CONTENTS

Cover

acknowledgments

about the author

introduction

chapter one understand the context

Exercise 1.1: get to know your audience
Solution 1.1: get to know your audience
Exercise 1.2: narrow your audience
Solution 1.2: narrow your audience
Exercise 1.3: complete the Big Idea worksheet
Solution 1.3: complete the Big Idea worksheet
Exercise 1.4: refine & reframe
Solution 1.4: refine & reframe
Exercise 1.5: complete another Big Idea worksheet
Solution 1.5: complete another Big Idea worksheet
Exercise 1.6: critique the Big Idea
Solution 1.6: critique the Big Idea
Exercise 1.7: storyboard!
Solution 1.7: storyboard!
Exercise 1.8: storyboard (again!)
Solution 1.8: storyboard (again!)
Exercise 1.9: get to know your audience
Exercise 1.10: narrow your audience
Exercise 1.11: let’s reframe
Exercise 1.12: what’s the Big Idea?
Exercise 1.13: what’s the Big Idea (this time)?
Exercise 1.14: how could we arrange this?
Exercise 1.15: storyboard!
Exercise 1.16: storyboard (again!)
Exercise 1.17: get to know your audience
Exercise 1.18: narrow your audience
Exercise 1.19: identify the action
Exercise 1.20: complete the Big Idea worksheet
Exercise 1.21: solicit feedback on your Big Idea
Exercise 1.22: create the Big Idea as a team
Exercise 1.23: get the ideas out of your head!
Exercise 1.24: organize your ideas in a storyboard
Exercise 1.25: solicit feedback on your storyboard
Exercise 1.26: let’s discuss

chapter two choose an effective visual

Exercise 2.1: improve this table
Solution 2.1: improve this table
Exercise 2.2: visualize!
Solution 2.2: visualize!
Exercise 2.3: let’s draw
Solution 2.3: let’s draw!
Exercise 2.4: practice in your tool
Solution 2.4: practice in your tool
Exercise 2.5: how would you show this data?
Solution 2.5: how would you show this data?
Exercise 2.6: let’s visualize the weather
Solution 2.6: visualize the weather
Exercise 2.7: critique!
Solution 2.7: critique!
Exercise 2.8: what’s wrong with this graph?
Solution 2.8: what’s wrong with this graph?
Exercise 2.9: let’s draw
Exercise 2.10: practice in your tool
Exercise 2.11: improve this visual
Exercise 2.12: which graph would you choose?
Exercise 2.13: what’s wrong with this graph?
Exercise 2.14: visualize & iterate
Exercise 2.15: learn from examples
Exercise 2.16: participate in #SWDchallenge
Exercise 2.17: draw it!
Exercise 2.18: iterate in your tool
Exercise 2.19: consider these questions
Exercise 2.20: say it out loud
Exercise 2.21: solicit feedback
Exercise 2.22: build a data viz library
Exercise 2.23: explore additional resources
Exercise 2.24: let’s discuss

chapter three identify & eliminate clutter

Exercise 3.1: which Gestalt principles are in play?
Solution 3.1: which Gestalt principles are in play?
Exercise 3.2: how can we tie words to the graph?
Solution 3.2: how can we tie words to the graph?
Exercise 3.3: harness alignment & white space
Solution 3.3: harness alignment & white space
Exercise 3.4: declutter!
Solution 3.4: declutter!
Exercise 3.5: which Gestalt principles are in play?
Exercise 3.6: find an effective visual
Exercise 3.7: alignment & white space
Exercise 3.8: declutter!
Exercise 3.9: declutter (again!)
Exercise 3.10: declutter (some more!)
Exercise 3.11: start with a blank piece of paper
Exercise 3.12: do you need that?
Exercise 3.13: let’s discuss

