create effective executive summary slides

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Business communications often require a brief, at-a-glance overview. This is commonly referred to as an executive summary (although many audiences beyond executives will benefit from one). Despite their ubiquitous presence in business settings, summary documents that are clear and concise can be challenging to design. In this article, I’ll aim to ease some of that pain by exploring executive summary slides through an example, sharing best practices, and offering alternative layouts so that the next time you need to build a one-page, data-driven recap, you are set up for success!

What is an executive summary slide?

An executive summary slide is a one- or two-page overview of a much longer presentation added to the start of a deck. The goal is to provide a reader with the main messages, so they don’t have to read the entire communication. Executive summary slides often retain the horizontal orientation of the rest of the slide deck. Since they are meant to be read, rather than presented, they generally include more text than a traditional slide. (Important reminder: the slides you present to audiences live should not contain a lot of text!)

Any time you are planning to circulate your presentation, consider creating a summary view. Or better yet, only send a recap page.

Let’s look at an example.

An executive summary example & makeover

Here’s a genericized executive summary slide based on material provided by a recent client. This recap was created to give the VP of Sales a comprehensive overview of last quarter’s sales performance across all three company brands (A, B, and C). The full presentation deck contained about 30 slides, with detailed sections for each brand. The distinct brand colors were used throughout the deck to make the presentation and summary cohesive and easy to navigate.

As in any makeover, it’s helpful to start by assessing both what’s working and what could be improved. Starting with the positives, I appreciate the use of color. Typically I’d argue against this much color in a single view; however, the three colors have sufficient contrast and make it easy to navigate through the larger presentation by searching for a distinct brand color. Also, it may not be immediately apparent, but the stacked bar chart is a solid choice and works well to explain sales performance over time by each contributing brand. 

That said, there are some opportunities to transform this executive summary into a cohesive, comprehensive, and concise data-driven overview. Let’s step through each of the changes I’d make, along with the reasoning behind them.

Craft an engaging slide title 

The title of any document is often the first place an audience will look. Use this precious real estate wisely! When constructing a summary—or any slide for that matter—make sure the title states the main takeaway and sets the tone for the rest of the page. You can learn more about crafting strong slide titles in the linked article.

In the original example, it’s clear that sales increased year over year (YOY) based on the title, but was the increase enough? Should the focus be on the quarterly performance? Let’s modify the slide title to refocus our message, and use more concise language so it fits on a single line.

Use basic story structure

A summary should be a complete overview of the entire communication, with an obvious beginning, middle, and end. Many summaries tend to only focus on the insights or data without a clear introduction or conclusion, and this example is no exception. 

Given that this is a quarterly update, let’s ease into the Q3’21 analysis by first sharing the big picture (the beginning of the story). How are sales doing overall on an annual basis? I could also include some essential background information, like the fact that only three brands contribute to sales—two of which launched recently—before jumping into quarterly performance. Only after level setting the audience, then I can dive deeper into how each brand performed compared to its quarterly sales goal (the middle). And finally, the conclusion should be a strong takeway: Brand C markedly exceeded its quarterly sales goal, so let’s replicate the same sales strategy for some of the other lines of business (the ending). 

Notice the distinct sections of the story. Having a clear narrative in mind will help further improve the design of the summary slide.

Design for scannability 

Recap slides contain large volumes of information, which can make them complex to navigate. Help your audience digest a dense document by creating easily-discernible sections. Think about grouping related text and graphs. It’s also a good idea to include text headers for each section so that someone scanning for just a few seconds will still understand the main points. 

We can use the three sections we defined in our story—annual performance (beginning), quarterly performance (middle), next steps (ending)—to segment the slide. I’ve crafted pithy headlines and created two main columns which group the data and supporting text. For now, I’ve left placeholders for some descriptive insights.

In addition to focusing on the scannability of the document, I also want to ensure that the visuals are easy to skim. I can improve the stacked bars on the left by emphasizing the first and last bars so that a busy executive can quickly find evidence of the YOY increase. Tables don’t generally make for quick reads, so I’ll opt to visualize the data table on the right-hand side for faster processing. The results look like the following.

