involved in developing and building KPIs, and it’s only once a KPI is in production that it can (potentially) be a useful tool for finding insights. Those insights may eventually become part of a story, but we can’t know what that story is before the KPIs are created in the first place. 

So, to answer this question as fully as possible, let’s dive a bit deeper into the process of building a KPI from the ground up.

What is a KPI?

The term “Key Performance Indicator (KPI)” is commonly used to describe a metric that provides a view into performance. KPIs can:

  • provide targets for teams to strive for; 

  • set milestones to gauge progress; and 

  • offer insights that help people across the organisation make better decisions.

A KPI’s journey begins with the request to create it, usually from a colleague who is looking to track an important element of their business.

If you are the dashboard designer, then this is the time to gather as much information as possible about the goal of the KPI. This will likely mean conversations with the requester to identify their specific needs. Understanding these requirements fully will also make the process of creating the KPI more efficient.

Building a KPI

Once those requirements are fully understood it’s time to begin gathering the data needed for the KPI. At this point, many factors need to be considered. For instance:

  • Is historic data required in order to provide a trend? 

  • If there is a goal, is it constant or changing over time? 

  • Do run rates (the average amount achieved to date) and required run rates (how much needs to be delivered in the remaining time) need to be calculated? 

  • Is there a projected value or forecast to consider?  

With KPIs often being part of regular reporting, getting the data structure correct at this point (with an added bonus of being able to automate it) will avoid the need for arduous repetition in the future. Indeed, creating a KPI will require many of the skills an analyst possesses.  Sourcing data, cleaning, structuring, designing, and creating the final output are all required. Significant time is often spent in these various phases. 

Publishing, reviewing, and maintaining a KPI

Finally, the big day arrives, and the KPI is published…but it still isn’t providing a story behind what it's showing. That's where you come in!

It's at this point that a critical (and often overlooked) element of analysis comes in: explaining the KPI. What is this metric telling us? What recommendations or actions should be proposed? This part is important to include, even in a regular report or dashboard.

Once the KPI is live, plan time into the production process to review the output, and to explain the data to an audience seeing it for the first time. It's tempting to fall into the habit of publishing regular content without providing an explanation of what it's showing. As a minimum, allocate time to take note of two or three key points of interest to your audience.

Yes, it's possible your audience will view these metrics for themselves.  “Self-serve reporting” has become a buzzword in recent times, and while it does enable direct and the benefit of faster access to information, consistency across teams with “one single truth” and increased capacity for the technical teams, audiences seeking their own answers do run the risk of making incorrect assumptions. You will likely know the data better than most, so use that knowledge to educate them.

As your products mature and become familiar and commonly used, spend time reviewing KPIs to ensure they remain relevant.  I have built many KPIs that were deemed crucial at the beginning of a performance year. Attention was paid; action-oriented discussions were held; and yet, these meetings, over time, became stale as the KPIs lost their relevance. Priorities change frequently in any business.  Ensure KPIs and accompanying reports are as agile.

In summary, while we don’t know what the stories are going to be behind our KPIs before they are built. By seeking input before and during development to understand the motivations behind them and then, once they are live, spending time reviewing them we can explain those outputs and bring them to life for our audience.

Check out these additional resources for more on ways to help explain your data:

when should I use a map?

Through virtual and in-person workshops around the globe, we have taught tens of thousands of people how to communicate effectively with data. This series captures some of the noteworthy questions we hear during those sessions—and our answers.

When should I use a map to show data by region?

People seem to love maps. I’m sure I’m not the only one who had maps on their walls as a kid. Something about the aesthetic of a map—any map—draws us in, invites us to explore, encourages us to find ourselves in the visual, and spurs ever-deepening investigations into finer and finer levels of detail.

As a Gen-Xer, the maps I grew up with probably feel a bit archaic these days: physical globes; road atlases; automobile-club-produced customized journey flipbooks, bound and highlighted by a travel agent; and later on, computer printouts of MapQuest directions. Today, our phones make the experience of finding our destination, our areas of interest, or ourselves on a map a seamless and ubiquitous part of navigating the world. 