chapter four focus attention

Exercise 4.1: where are your eyes drawn?
Solution 4.1: where are your eyes drawn?
Exercise 4.2: focus on...
Solution 4.2: focus on...
Exercise 4.3: direct attention many ways
Solution 4.3: direct attention many ways
Exercise 4.4: visualize all the data
Solution 4.4: visualize all the data
Exercise 4.5: where are your eyes drawn?
Exercise 4.6: focus within tabular data
Exercise 4.7: direct attention many ways
Exercise 4.8: how can we focus attention here?
Exercise 4.9: where are your eyes drawn?
Exercise 4.10: practice differentiating in your tool
Exercise 4.11: figure out where to focus
Exercise 4.12: let’s discuss

chapter five think like a designer

Exercise 5.1: use words wisely
Solution 5.1: use words wisely
Exercise 5.2: do it better!
Solution 5.2: do it better!
Exercise 5.3: pay attention to detail & design intuitively
Solution 5.3: pay attention to detail & design intuitively
Exercise 5.4: design in style
Solution 5.4: design in style
Exercise 5.5: examine & emulate
Exercise 5.6: make minor changes for major impact
Exercise 5.7: how could we improve this?
Exercise 5.8: brand this!
Exercise 5.9: make data accessible with words
Exercise 5.10: create visual hierarchy
Exercise 5.11: pay attention to detail!
Exercise 5.12: design more accessibly
Exercise 5.13: garner acceptance for your designs
Exercise 5.14: let’s discuss

chapter six tell a story

Exercise 6.1: use takeaway titles
Solution 6.1: use takeaway titles
Exercise 6.2: put it into words
Solution 6.2: put it into words
Exercise 6.3: identify the tension
Solution 6.3: identify the tension
Exercise 6.4: utilize the components of story
Solution 6.4: utilize the components of story
Exercise 6.5: arrange along the narrative arc
Solution 6.5: arrange along the narrative arc
Exercise 6.6: differentiate between live & stand-alone stories
Solution 6.6: differentiate between live & stand-alone stories
Exercise 6.7: transition from dashboard to story
Solution 6.7: transition from dashboard to story
Exercise 6.8: identify the tension
Exercise 6.9: move from linear path to narrative arc
Exercise 6.10: build a narrative arc
Exercise 6.11: evolve from report to story
Exercise 6.12: form a pithy, repeatable phrase
Exercise 6.13: what’s the story?
Exercise 6.14: employ the narrative arc
Exercise 6.15: let’s discuss

chapter seven practice more with cole

Exercise 7.1: new advertiser revenue
Solution 7.1: new advertiser revenue
Exercise 7.2: sales channel update
Solution 7.2: sales channel update
Exercise 7.3: model performance
Solution 7.3: model performance
Exercise 7.4: back-to-school shopping
Solution 7.4: back-to-school shopping
Exercise 7.5: diabetes rates
Solution 7.5: diabetes rates
Exercise 7.6: net promoter score
Solution 7.6: net promoter score

chapter eight practice more on your own

Exercise 8.1: diversity hiring
Exercise 8.2: sales by region
Exercise 8.3: revenue forecast
Exercise 8.4: adverse events
Exercise 8.5: reasons for leaving
Exercise 8.6: accounts over time
Exercise 8.7: errors & complaints
Exercise 8.8: taste test data
Exercise 8.9: encounters by type
Exercise 8.10: store traffic

chapter nine practice more at work

Exercise 9.1: create your plan of attack
Exercise 9.2: set good goals
Exercise 9.3: give & receive effective feedback
Exercise 9.4: cultivate a feedback culture
Exercise 9.5: refer to the SWD process
Exercise 9.6: make use of an assessment rubric
Exercise 9.7: facilitate a Big Idea practice session
Exercise 9.8: conduct an SWD working session
Exercise 9.9: set yourself up for successful data stories
Exercise 9.10: let’s discuss

chapter ten closing words

index

End User License Agreement

List of Illustrations

Introduction

Figure 0.1 How SWD chapters correspond to this book

Chapter one

Figure 1.7 Back-to-school shopping: a potential storyboard
Figure 1.8 Pet adoption pilot program: a potential storyboard
Figure 1.14 Potential components of a storyboard
Figure 1.16 University elections colleague’s storyboard