Write in complete sentences 

Try to avoid using bullets in a summary view unless you are listing elements. With bulleted text, your audience has to spend mental energy connecting the distinct points. In an executive summary, the goal is to inform and persuade an audience, and a few well-constructed sentences will accomplish this better than disjointed thoughts. 

Taking the original bulleted points and elaborating further on the story, I’ll create mini-paragraphs above each graph.

The summary slide is starting to take shape! As a final check, I’ll want to ensure that all of the text and visuals work to reinforce each other. If there is any unrelated information, that’s an indication that I need to expand my narrative or exclude these details from the overview. This is a concept is known as vertical logic.

I also want to ensure that it’s easy to navigate between reading and scanning the visuals. The clear sections certainly help with this, but let’s take things a step further by using similar colors in the written text.

My final revised executive summary could look like the following.

Comparing the before and after, notice how much easier it is to interact and skim the view on the right, despite the fact that the revised version is denser! Moreover, the key takeaways are now unmistakable, giving an audience a much fuller understanding of the latest sales performance.

While these changes did take a considerable amount of effort, especially when energy was already spent on the presentation slides, I’d argue it’s worth it. An executive summary is often created for a high-stakes communication to senior staff—hence the name. Moreover, this summary may be the only thing your audience ever looks at!

So far, we’ve explored best practices when it comes to a summary slide via an example. In the next section, I’ll share some alternative samples and layouts that cover a wider variety of content.

Executive summary slide templates & layouts

Since many audiences crave something to reference either before or after a meeting, I make it a habit to build summary slides for every presentation. Over time, I’ve found that two distinct layouts meet most of my needs.

Side-by-side layout

The most common design is similar to the makeover I shared above, where there are two side-by-side graphs or sections.

This template works well anytime you want to communicate a big picture understanding (section on the left) and then get into more granular details (area on the right). Or, if there are two graphs you want to share, it’s nice to split the slide in half so there is balance in the design. Here are a few additional examples.

Single visual layout

The second layout contains a single graph with more descriptive text. This works well when you need to set a deeper amount of contextual information as there is extra white space to use.

Here are a few samples of how this layout could look with data and supporting text.

These certainly aren’t the only possible layouts, but two that I rely on most frequently despite the presentation. You’ll encounter scenarios where you don’t have a visual or maybe you have more than one or two charts. It’s still important to craft a strong title, leverage story structure, write in complete thoughts, and focus on scannability.

Below are a few executive summary slides that required multiple visuals.

Final thoughts

Creating a single-page summary is not an easy feat, but it can help your audience gain a deeper understanding of your presentation when done well. 

If you have other approaches and thoughts on executive summary slides, please share them in the related community conversation.

why don't you capitalize your graph titles?

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 school, I was taught that you should center-align and capitalize the first letters of words in titles. I’ve noticed, though, that storytelling with data charts only capitalize the first word in the chart title, use ALL CAPS for the axis titles, and don’t center-align anything. Why?

This is a great question! There are good reasons why many tools use title-case, center-aligned text as the defaults for headers and titles—these formatting choices help that text stand out.

• Most written text is left-aligned, because it’s easiest to read. Center-aligned text tends to grab a reader’s attention due to its contrast with other text on the page. 

• Capitalizing every word in a phrase helps set it off from surrounding text, and makes it seem more formal and important.

In this bar chart, the header and the axis titles are following common default settings. The text is centered with each word’s first letter capitalized (“title case”), and the axis titles are in bold.

In graphs for business communications, though, the title shouldn’t be the element that stands out the most. It will certainly provide important context for the viewer, but data and insights should be the stars of the show. Some slight tweaks to these default settings can make the title a stronger supporting player, without stealing focus from the key elements of a communication.

Left-align graph titles for visual framing

Center-aligned text helps a reader to see that a new chapter, section, or page of text is about to begin…but a graph is already easily distinguishable from any nearby text, and doesn’t need center-aligned titles to emphasize that difference. 

Left-aligning chart titles creates a visual frame around the graph, without requiring us to draw any additional lines. Putting the title in the top left also ensures that a viewer sees that important context first.

Left-aligning the title creates a visual frame around your chart, without the need to draw in additional borders.