That ubiquity has given all of us an increased familiarity with maps, as well as a deeper affinity for them. (Probably a dependence as well!) It’s natural, then, to want to use a map to visualize data that has a geographic dimension. Why not, right? There is an obvious upside: audiences are drawn to the way they look, as it’s a more memorable image than the same old bar chart or line graph. Not to mention: it’s fun to make maps!

The problem is that maps look interesting, but their very nature limits our options for visualizing data within them. Per a recent paper by Franconeri, Padilla, Shaw, et. al., here are a couple of the comparisons that people are very good at making, perceptually:

  • Position (is something higher than something else on the screen, or farther to one side?)

  • Length or relative distance (is one thing longer than something else, or is one pair of things farther apart than another pair of things?)

…and here are a couple of comparisons we are NOT good at making:

  • Area (the relative size of circles, or comparing how two dimensions change simultaneously)

  • Intensity (how much bolder or more-faded-out is one color than another)

Think about what a map, inherently, is: an abstract representation of the position, relative distances, and areas of geographic regions. That means that a map already is taking up both of the visual comparisons we are good at making (position and length) AND another one that we’re not great at (area).

What in the world do we do when we want to overlay data onto a map? Our options are pretty limited.

  • We can apply a heatmap to the regions in our map—leveraging a color’s intensity, which we aren’t good at making fine distinctions about; or

  • We can plot a secondary layer of points on top of our base map, and then size those points by the value of the data we’re representing. This still means that we are using the points’ areas, a less-than-optimal dimension, to depict our data.

Given these challenges, we should limit our use of maps to those cases when the values being visualized have some specific correlation with the geographic locations of the items in the data set.

For instance, the type of weather you experience is 100% correlated to your geographic location, so a map is a great choice for visualizing this type of data.

This choropleth map shows the number of tornado watches U.S. counties have experienced in 2022, as of late May. Weather- or climate-based maps, like this one, are excellent use cases for showing data geographically, since physical location is inherently related to the measured and visualized information.

On the other hand, the total payrolls of the 30 teams in Major League Baseball would be a poor data set to visualize on a map. Even though each team has a physical, geographic location, the specific payroll a team spends is dependent on many other factors. Even if we were to try to use a map for this data, we’d have to use area (by sizing each team’s circle appropriately) to show the differences in payroll; once I add in a few colors to categorize teams by their respective leagues and divisions…well, see for yourself:

A map is a poor choice for visualizing the total payroll of the 30 teams in Major League Baseball. Physical location is a small part of what drives payroll, and the loss in readability isn't worth the gains from visualizing each team's location.

A map is a poor choice for visualizing the total payroll of the 30 teams in Major League Baseball. Physical location is a small part of what drives payroll, and the loss in readability isn't worth the gains from visualizing each team's location.

With data like this, you’d be better off visualizing with, yes, the boring old bar chart:

With a bar chart, comparisons within divisions, across divisions, and across all of MLB are easier to see. Even though we’ve retained color from the original map—not the most effective use of hue—the data itself is much clearer for a reader.

With a bar chart, comparisons within divisions, across divisions, and across all of MLB are easier to see. Even though we’ve retained color from the original map—not the most effective use of hue—the data itself is much clearer for a reader.

Any organization with multiple offices, branches, regions, or stores will face these kinds of visualization choices frequently. Especially as our tools make it easier and easier to create maps on the fly, it’s worth pausing to consider: does the data I’m analyzing depend on the specific locations of my offices, branches, or stores? Are there insights that are only going to emerge if I visualize their specific geographic position? If so, then give maps a shot—otherwise, stick with a simpler chart type that’s likely to communicate your key messages as effectively as possible.