Chapter two

Figure 2.1a Original table
Figure 2.1b Slightly improved table
Figure 2.1c Table with heatmapping
Figure 2.1d Table with embedded bars
Figure 2.1e A pair of pies
Figure 2.1f Two horizontal bar charts
Figure 2.1g Horizontal dual series bar chart
Figure 2.1h A vertical bar chart
Figure 2.1i Let’s draw some lines
Figure 2.1j Take away the bars
Figure 2.1k A slopegraph
Figure 2.2a Table showing meals served over time
Figure 2.2b Table with heatmapping
Figure 2.2c Bar chart
Figure 2.2d Line graph
Figure 2.3a Let’s draw this data!
Figure 2.3b My data drawings
Figure 2.4a Basic bars
Figure 2.4b Line graph
Figure 2.4c Overlapping bars
Figure 2.4d Stacked bars
Figure 2.4e Dot plot
Figure 2.4f Graph the difference
Figure 2.5a Attrition over time
Figure 2.5b Dot plot
Figure 2.5c Line graph
Figure 2.5d Line graph with shaded area depicting average
Figure 2.5e Area graph
Figure 2.5f Bar graph
Figure 2.6a The weather forecast
Figure 2.6b Bar charts must have a zero baseline!
Figure 2.6c Let’s compare the two graphs
Figure 2.7a Bank index
Figure 2.7b Revamped graph
Figure 2.8a What is confusing in this graph?
Figure 2.8b An alternative view
Figure 2.9a Average time to close deal
Figure 2.11 Original visual from dashboard
Figure 2.12a Pies
Figure 2.12b Bars
Figure 2.12c Divergent stacked bars
Figure 2.12d Slopegraph
Figure 2.13 What’s wrong with this graph?
Figure 2.14 Let’s visualize & iterate

Chapter three

Figure 3.1 Which Gestalt principles are in play?
Figure 3.2a How can we visually tie the words to the graph?
Figure 3.2b Proximity
Figure 3.2c Proximity with emphasis
Figure 3.2d Similarity
Figure 3.2e Enclosure
Figure 3.2f Enclosure with color differentiation
Figure 3.2g Enclosure plus similarity
Figure 3.2h Connection
Figure 3.2i Connection plus similarity
Figure 3.3a How might we better use alignment & white space?
Figure 3.3b Better employment of alignment & white space
Figure 3.4a Let’s declutter!
Figure 3.4b Remove heavy lines
Figure 3.4c Remove gridlines
Figure 3.4d Drop trailing zeros from y-axis labels
Figure 3.4e Eliminate diagonal text on x-axis
Figure 3.4f Thicken the bars!
Figure 3.4g Pull data labels into ends of bars
Figure 3.4h Eliminate data labels
Figure 3.4i Make it a line graph
Figure 3.4j Label the data directly
Figure 3.4k Make data labels the same color as the data
Figure 3.4l Upper-left-most orient graph title
Figure 3.4m Remove title color
Figure 3.4n Put the goal in the graph
Figure 3.4o Iterating: different formatting for Goal line
Figure 3.4p My favorite of the Goal line iterations
Figure 3.4q Remove color
Figure 3.4r Focus attention
Figure 3.4s Focus attention elsewhere
Figure 3.4t Introduce a bit more color to really direct attention
Figure 3.4u Focus attention on yet another takeaway
Figure 3.5 Which Gestalt principles are in play?
Figure 3.7 How can white space & alignment improve this visual?
Figure 3.8 Let’s declutter!
Figure 3.9 Let’s declutter!
Figure 3.10 Let’s declutter!

