Although we might primarily think of PowerPoint as a slide-creation tool, it also has the capability to build graphs natively without the need to import or link from Excel and is our go-to tool for developing the customized content used in our corporate team trainings.

In this lesson, we'll explore the basics of creating a chart and understanding the elements of our visuals that make up its overall structure or skeleton.

To begin, click the Insert menu, then Chart, and select bar chart. You can also achieve this via the Insert ribbon menu. A separate Excel file will open (its only purpose is to hold the data for your bar chart). You can type (or paste) in the data and then close Excel.

Here is the data from the video if you want to follow along and create the bar graph:

Month Headcount
January 317
February 309
March 275
April 265
May 287
June 289
July 286
August 302
September 297
October 291
November 340
December 311

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Adding data labels to our charts provides our audience with the exact values of a specific data point. This can be useful, but in this video, we'll take a look at how labeling all of our data might not be the best approach and why a more sparing selection of labels would have a greater effect. Download the slide and follow along with the video.

• To add labels, right-click on any bar, and this will select the whole set of bars (the data series).

• In the menu of options that appears, click Add Data Labels. The default setting is to add the labels above the bars, but we can do something slightly different here with the formatting options.

• We have many formatting options available to us. We can alter the font style, color, and size of our labels, and if we right-click on the labels and select format data labels, we have a host of additional options.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Take intentional steps to make your chart axis easy to read:

1. Rotate text horizontally for easier reading

2. Add clear axes titles so it’s clear what is represented

3. Remove extraneous decimals and format numbers to reduce the number of zeroes

Download the slide and follow along with the video.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Take intentional steps to make your chart axis easy to read:

1. Rotate text horizontally for easier reading

2. Add clear axes titles so it’s clear what is represented

3. Remove extraneous decimals and format numbers to reduce the number of zeroes

Download the slide and follow along with the video.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Ensuring that our graphs are as easy to process as possible is crucial in gaining our audience's attention and engagement. One way we can achieve this is with careful alignment of our chart titles. In this video, we examine where we recommend chart titles be placed to create an immediate sense for the viewer of what the chart is displaying.

Download the slide and follow along with the video.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Without a clear and thoughtfully incorporated legend, viewers of our data communications will struggle to understand exactly what we’re presenting to them. Any additional effort an audience needs to devote to solving the mystery of “which data series is green?” or “what’s the difference between square data markers and circles?” is energy they won’t have to put towards grasping your visual’s important insights. A well-designed legend will remove that cognitive burden.

One option we have is to move the legend to the top so we see the color & category key sooner. To make this change, click on the chart, then navigate to the 'Chart Design' ribbon at the top. On the left, select the 'Add Chart Element' dropdown > Legend > Top. This automatically moves it to the top center under the chart title, but we could move it to the left to align it with the title by selecting and dragging it over to create a cleaner aesthetic.

We could also move the legend directly next to the data it describes. This alleviates the need to refer back and forth between the legend and the data. There are a couple of ways to do this:

1. opt to add a data label directly > click twice, right-click, add label, highlight retype. Adjust size, and font.

2. another option is to add a text box

Having the label next to the line uses the proximity principle, which is when things are close to one another, we tend to relate them. We can go a step further and apply something called the similarity principle and make the labels the same color as the line to visually tie them together. Simply click on the label text box and adjust the text color on the 'Home' menu ribbon.

Download the slide and follow along with the video.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

There are so many different visualization graphing options that it can be difficult to know which one is right. Rather than focusing on one graph for any given type of data, it's important to explore different options. Looking at alternative views using a low-tech approach like sketching can reveal an approach that shares your data in the most compelling way, bringing those important insights to life.

Sketching graph ideas is one of our favourite exercises from our corporate team training workshops, and in this video, we explore ways to quickly iterate to different views within PowerPoint.

Download the slide to follow along with this video.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

In this module, we showed you how to make your visuals clearer so your data stands out. For reference, download this guide to creating good graphs.

The great news is that you can create a chart template that automatically applies most of these changes from the start. This means you won't have to spend as much time designing the look of your charts.

To create a template, right-click on your finished chart and choose the option to save it as a template. Give your template a name and click OK. Your new template will be ready to use right away. You can find it in the templates folder by going to INSERT (at the very top), then charts, and finally templates.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

You learned in this module that a frequent source of clutter in data visualization comes from unnecessary graph elements: borders, gridlines, data markers, and the like. These can make our visuals appear overly complicated and increase the work our audience has to undertake in order to understand what they are viewing. As we eliminate the things that don't need to be there, our data stands out more.

You've watched Amy and Simon demonstrate the decluttering steps specific to the sales manager headcount graph. In this practice exercise, you will consider another example, which shows the time to close deals, measured in days, for direct and indirect sales teams over time.

Consider what visual elements you could eliminate in this example. What other changes would you make to what is shown or how it’s shown to reduce cognitive burden? How many changes would you make to this visual? Spend a moment thinking through these questions and making some notes, then download the data and create your decluttered graph using PowerPoint, applying the steps Simon and Amy walked through in the learning videos.