This only scratches the surface of what maps can, and can’t, do. (For instance: we didn’t even touch on electoral maps, cartograms, or misleading map projections.) Check out our recent podcast episode with Kenneth Field, the author of Cartography, for a more in-depth discussion; and look through the 58 submissions our community members created during our March MAPness challenge last year.

I have to deliver the same presentation over and over again. how do i keep from getting bored?

Through virtual and in-person workshops around the globe, we have taught tens of thousands of people how to communicate effectively with data. This series captures some of the noteworthy questions we hear during those sessions—and our answers.

In my role supporting our corporate leadership team, I often need to build one presentation, and then deliver it over and over again as I bring it to various local and regional offices. How do I keep myself from getting bored when I have to tell essentially the same story 5, 10, or 20 times in a row?

A woman sitting in front of her open laptop is bored, possibly because this is the 100th time she's had to deliver the same presentation.

Anyone who has to share the same communication multiple times is going to struggle with this challenge. For a presentation to be effective and compelling, we as storytellers have to be engaged with it, and it’s natural to find that an easier task when the story is fresh to us, versus when we’ve delivered it dozens of times. 

There are a few techniques to use that we’ve found effective in keeping us present, focused, and compelling to an audience, even when telling a story that we’ve told many times before.

1. Since every audience is unique, every presentation will be unique as well.

If you are delivering a communication to a dozen different local or regional offices, each one of those offices is going to have a different set of local competitors, a different set of circumstances, or a unique composition of team members. Because of this, even if 80–90% of your presentation is the same every time, there will still be 10–20% that is distinctly, specifically relevant for each specific audience. (Ideally, you would have a few slides in every presentation that are customized for that day’s session.) That custom content will keep you engaged as you prepare the presentation, and will help to make the overall story more meaningful to your audience as you deliver it.

But even if the slide deck, for whatever reason, stayed exactly the same, it’s unlikely (if not impossible) that any two presentations would ever be exactly the same. How the content is framed, what parts of the story are more meaningful, the nature and volume of questions the audience will have, and the level of detail you share are all dependent on the specific group with which you’ll be speaking. Staying attuned to what your audience is telling you—verbally and nonverbally—while you’re presenting will help keep you from going on autopilot.

2. For the audience, this is Opening Night.

You might have delivered this same message 100 times before to 100 different offices; but for the people in front of you, it is their first time hearing the presentation. Stage actors might be called on to do 9 shows a week for months on end, but they can’t just phone it in or not give their best every time; their job is to provide a great experience for the theatergoers in the crowd who will only ever see one performance. 

If anything, your past experience of giving a similar presentation will make you even more prepared to adjust to your audiences’ specific needs and interests on the fly. Your command of the prepared material will make you more confident and capable to handle whatever questions they might have; by the 20th presentation, it’s likely that you have heard (and answered) most of the common inquiries before, and you’ll have more headspace and enthusiasm to handle the unusual or challenging ones.

3. You are not the audience.

Resist the temptation to make changes just to keep yourself entertained. Your slides don’t need new graphics, or a new template, or different graphs, just because you’re tired of looking at them over and over again. 

Revising your work is certainly justifiable in some cases: if you see that certain sections of the presentation aren’t resonating well with most audiences, and you know you can improve them, then you’d be remiss not to iterate. 

However, making changes just for the sake of making changes is ill-advised. I found that when I would go down that path, it rarely made the communication better…at best, it would simply make it different, at the cost of a lot more effort. It was usually a warning sign that I was losing sight of the audience, and instead focusing on keeping myself entertained. It’s a clear case of misplaced priorities when we start to value the presenter’s amusement over the audience’s engagement.  


How do you keep your presentations from getting stale if you have to deliver them multiple times? Join the discussion in the SWD community, and let us know your tips and tricks!



what tool did you use, and what do you suggest we use?

Through virtual and in-person workshops around the globe, we have taught tens of thousands of people how to communicate effectively with data. This series captures some of the noteworthy questions we hear during those sessions—and our answers.

you asked...