Chapter four

Figure 4.1a Where are your eyes drawn?
Figure 4.1b Where are your eyes drawn?
Figure 4.1c Where are your eyes drawn?
Figure 4.1d Where are your eyes drawn?
Figure 4.1e Where are your eyes drawn?
Figure 4.1f Where are your eyes drawn?
Figure 4.2a Let’s focus attention in this graph
Figure 4.2b Focus on Lifestyle brand line
Figure 4.2c Focus on Feline brand line
Figure 4.2d Focus on decreasing brands
Figure 4.2e Focus on the brands that most decreased
Figure 4.2f Focus on increasing brands
Figure 4.2g Comprehensive slide #1: Lifestyle and Feline brands
Figure 4.2h Comprehensive slide #2: decreasing and increasing brands
Figure 4.3a How could we focus attention on the Referral line in this graph?
Figure 4.3b The “look here” arrow
Figure 4.3c Circle the data
Figure 4.3d Cover everything else up with transparent white boxes
Figure 4.3e Highlighting the transparent white boxes
Figure 4.3f Thicken the line
Figure 4.3g Change the line style
Figure 4.3h Make it darker
Figure 4.3i Position in front of other data
Figure 4.3j Change the hue
Figure 4.3k Use title words to prime audience
Figure 4.3l Eliminate the other data
Figure 4.3m Add data markers
Figure 4.3n Add data labels
Figure 4.3o Employ end markers and labels
Figure 4.3p Combine multiple preattentive attributes
Figure 4.4a Bank index
Figure 4.4b Can show all the data if we push most of it to the background
Figure 4.4c Could focus on latest year-to-year period of time
Figure 4.5a Where are your eyes drawn?
Figure 4.5b Where are your eyes drawn?
Figure 4.5c Where are your eyes drawn?
Figure 4.5d Where are your eyes drawn?
Figure 4.5e Where are your eyes drawn?
Figure 4.5f Where are your eyes drawn?
Figure 4.6 Practice focusing attention within this table
Figure 4.7 How could we direct attention to Our Product in this graph?
Figure 4.8 How can we focus attention on above average medical centers?

Chapter five

Figure 5.1a Could we use words more wisely?
Figure 5.1b Clear title text aids understanding
Figure 5.1c Different text could lead to completely different interpretation
Figure 5.2a Default output from tool
Figure 5.2b Remade visual
Figure 5.2c Presenting on a single slide
Figure 5.3a Your colleague’s original slide
Figure 5.3b Redesigned graph with greater attention to detail
Figure 5.3c Graph the data as lines
Figure 5.3d Change x-axis to monthly calendar year to better see seasonality
Figure 5.3e Change x-axis to run from July to June
Figure 5.3f My redesigned slide
Figure 5.4a Graph with storytelling with data branding
Figure 5.4b Branding inspired by United Airlines
Figure 5.4c Branding inspired by Coca Cola
Figure 5.4d Less ink-heavy background
Figure 5.6 Your original slide
Figure 5.7 How could we improve this?
Figure 5.8 Brand this!
Figure 5.9 Use words wisely

Chapter six

Figure 6.1 What’s the story?
Figure 6.2a Put it into words
Figure 6.2b Modify the data so we can stack it
Figure 6.2c Change to stacked 100% bars
Figure 6.2d Let’s change to stacked area
Figure 6.2e Put it into words!
Figure 6.4a The narrative arc
Figure 6.4b Back-to-school shopping narrative arc
Figure 6.5a The narrative arc
Figure 6.5b Pet adoptions narrative arc
Figure 6.6a Time to fill
Figure 6.6b Skeleton graph
Figure 6.6c Introduce goal
Figure 6.6d First point of external line
Figure 6.6e External time to fill increased in first half of year
Figure 6.6f External time to fill varied in second half of year
Figure 6.6g Add first point of internal line
Figure 6.6h Internal time to fill low first few months of year
Figure 6.6i Increased April to May
Figure 6.6j Another dip and increase
Figure 6.6k Yet another dip and increase
Figure 6.6l Internal ends the year above external
Figure 6.6m Let’s discuss the implications looking forward
Figure 6.6n Fully annotated view to be distributed
Figure 6.7a Project dashboard
Figure 6.7b Story on a single slide
Figure 6.9 University elections colleague’s storyboard
Figure 6.11 Key Metrics
Figure 6.14 The narrative arc