This exercise is based on Let's Practice! Exercise 3.4.

OPTIONAL: upload your solution in the SWD community

The SWD Community is your free, online destination for honing data visualization and storytelling skills and connecting with others. It is free to join using a valid email address. Once you sign up, share your solution to this declutter exercise here. After submitting, review those shared by others.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Participants of our workshops will often explain the main purpose of the example they’ve shared with us. And, when we create a graph we are know exactly what the main point of it is. However, unless we make that clear to our audience we run the risk of them making assumptions or drawing incorrect conclusions.

In this video, we are going to explore how the use of a simple test can help us understand where our audience's eyes will go when they first look at our content.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

In this video, we explore various ways to emphasize a single line in a graph. Download the slide and follow along with the video.

There are multiple approaches to highlight a single element in a chart:

1. Color. Select just the line you want to emphasize, then go to the Home ribbon menu, and on the right, select the 'Shape Outline' drop-down and select blue.

2. Thickness. With the line still selected, bump up the weight or thickness in the 'Shape Outline' menu. A line weight of around 4.5 pts is usually plenty to make it stand out from the rest if they are less than 3 pts.

3. Line style. With the line selected, pick the desired dash type from the drop-down from the "Shape Outline' menu. This is an option to explore for emphasis; however, be aware that dashed or dotted lines are often associated with uncertainty—things like forecasts or estimates.

4. Data markers. To add data markers, right-click the graph and select 'Format Data Series', so the menu options appear on the right hand side. Navigate to the 'Fille & Line' menu—the one that looks like a paint can. Here, you can see the color, width and style options we applied from the 'Shape Outline' menu on the Home ribbon—you can quickly make those same modifications from this menu as well. To add data markers, click the 'Markers' toggle at the top, then "Marker Options", select 'Built in' and select the type and size. Below this are options to change the fill & border colors.

5. Data labels. Select each point, right click, and pick add "Data Labels". To just add the label to a single point, click the point, wait a moment, then click again so just the single point is selected. The default is a black font on the right side. You can move these to the top, change them to a different color, make them bold, and a bit larger font. You can easily adjust the font in the Home menu once you select the data labels. To play with other formatting, use the 'Format Data Labels' format pane on the right. Go to the label options menu and then the one that looks like bars. Under 'Label Options' you can tick 'Above' in the 'Label Position' section.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

We continue to look at ways to focus attention. In this video, we'll explore categorical data with bar charts and understand the variety of techniques we can apply to emphasis the important aspects of our view. Download the slide to follow along with this video and apply the steps below.

1 Position. With bars and categorical data, we have the opportunity to sort the bars in any order we'd like. Of course, if there is a natural order for the categories (perhaps known survey questions), then it'd be advisable to retain that order. If there isn't an inherent order, we can use the position of the bars to draw our audience attention. To sort our bars, we need to sort the data that's being plotted. Right-click on the graph and select Edit in Excel. Once Excel has opened with the data, click data -> sort (either descending or ascending).

2 Pattern fill. One option we have with bars that aren't open to lines is to change the pattern within the bars. To change the pattern, we can right-click the bar we want to draw attention to, select Format Data Point -> Paint Bucket Tool -> Fill -> Pattern Fill, and select a pattern layout option and colors. Note that while this is extremely attention-grabbing, it is overused and can be extremely attention-grabbing. Patterns in bars are often reserved to provide a sense of uncertainty, like a forecast.

3 Border. A subtle way to emphasize a bar is to add a border; within the same set of menu options, the next set of options concerns border control.

4 Color. Select the bars, and back in the fill options, select Solid Fill, and then choose the color.

5 Intensity. We can choose to increase the transparency of the other bars. Within the fill options, this is as simple as increasing the transparency slider. Note this has to be done with each bar so a similar effect can be achieved with a white text box placed over the graph. Then, within the shape format options, applying transparency to the text box will let those bars become visible, albeit with less intensity than the others.

6 Data labels. We can add data labels to our view. To add labels, right-click on the bar in question and select Add data labels. The labels can be formatted in a number of different ways, and when it comes to bar charts, one recommendation is to add the labels inside the bar’s ends. This can be achieved by selecting the data labels, clicking the graph icon, and then, within the label position options, selecting Inside End.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

An annotation is just a block of text that provides additional context, highlights important data points, or explains trends. The quickest and easiest way to achieve this in PowerPoint is to add a text box on your slide. Under the Home ribbon, click Text Box towards the right and click on the slide where you want it placed. Then click into the textbox and type your words.

Using a textbox allows you to easily move the text around so that your audience can quickly understand what is happening in the graph. Ideally, we want to annotate as close to the data as possible, directly on the graph itself. This way, our audience won't have to move their eyes back and forth between the words and the data they describe.