Use sentence case for clarity and speed of comprehension

Title case does a great job of setting text apart from any surrounding words…but in our graphs, the title sits on its own, and doesn’t need that kind of distinction. Sentence case—in which one capitalizes only the first word of our titles—offers several advantages:

• It is easier and faster to read, especially in a longer block of text. It Should Be Clear In an Instant That It Is Not Easy or Pleasant to Read the Text in This Particular Sentence When Every Word Is Capitalized.

• Sentence case feels less formal and more approachable than title case, which can be beneficial in those situations where your audience might be unfamiliar with the data you are presenting (or with data in general).

• Proper nouns are hard to pick out when we use title case; sentence case makes them easier to see.

Use sentence case in your chart titles to make them easier to read, and to make the visual feel more inviting for an audience.

Make axis titles easy to find and easy to ignore

Axis titles provide important information to a viewer of the graph, but they shouldn’t be distracting. Instead, they should be easily discoverable, while at the same time can fade into the background. They’re part of the skeleton of the graph—providing structure, but letting the data itself take center stage.

Axis titles provide important context, but they shouldn’t stand out or draw attention away from the data.

There are several ways to achieve this “easy to find, easy to ignore” balance in axis titles:

• Set the text to a neutral, but readable, gray color;

• Use ALL CAPS, so the title’s outline is a regular rectangle, rather than a jagged mix of “ascenders and descenders” (the parts of lowercase letters that stick up above the average height or drop below the baseline of the font); and

• Align them to the top of the y-axis or the left of the x-axis so that they can always be found easily, and so that they also create implicit (rather than actual) borders around our graph.

Some techniques for making axis titles useful without being overwhelming include using a neutral text color, writing the titles in all caps, and aligning the titles to the top of the y-axis and the left of the x-axis.

Keep in mind, of course, that these choices are not right or wrong; they merely reflect our data storytellers’ styles, preferences, and priorities. In business, it’s important to maximize understanding and clarity in charts, and these choices are all about accomplishing that most effectively. If your organization has an established style guide or follows other existing guidelines (e.g., AP, Chicago, APA), then stick with those conventions. Otherwise, consider the impression you want to make on your audience, and make your own capitalization and alignment choices accordingly.

A few small changes to default settings for chart titles and axis titles can make visualizations cleaner and more approachable, while at the same time making the data and the insights easier to understand.

your graph skeleton shouldn't be spooky

As I write this, it’s mid October. I’m looking at my neighbor’s lawn, and it is covered with vampires, mummies, ghosts, goblins, and most of all: skeletons. Obviously, it’s meant to be fun for Halloween. Sort of pretend-scary. But there’s another place where skeletons should NEVER be scary: in our graphs.

My colleague Alex was the first person I heard refer to the underlying structure of a graph as its “skeleton.” This includes all the features that give form and shape to your graph, but that ideally—like bones—we never even really notice or see. The skeleton frames and structures our graph, but doesn’t include the data itself. 

If we don’t take the time to organize the skeleton of a chart thoughtfully and intentionally, our data won’t be appropriately supported. To an audience, something will always seem a little bit amiss.

Here’s a chart with a very spooky skeleton:

I’m REALLY noticing the bones here. The skeleton is so distracting, I can’t pay attention to the data or the message. The gridlines are overwhelming, making the legend and the data series barely legible. Our axes have diagonal text, lots of extra zeroes and duplicative information, and an absence of helpful titles. The chart title could stand some changes in color, positioning, capitalization, and word choice.

let’s fix this skeleton

First, I’ll remove the data, so we’re just left for now with a pile of bones.

There are nearly 100 gridlines here, and that’s about 100 too many. We see this sometimes when designers are trying to mimic old analog graph paper. It’s fine as a visual metaphor, but practically speaking, it’s clutter. Getting rid of gridlines, and replacing them with muted axis lines, is my first step in putting my skeleton back together.

Next, I’ll clean up my x-axis by removing the repeated “2019” and rotating my text to be horizontal, and I’ll add an axis title to make it clear what we’re showing. 

The numbers on the y-axis can be simplified by showing them as thousands. I’ll also add an axis title to reflect that. The tick mark intervals can be closer together, maybe every 25,000 visitors rather than every 50,000; my preference is to minimize the number of gaps between tick marks, as long as the intervals are logical and the text doesn’t feel too cramped.