Chapter seven

Figure 7.1a Advertisers are getting more sophisticated sooner
Figure 7.1b Quick and dirty views of data
Figure 7.1c Sophistication increasing with time & age
Figure 7.2a Sales channel update
Figure 7.2b Visualize units sold over time with a line
Figure 7.2c In a live progression, first set up graph
Figure 7.2d Live progression
Figure 7.2e Live progression
Figure 7.2f Live progression
Figure 7.2g Live progression
Figure 7.2h Live progression
Figure 7.2i Live progression
Figure 7.2j Live progression
Figure 7.2k Live progression
Figure 7.2l Annotated line graph
Figure 7.2m Another view: channel breakdown
Figure 7.2n Focus on retail
Figure 7.2o Focus on e-commerce
Figure 7.2p Focus on direct mail
Figure 7.2q Focus on partner
Figure 7.2r The desired shift in channels has happened: success!
Figure 7.2s Single slide for distribution
Figure 7.3a Model performance by LTV
Figure 7.3b Pull the data apart into two graphs
Figure 7.3c First, set the stage
Figure 7.3d Actual prepayment doesn’t vary by LTV
Figure 7.3e Model overpredicts at low LTVs and underpredicts at high LTVs
Figure 7.3f Distribution of loans across the portfolio
Figure 7.3g Add prepayment back to graph
Figure 7.3h Model over-predicts prepayment at low LTVs
Figure 7.3i Model under-predicts prepayment at high LTVs
Figure 7.3j Annotate important points directly on slide
Figure 7.4a Back-to-school shopping survey results
Figure 7.4b Scatterplot
Figure 7.4c Line graph
Figure 7.4d Vertical bars
Figure 7.4e Horizontal bars
Figure 7.4f Sort ascending
Figure 7.4g Sort descending
Figure 7.4h Decluttered graph
Figure 7.4i Focus attention
Figure 7.4j Add words
Figure 7.4k My Big Idea summarized in a pithy, repeatable phrase
Figure 7.4l Back up and set the plot
Figure 7.4m What we’ll cover today
Figure 7.4n Set up the graph
Figure 7.4o Focus on our business
Figure 7.4p Focus on highest scoring items
Figure 7.4q Focus on lowest scoring items
Figure 7.4r Add competitor data
Figure 7.4s Highlight where we underscore competition
Figure 7.4t Shift from focus on absolute to difference
Figure 7.4u Focus on items we outperform
Figure 7.4v Focus on items we underperform
Figure 7.4w Underperform the most in promotions
Figure 7.4x Recommend focusing on areas we can control
Figure 7.4y Repeat my Big Idea summarized in a pithy, repeatable phrase
Figure 7.4z Final annotated version
Figure 7.5a Diabetes rates by medical center
Figure 7.5b My initial storyboard
Figure 7.5c My storyboard arranged along the narrative arc
Figure 7.5d My visual completed for end-of-day fire drill request
Figure 7.5e A question to ponder
Figure 7.5f Start by setting the stage
Figure 7.5g Overall diabetes rate was 7.2% in 2015
Figure 7.5h There were 8 centers with rates higher than overall
Figure 7.5i There were 5 centers with relatively low diabetes rates
Figure 7.5j Diabetes rate across our medical centers is 8.6% in 2019
Figure 7.5k Medical centers having relatively high diabetes rates increased
Figure 7.5l Those centers having lower diabetes rates also increased
Figure 7.5m This is a consistent rise of 0.5 points per year
Figure 7.5n We project a continued increase
Figure 7.5o This implies 14,000 more patients with diabetes per year
Figure 7.5p Annotated slide to distribute
Figure 7.6a Typical graphs presented in monthly meeting
Figure 7.6b Narrative arc
Figure 7.6c Title slide
Figure 7.6d Goal today
Figure 7.6e NPS: flat to increasing over time
Figure 7.6f We rank 4th against the competition
Figure 7.6g Let’s look at NPS components
Figure 7.6h Proportion of passives decreasing
Figure 7.6i Proportion of promoters increasing
Figure 7.6j Proportion of detractors increasing
Figure 7.6k Detractors: nearly doubled since Aug
Figure 7.6l Detractors: relatively more comments
Figure 7.6m Comments provide insights into issues
Figure 7.6n Recommendation