When it comes to annotations, a key tip is to ensure clean and thoughtful alignment between data elements and annotations. By aligning text boxes with data points or chart elements, you can create a professional and visually appealing presentation. This is easily achieved by moving the textbox and adjusting the font alignment within the text box itself, a feature readily accessible in the Home ribbon. For bar charts, align annotations with the edges of bars. This alignment not only creates a visual connection that guides the viewer's eye but also enhances their understanding.

A final tip for annotating graphs is to ensure your words are visually consistent with the chart. This means matching the font style and size of your annotations to the chart text. Use colors from your chart's palette in your annotations. This consistency creates a cohesive, professional look.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

It's a common misconception that the 'data should speak for itself'. Without the use of words to explain our charts, we run the risk of our audience drawing incorrect conclusions. Ensuring our graphs are well titled will ensure those viewing the visual gain an immediate appreciation of the information on display.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

The slide title will be the first thing your audience sees. If they only spend a few moments scanning your slide, make it easy for them to understand the primary point. Transform descriptive slide titles into active takeaway titles. To make it easier to read, we recommend a pithy title that fits on a single line.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

In addition to setting the stage for what’s coming, a navigation scheme employed well will help orient the audience in the midst of content. When making use of one, introduce it somewhere close to the beginning, then revisit it as you transition from one section or topic to the next. In this manner, you can make it clear to your audience where you are presently in the presentation as it relates to both where you've been and where you're going.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Speaker notes are a fantastic tool for clarifying your talking points and making notes so you remember important points during your delivery. Keep things simple so you can quickly glance at them during your presentation. Don't plan to read your speaker notes word for word out loud when presenting—that would not be very engaging or preofessional. However, if you are sending your slides around or if someone else will present your slide, you can include more detailed notes to make sure all the key points are captured.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

We can also use PowerPoint's built-in functionality for graph animations. Download the slide and follow along with the video.

• Begin by selecting your chart, then go to the 'Animations' ribbon.

• Choose an animation effect like 'Appear.' This will have the chart appear as a whole when you click to animate.

• To animate specific elements, make adjustments in the animation pane by expanding the 'Chart Animations' menu.

• You can also make adjustments to the 'Timing' menu to make certain elements appear at the same time.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Dense, text-heavy slides can be overwhelming for your audience, especially if you are presenting live. Don't present a wordy slide, instead plan animated short & pithy statements that you expand upon.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

One question we often receive during our workshops is “How many slides should I have?”. Depending on how you deliver the content, that answer will vary. A summary slide is a concise overview of a longer presentation or report.

It is usually one or two pages that provide the main messages, allowing readers to grasp the key points without going through the entire document. In a live setting, slides should be sparse and serve as visual support for you as the narrator. When slides must stand on their own, as read-aheads or as reference documents, they can (and should) include more text, since you won’t be there in the room to answer your audience’s questions in the moment.

Creating a single-page summary is not always a straightforward process, but it can help your audience gain a deeper understanding of your presentation when done well. Designing scannable text, showing clear visuals, and tying related elements together with similar colors help to make effective executive summaries.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

Imagine that you work as an analyst in Human Resources. The client team you support recently concluded an upward feedback survey, where individuals assess their manager across various dimensions. From this, an aggregate "manager score" is calculated (the manager score ranges from 0 to 10—the higher, the better). Your company also conducts an annual performance review process, where each individual's manager assigns them a numeric rating (on a scale from 0.0 to 5.0, again, the higher the score, the better).

You've been asked by your client to pull together data showing their population of managers by manager score and performance score (assigned by the given manager's manager). Given the two measures, you're pretty sure a scatterplot will be a good way to show this data.

When you share your scatterplot with a colleague, you receive feedback that it may be too complicated for your client group, who tend to consider themselves "non-data" people. In spite of that, you'd like to make it work—perhaps even increasing your client group's graphicacy along the way. In light of this scenario, tackle the following:

STEP 1: Graph titles are important. They help set expectations for what your audience will see in the graph and can even help the graph itself be more memorable. How would you title this graph?

STEP 2: Are there additional changes you would make? Consider if you would add or remove words, whether it could make sense to highlight or categorize parts of the data, or if there are other modifications you would make to help make the data easier to understand. Write a couple sentences summarizing your ideas.

STEP 3: Imagine that you will present this data to your client group in a live meeting. Rather than start with the full scatterplot, this affords you the ability to build it piece by piece. How would you approach this? Outline the steps you would take and then download the slide (the graph is built there, so everything is directly editable in PowerPoint) and create your recommended progression.

OPTIONAL: upload your solution in the SWD community

The SWD Community is your free, online destination for honing data visualization and storytelling skills and connecting with others. It is free to join using a valid email address. Once you sign up, share your solution to this declutter exercise here. After submitting, review those shared by others.

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.

CONGRATULATIONS on working through the course content!

• Complete the final quiz to test your learning

• Continue developing your skills with our additional resources

The examples featured throughout this course can be found in Chapter 18: Explain with data stories (not dashboards) | Knaflic, Cisneros, and Velez. Storytelling With Data: Before & After, Wiley, © 2025.