The last thing to change is the title. I’ll make it left-aligned (to help frame the chart more), sentence case (so that it’s easier to read), and a neutral color (rather than the same reddish-purple as my “in-state” data series). I’ll also rewrite it slightly, adding a subheader, so that the metric I’m using in my chart is clearer to the viewer. 

Look at how orderly my skeleton is now! Rather than being distracting and obtrusive, it quietly provides structure for the visualization I’m creating. Instead of a spooky skeleton, my graph now has good bones.

now bring back the data

When I put the original data series lines back in—making no changes whatsoever to their formatting or layout—the improved skeleton makes the information much easier to see and understand.

With my data on this improved skeleton, it’s now easier for me to identify how I could refine this visual even more. I’ll remove the “total” series (since it doesn’t add any new information), and I’ll include some helpful annotations to the lines that remain, instead of keeping the legend. This way, I’m making sure that my audience can not only see my data, but understand what insight they’re meant to understand after looking at it. 

So remember: skeletons are important to think about all year round, not just at Halloween. The only place where it’s OK for them to be spooky is in our decorations.

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Want to learn more about how small design decisions can lead to big impacts? Cole walks you through ten specific tips in our video, “it’s the little things.” Check it out!

exploring data is different than explaining data

Today’s topic was inspired by a discussion in a recent client workshop. At the beginning of our sessions, we ask attendees to share what they want to learn during our time together. Their answers usually include being more concise, creating better presentations, getting stakeholders to act, ways to visualize data differently, and so on. 

Recently Mike and I were conducting a session where these two responses came in back-to-back:

Participant 1: I want to learn to create interactive data visualizations that enable my stakeholders to find the story.

Participant 2: I want to develop a sharper editorial eye for what data to include to tell the right story. 

While these two responses might seem at odds with one another, they really aren’t. They’re just describing two different stages in the analytic process: the exploratory stage and the explanatory stage.

Exploratory analysis is what you do to get familiar with the data. You might begin with a hypothesis or question you want to answer, or you might just look at the data from different angles to find what’s interesting about it. We’re often using dashboards (or interactive data visualizations, as Participant 1 described them) in this step of the process. When designed well, they can lead us to insights faster. 

Compare that to explanatory analysis, which is when you’ve identified something specific, and are ready to communicate it to someone specific. At this stage, we’re all about driving action and positive change: we want to make it abundantly clear to a decision-maker that something demands attention and (hopefully) action. This requires—as Participant 2 put it—developing a sharper editorial eye for what data to include.

The challenge with using the same output from our initial exploratory analysis for our final explanatory communication is that it will often include not just the important, actionable insights, but also a bunch of other irrelevant details. For our audience, that makes the story harder to absorb. 

To be effective data communicators, we should strive toward Participant #2’s goal: developing a sharper editorial eye for how to weave data into an overarching story.

Illustration by Catherine Madden

I’ll use a recent client makeover to illustrate why the visual you use in exploratory analysis might—and should—differ from what you use to communicate. 

In this example, imagine you work for a pharmaceutical company that is conducting market research on your newly launched hypertension therapy, Vinsulfan. A third party aggregates and provides the data to you for analysis. One metric—physician's likelihood to prescribe—is shown in the graph below. (Details, including the names of the drugs, have been modified to protect client confidentiality.) 

This view might suffice for you during your initial analysis. However, once you’ve identified what’s interesting about the data, you should modify this visual so that those insights stand out more for your intended audience. 

For example, let’s assume we want to draw attention to the favorable responses—”likely” and “extremely likely.” I can use color sparingly to emphasize the proportion of these actions. Here I’m electing to use green to focus attention because it’s the drug’s brand color—a different scenario might call for a different color palette.

Or, I might even modify the intensity of color to draw attention to one particular insight—in this case, that more physicians responded favorably to initiating our brand than the other options.