Your charts always look so clean and well designed.  Which tool do you use to build them and what tools would you recommend?

Although my colleagues and I have used a wide range of tools before, and during, our time at storytelling with data, we most often use Excel and/or PowerPoint for our client work, leveraging the latter to pull our workshop presentations together.

In some ways, the choice of which tool to use has already been made for us: Excel is simply so ubiquitous in business today, chances are high that our SWD audiences have at least some experience with it. But Excel has a few other things going for it besides “everyone already has it:”

  • Community - There are online Excel blogs, tutorials, videos, and courses available to suit all levels of proficiency.  Very rarely is there a question or challenge that can’t be solved by searching the internet.  Indeed, our own community has provided a number of resources

  • Flexibility - Most common chart types are easily built in Excel. With a little creativity (and, on occasion, brute force techniques), you can bend Excel to your will in terms of formatting.

  • Simplicity - Our goal is to communicate effectively with our audience ,and often this requires our visualisations to be simple.  Excel allows this. It shows that good stories can be told using available tools.

Does that mean YOU have to use Excel? Of course not. There are many different options for visualising your data, as folks in our community have demonstrated. We’ve seen excercises and challenges built in Excel, Tableau, PowerBI, Flourish, D3, R, and loads of other applications. Any or all of these tools, in certain scenarios, might work best for you; the only way to know for sure is to give them a try. It’s important to not let unfamiliarity with a tool (or a blind devotion to one) become a limiting factor when it comes to communicating effectively with data.

There’s no wrong way to start experimenting with visualization software. Some folks find courses and tutorials are a good way to explore and understand the basics; others feel there is no better substitute to properly learning a tool than diving in and getting “hands-on,” experiencing the struggle to achieve an end result, and feeling the satisfaction of accomplishment on their own. 

While we can’t offer any blanket recommendations when an organization is looking into acquiring or upgrading their visualization tools, we do suggest asking a few questions to help decision makers in that process:

  • Does the tool provide the chart and graph types to meet the business needs and show the right types of analysis? 

  • Does the tool have the capacity to store and analyze the volume of data your organisation possesses?

  • Do reports need to be automated or consumed in a self serve way?

  • What is the learning curve for the tool? How easy are the tools to use both from the perspective of the creator to build and the audience to understand?

  • What is our appetite for the logistics of acquiring and implementing this tool, in terms of cost, ease of integration, and maintenance?

Curious about what is possible to accomplish in various visualization packages? Check out these additional resources to see what our SWD community members have created:

what’s the right amount of detail to include in a single visualization?

Through virtual and in-person workshops around the globe, we have taught tens of thousands of people how to communicate effectively with data. This series captures some of the noteworthy questions we hear during those sessions—and our answers.

you asked...

How do I know how much detail to include in my slides? I want to make sure the context of the communication is clear, but I don’t want my visuals to feel cluttered, or to have so much explanation that my audience thinks I’m talking down to them.

Our workshops emphasize the importance of simplifying our communications without OVER-simplifying them. We want to get rid of anything that gets in the way of understanding—removing unnecessary lines, digits, data labels, and so on—but we also don’t want to remove SO much information that we leave our audiences guessing about what they’re even viewing.

How much context, then, is necessary to include, so that we have an understandable (but un-cluttered) visual, presented with enough background information for the viewer to grasp its meaning, with the key insights and recommended actions emphasized?

When we’ve addressed this question in the past, we’ve relied on the always-true, if sometimes unsatisfying, response of, “It depends.” Every situation is unique, and there’s no checklist or scorecard you can use in every circumstance to ensure that you’ve hit the perfect amount of detail.

However, there are a couple of considerations that will help you zero in on just the right amount of context to provide in your particular communication, and those are: the method of delivery you’ll be using; and the relationship you have with your audience. 