Chapter eight

Figure 8.1 Program hiring highlights
Figure 8.2 Sales by region
Figure 8.3 Revenue forecast
Figure 8.4 Adverse events
Figure 8.5 Reasons for leaving
Figure 8.6 Accounts over time
Figure 8.7 Errors & complaints
Figure 8.8 Taste test data
Figure 8.9 Encounters over time by type
Figure 8.10 Your original graphs

Chapter nine

Figure 9.6 Example assessment rubric

introduction

I often receive emails from people who have read my first book, storytelling with data, or attended one of our workshops by the same name. There are notes of encouragement, support for the work we’re doing, and plenty of questions and requests. I especially love hearing the success stories: reports of having influenced a key business decision, spurred an overdue budget conversation, or prompted an action that positively impacted an organization’s bottom line. The most inspiring accounts are those of personal growth and recognition. One grateful reader applied storytelling with data principles during an interview, helping him land a new job. All of this success is the result of people from different industries, functions, and roles committing time to improve their ability to communicate with data.

I also hear regularly from people who want more. They’ve read the book and understand the potential impact of telling stories with data, but struggle with the practical application to their own work. They have additional questions or feel they are facing nuanced situations that are keeping them from having the desired impact. It’s clear that people crave more guidance and practice to help fully develop their data storytelling skills.

Others reach out who are—or would like to be—teaching the lessons outlined in storytelling with data. In many cases, they are university instructors (it’s amazing to think that storytelling with data is used as a textbook at more than 100 universities around the world!) or they are a part of a learning and development function within an organization, interested in building an in-house course or training program. There are also leaders, managers, and individual contributors who want to upskill their teams or provide good coaching and feedback to others.

This book addresses all of these needs for individuals, teachers, and leaders. By sharing invaluable insight through many practical examples, guided practice, and open-ended exercises, I will help build your confidence and credibility when it comes to applying and teaching others to apply the storytelling with data lessons.

How this book is organized & what to expect

Each chapter starts with a brief recap of the key lessons that are covered in storytelling with data. This is followed by:

practice with Cole: exercises based on real-world examples posed for you to consider and solve, accompanied by detailed step-by-step illustration and explanation

practice on your own: more exercises and thought-provoking questions for you to work through individually without prescribed solutions

practice at work: thoughtful guidance and hands-on exercises for applying the lessons learned on the job, including practical instruction on when and how to solicit useful feedback and iterate to refine your work from good to great

Much of the content you’ll encounter here is inspired by our storytelling with data workshops. Because these sessions span many industries, so do the examples upon which I’ll draw. We’ll navigate between different topics—from digital marketing to pet adoption to sales training—giving you a rich and varied set of situations to learn from as you hone your data storytelling skills.

Warning: this is not a traditional book that you sit and read. To get the most out of it, you’ll want to make it a fully interactive experience. I encourage you to highlight, add bookmarks, and take notes in the margins. Expect to be flipping between pages and examples. Draw, discuss with others, and practice in your tools. This book should be beat up by the time you’re done with it: that will be one indication that you’ve utilized it to the fullest extent!

How to use this book in conjunction with the original

SWD: let’s practice! works as a great companion guide to storytelling with data: a data visualization guide for business professionals (Wiley, 2015; henceforth referred to as SWD). It will not replace the in-depth lessons taught there, but rather augment them with additional dialogue, many more examples, and a focus on hands-on practice.

This book generally follows the same chapter structure as SWD with a couple of differences, as shown in Figure 0.1. Chapters 7, 8, and 9 are comprehensive exercises that offer additional guidance and practice applying the lessons covered throughout SWD and here.

Image shows the comparisons of chapters between SWD: original book and SWD: let's practice! Both the books consist of 10 chapters. Chapters one to five and 10 of both books represent the similar thought. Both books first chapter states about the importance and understanding of the main context; the second chapter of both the books discuss about choosing an effective visual; the third chapter is about eliminating the clutter; fourth related to focus attention; fifth states the topic “think like a designer.” The sixth, eight, and ninth combined chapters of SWD: original book is related to chapter 7 of SWD: let's practice! All related to practice more with Cole. The seventh chapter of SWD: original book is related to sixth SWD: let's practice! Chapter (lessons in storytelling). Chapter 10 states about the final thoughts. — **Figure 0.1** How *SWD* chapters correspond to this book

If you’ve picked up both SWD and SWD: let’s practice!, you can use them in a couple of ways. You can read SWD once from start to finish to understand the big picture before digging into specifics. From there, you can determine which lessons you’d like to practice and can dive into the relevant sections within this book. Alternatively, you can peruse SWD one chapter at a time, then turn here to practice what you’ve read through hands-on exercises.

If you’ve already read SWD, feel free to jump right in as you will be familiar with these topics.

And if you’ve only bought this book, there is enough context within to give you the basics. You can always pick up a copy of SWD or check out the many resources at storytellingwithdata.com for supplemental guidance.

Do you want to learn or teach?

SWD: let’s practice! was written with two different audiences in mind, united by a common goal—to communicate more effectively with data. Broadly, these two distinct groups are:

Those wanting to learn how to communicate more effectively with data, and
Those wanting to provide feedback, coach, or teach others how to communicate more effectively with data.

While the content is relevant for both groups, there will be subtle differences when it comes to getting the most out of it. Depending on your goal, the following strategies will maximize efficiency.

I want to learn to communicate more effectively with data

Because some later content builds upon or refers back to earlier content or exercises, begin with Chapter 1 and work through in numerical order. After that, you’ll likely find yourself revisiting sections of interest and focusing your practice based on your specific needs and goals.

Start by reviewing the lesson recap for a given chapter. If you encounter anything that isn’t familiar and you have access to SWD, turn back to the corresponding chapter for additional context.

After that, move straight into the practice with Cole exercises. First, work through each on your own—don’t just jump to the solution (you’re only cheating yourself!). If you’re using this book with others, many of these activities lend themselves well to group discussion. The exercises in this section don’t necessarily need to be worked through in order, though they do occasionally build upon prior exercises.

Once you’ve spent time on the given exercise (not just in your head: I strongly encourage you to write, draw, and use your tools), read through the provided solution. Observe where there are similarities and differences between that and your response. Be aware that there are very few situations where there is a single “right” answer. Some approaches are better than others, but there are usually numerous ways to solve a given problem. My solutions illustrate just one method that applies the lessons covered in SWD. Do read through all of the solutions, as many points of advice, tips, and nuances will arise that you will find helpful and insightful.

After completing the practice with Cole exercises, turn to the practice on your own section for more. These problems are similar to those in the first section, except that they don’t include any predetermined solutions. If you are working in a group, have individuals first tackle a given exercise separately, then come together to present and discuss. Invariably, different people approach exercises in distinct ways, so you can learn a good deal through this sharing process. Conferring with others is also great practice for talking through your design choices and decisions, which can further clarify thinking and help improve future application. Whether completing on your own or as part of a group, get feedback on your recommended approach. This will help you understand if what you propose is working, as well as where you can iterate to further improve effectiveness.

If, at any time, you find yourself with a current project that would benefit from applying the lessons outlined in a specific chapter, flip straight to the practice at work exercise section within that chapter. These contain guided practice that can be applied directly to real-world work situations. The more you practice implementing the various lessons in a work setting, the more they will become second nature.

Each chapter ends with discussion questions related to the lessons. Talk through these with a partner or perhaps even use as the basis of a larger book club conversation.

While the exercise sections in each chapter focus primarily on applying the given lesson, Chapters 7, 8, and 9 offer more comprehensive examples and exercises for applying the entire storytelling with data process. Chapter 7 (“practice more with Cole”) contains full-blown case studies presented for you first to solve, followed by my thought process for tackling and completing. Chapter 8 (“practice more on your own”) has additional case studies and robust exercises to practice the process without prescribed solutions. Chapter 9 (“practice more at work”) has tips on how to apply the storytelling with data process at work, guides to facilitate group learning, and assessment rubrics that you can use to evaluate your own work and seek feedback from others.

As part of your learning, it’s also imperative that you set specific goals. Communicate these to a friend, colleague, or manager. See Chapter 9 for more on this.

Next, let’s talk about how those interested in teaching others to effectively tell stories with data can use this book.

I want to provide feedback, coach, or teach others

You might be a manager or leader who wants to give good feedback on a graph or presentation from your team. Or perhaps you have a role in learning and development and are building training programs around how to communicate effectively with data. You may be a university instructor teaching students this important skill. In all of these scenarios, the chapter recap will provide an overview of the given lesson. After that, you will likely find the most value in the second and third exercise sections: practice on your own and practice at work. Each chapter ends with discussion questions that can be assigned, incorporated into tests, or used as the basis of group conversations.

The practice on your own section within each chapter contains targeted exercises helping those undertaking them practice the lessons outlined in the respective chapter and relevant section of SWD. These can be used as the basis of hands-on exercises in a classroom setting or assigned as homework. Some will also lend themselves well for use as group projects. These examples are provided without prescribed solutions. The problems in these sections can also work as models: consider where you could substitute data or visuals to create unique exercises.

Practice at work’s guided exercises can be used directly in a work setting as part of an ongoing program for professionals. They can be assigned, completed, and discussed in a group or classroom setting. Managers looking to develop their team’s skills may ask them to focus on specific exercises through their work or projects, or use with individuals as part of a goal-setting or career development process. For those teaching, Chapter 9 has additional practice at work exercises, including facilitator guides and assessment rubrics.

A quick note on tools

Many tools are available for visualizing data. You may use spreadsheet applications like Excel or Google Sheets. Perhaps you are familiar with chart creators such as Datawrapper, Flourish, or Infogram or data visualization software like Tableau or PowerBI. Maybe you write code in R or Python or leverage Javascript libraries like D3.js. Regardless of your tool of choice, pick one or a set of tools and get to know them as best you can so the instrument itself doesn’t become a limiting factor for effectively communicating with data. No tool is inherently good or evil—pretty much any can be used well or not so well.

When it comes to undertaking the exercises in this book, you are encouraged to use whatever means for visualizing the data you have at your disposal. These may be tools you use currently, or possibly one or more that you’d like to learn. The visuals that illustrate the practice with Cole solutions were all created in Microsoft Excel. That said, this is certainly not your only choice and I welcome you to use other tools. We are also adding solutions built in other tools to our online library for you to explore.

On the topic of tools, there are a couple I highly recommend having on hand while reading this book: a pen or pencil and paper. You may consider dedicating a notebook to use as you work your way through the various exercises. Many direct you to write and sketch. There are important benefits to low-tech physical creation and iteration that we’ll explore and practice, which can make the process of working in your technical tools more efficient.

Where to get the data

Downloads for the data throughout this book and for all of the visuals shown in the solutions for the practice with Cole exercises can be found at storytellingwithdata.com/letspractice/downloads.

Let’s get started

There has never been a time in history where so many people have had access to so much data. Yet, our ability to tell stories with our graphs and visualizations has not kept pace. Organizations and individuals that want to move ahead must recognize that these skills aren’t inherent and invest in their development. With a thoughtful approach, we can all tell inspiring and influential stories with our data.

I’m excited to help you take your data storytelling to the next level.

Let’s practice!