If I really want to make sure my audience doesn’t miss the point, I should state that in words:

Or, I could summarize multiple takeaways with a single slide like this:

Compare my original exploratory visual with the one I’m using to explain my findings. It’s the same data in both cases, as well as the same chart type, and many of the same words. But in the end, some minor modifications to the color and words I use make my actual insight unmistakable, and my recommended action clear. In the final visual, I’ve honed my editorial eye towards highlighting how this data fits into an overarching story in my organization. 

Here are some additional resources to help you and others you work with practice differentiating between exploratory and explanatory analysis:

• READ: another example, five questions to ask yourself when explaining data, the role of dashboards

• WATCH: how to pull a story out of a dashboard (open to premium members)

• PRACTICE: create a story from a dashboard (August 2021 SWD challenge)

• ATTEND: our Fall 2021 webinar series (specific topics below)

visualizing gender identity

At a recent custom client workshop, the question was raised: how do we best visualize the results of our gender identity survey? 

The organization had collected data on gender self-identification from four categories of employees: the board, directors, managers, and associates. Their responses are summarized in the table below (details have been slightly modified to protect confidentiality.)

Before we jump straight to visualizing this data, let’s spend a minute familiarizing ourselves with the responses. To do this, I’ll introduce some visual elements into this tabular data, to draw attention to some interesting things. 

A heatmap allows us to convey the relative magnitude of the numbers with color saturation. We could do this within a single column:

Or, across multiple columns:

A heatmap alleviates some of the cognitive burden of processing tabular data. 

However, there’s an interesting piece of the data that might be better served with a different visual: the wide range of magnitude in responses. Scanning down then columns, the minimum value is zero, then some single-digit values (1%), and a maximum value anywhere from 50% to 73%. 

Along our rows at the bottom, where we are counting the absolute numbers of people in each role, the range is even greater, from a low of eight directors to a maximum of 161 associates:

One benefit of switching from a table to a graph would be to help a viewer understand the overarching shape of the data, which is less apparent when visualized in tabular form. While there’s many ways we could graph this data, I opted for a square area chart for its versatility in displaying numbers of different magnitudes.

A square area chart is an example of a unit graph: a single square represents one unit. The benefit of this type of graph is that you can visualize more information—two dimensions encoded as width and height—in less space. 

I used Excel to create my square area graph, first illustrating the survey population:

Then displaying the overall breakdown with color saturation:

I could split this into 4 separate graphs to show the breakdown by role—and where the number of roles is concentrated.

When working with survey data, a square area graph can be an effective choice to visualize the magnitude of responses within a population. If interested, you can download the Excel file for a behind-the-scenes peek at how I created these visuals. 

A square area chart is just one example of a unit graph. Check out these additional resources on this type of visual:

• Another use case: visualize a hiring funnel

• Previous SWDchallenge: square area graph

• Current SWDchallenge: create and share a unit chart

• Monthly event (open to premium subscribers): a unit chart for two different audiences

• Video: Jon Schwabish’s One Chart At a Time video series: Unit, Isotype and Waffle Charts  

• Article: Robert Kosara’s post (w/ video) on unit charts and what makes them special

connecting the slide title to the graph

Today’s post outlines one approach to get your message across more clearly: use color to connect the slide title to the graph. 

First, a bit of background. When communicating with data in PowerPoint, your slide title is precious real estate. Your audience is typically looking there first to understand what the slide will display, so we should be using active slide titles to help set their expectations.

Let’s look at an example, adapted from Exercise 5.7 of storytelling with data: Let’s Practice!. The following visual shows a competitive landscape overview for an on-demand printing company.

Consider the slide title. I’d categorize it as an active title because it primes me for what I should see in the forthcoming data. The designer was thoughtful both to put the main point into words and to make the words stand out via their size and placement at the top of the page.

If you’re like me,  then you’re probably now searching for evidence of an increase in XBX Business in the graph. You’ll find it eventually, but there are ways to eliminate the need for this tedious search process altogether.

One option is to use the same color between the data and the text, while simultaneously de-emphasizing the rest of the visual with grey. Check out what a difference this makes: 

This simple change—the power pairing of color and words—ensures that the audience is more likely to immediately understand the results of all the hard work we’ve done. All we have to do is make it easier for them to see in the first place. 

Are there more improvements we can make to this slide? Absolutely—you can download the data and practice improving this visual with me in the SWD community exercise from good to great.