Delivery: live vs. written

When you present something in a live or a virtual setting, you have tremendous flexibility. You can respond to audience cues and questions; you can add or skip over details and background information on the fly, based on the reactions you’re getting; and you can (and should!) prepare more slides, to visually support your step-by-step explanations and keep viewers’ attention (particularly in an online communication). You can get away with having less context and detail physically written down or shown because you are there, live, to fill in any blanks. 

This is not the case in written communication, where the level of explicit detail must be higher. Without you present to facilitate the flow of information, your words and visuals must paint the full picture (and address at least first-order questions) on their own. In addition, people have a higher tolerance for detail on a slide, or on a single page of a report, if they can consume it privately at their own pace versus in a live group setting. Because of this, the level of detail necessary for written communication is much higher than for a presentation.

To see what these differences look like when we start from the same data, try your hand at the “optimize your output” exercise in the storytelling with data community.

Relationship: who are you to the audience (and vice versa)?

Even when we take care to identify our intended audience—as we should, whenever we communicate with data—we should also think how they will perceive us. Perhaps we have worked with this group before, or with mutual acquaintances; and as a result, will begin the presentation having already established our bona fides. If you have an established, trusting relationship with your audience, you can get away with showing less detail without your audience questioning it. 

On the other hand, we might be a completely unknown quantity…or we might have had to deliver unwelcome news in prior presentations to this same group. If you haven't established a basis of trust with your audience, or if they harbor negativity from prior communications, you may need to show more detail explicitly. That way, your audience is less likely to feel that you are trying to mislead by only showing the parts that back up your story and selectively discarding the rest.

You can test out different structures and levels of detail in your presentation early in the creative process, by employing the decidedly low-tech but incredibly effective technique of storyboarding. If you don’t storyboard on a regular basis but would like to see how it can be put into action, our exercise “storyboard your project” can give you some guidelines for getting started.

how do i avoid reworking my entire presentation if i have to share slides?

Through virtual and in-person workshops around the globe, we have taught tens of thousands of people how to communicate effectively with data. This series captures some of the noteworthy questions we hear during those sessions—and our answers.

Often a graph that makes sense during a live presentation loses meaning when distributed as a PowerPoint later. How can we retain context when transitioning between audiences without having to rework the entire presentation?

This is a relevant question in the time constraints we constantly are under in a real organization. We want to avoid using so-called slideuments in live presentations because it is difficult to both listen to a presenter and read text-heavy slides at the same time.  

But if you’re crunched for time, there are a few time-saving strategies that will help you avoid having to create a completely separate deliverable.

Let’s illustrate with a business example. Take a few minutes to watch Cole deliver a live data story (starting at 6:08): 

This presentation was notable because:

  •  The slides were well-designed, with effective graph choices, minimal clutter, and smart use of pre-attentive attributes to focus attention.

  • The visuals were paired with a strong narrative. 

If you flip through the same slides on your own—would the story still be as clear? Likely not.

Back to the original question: if we must send out the entire slide deck, then let’s look at two ways we could retain Cole’s narrative without having to rework the entire presentation.

  1. Write active slide titles. When you’re not presenting live, strong takeaway titles on your slides make it easy for the reader to understand the main point. The title bar is usually the first place your audience looks when consuming a slide deck on their own. Order your slides logically so that the reader can read just consecutive slide titles to get the overarching story you want to communicate. This is called horizontal logic.

  2. Add a fully annotated summary slide at the beginning of the deck. In this Craveberry video, Cole created this single summarized slide for the product that gets sent around after the meeting, as shown below. The audience gets the salient information without having to hear a live presenter or having to flip through the deck, because all of the information on the slide is self-reinforcing (an example of vertical logic). Adding it at the beginning means the audience could obtain the relevant details without having to flip through all the slides.

data storytelling and data visualization example

Here’s another example of adapting a live progression for written consumption.  

Employing either of these two approaches goes a long way in effective data storytelling because they allow us to tailor our mode of delivery to how our audiences are consuming it. 


Build your data storytelling skills in the community with these related exercises: