Figure 17.1 Principles for fact-based storytelling.
“The most important thing about communicating with data is the communication, not the data. And storytelling is the way to do it.”
—Andrew Marritt
Founder, Organization View
Warming his hands on a hot drink in a noisy cafe just off 42nd Street in Manhattan, Jeremy Shapiro, Global Head of Talent Analytics at Morgan Stanley, talked about what’s new in analytics. The conversation was not about new methodologies, new technologies, or even statistical skills. The topic was a critical aspect of analytics, which also happens to be one of the oldest traditions in human history: storytelling. Here’s what Jeremy said during that conversation: “It’s a great feeling when, after your team has worked so hard to develop strong insights, the story comes through loud and clear to someone else, particularly to a leader. People can’t make decisions based on data they don’t understand.”
Given the importance of storytelling in workforce analytics, this chapter discusses the following:
• Principles and techniques for constructing fact-based stories
• A three-step model and other essentials to build effective visualizations
• Understanding your audience and tailoring communications
• The need to keep things simple
People have been telling stories for millennia. The U.S. National Storytelling Network (www.storynet.org) defines storytelling as “an ancient art form and a valuable form of human expression.” In her 2002 Harvard Graduate School of Education article, Deborah Sole describes storytelling as “an ancient and traditional way of passing on complex, multi-dimensional information and ideas through narrative.” Nancy Duarte, a TED Talk storyteller and author of award-winning books on presentation skills, explains that an idea is powerless if it stays inside you: “Maybe some of you have tried to convey your idea and it wasn’t adopted; it was rejected and some other mediocre or average idea was adopted. And the only difference between those two [ideas] is in the way it was communicated.”
Storytelling is not only about passing on wisdom or sharing ideas; in the business environment, it is an agent for change. David Boje, a professor at New Mexico State University, stated in his 2006 Academy of Management Review article, “Storytelling is widely acknowledged as instrumental to organization change, training, strategy, and leadership.” Paul Yost, associate professor at Seattle Pacific University, supported this view in a 2015 paper when he and his co-authors wrote, “storytelling is becoming an increasingly utilized art for leading and managing change.”
Data and insights from workforce analytics can be complex and plentiful. Storytelling, with emotional content and characters, is a great technique for ensuring that the data and insights from workforce analytics projects are memorable. In fact, studies have shown that listeners have better understanding and recall of a speaker’s key points when emotional content and character-driven stories are used. Paul Zak’s 2014 Harvard Business Review article “Why Your Brain Loves Storytelling” is a good first article to read on this topic.
With better understanding, we increase the chances of action—and that is, after all, why we undertake workforce analytics projects. That action could be to change something or to actively decide to continue doing things as they are. Either way, storytelling can ensure that recommendations are discussed, understood, endorsed, and implemented. Christian Cormack, Head of HR Analytics at AstraZeneca, illustrated this point when he summarized one of his analytics projects: “We looked historically at the turnover in one business. It was very low and the management thought that was a good thing, until we showed them what the potential impact was, such as an inability to refresh talent and bring in new ideas. If we had just shown the turnover numbers, it would have looked like there was no problem. But we didn’t—we told a story, and that meant we created impact.”
Furthermore, the very process of developing the story for workforce analytics communication can clarify the business problem. Josh Bersin, Principal and Founder of Bersin by Deloitte, goes even further: “If you are an analyst and can’t turn your project into a story, then you really don’t know the problem yet.”
People often associate stories with fiction, whether a book, a film or some other media. However, storytelling with data must not be fictitious; it is, and should be, fact based. The following principles (see Figure 17.1 for illustration) are designed to guide how the analytics practitioner communicates with data through storytelling.
Figure 17.1 Principles for fact-based storytelling.
• Principle 1: Educate, don’t fabricate. Storytelling with data in workforce analytics is about presenting facts using words and images that convey a message to the audience. It is not about embellishing the facts, concocting information that does not exist, or selectively omitting information. In summary, don’t make things up and don’t leave out relevant information.
• Principle 2: Enlighten, don’t overwhelm. Storytelling in workforce analytics should highlight key insights and associated recommendations. Your audience does not need to know about all the excruciating details and multiple iterations of your analysis; present just the most relevant. In summary, don’t show up with a 40-page presentation when 3 pages will suffice.
• Principle 3: Convince, don’t confuse. Storytelling in workforce analytics is about informing decision making and guiding your audience convincingly by clearly stating the actions needed. It is not about confusing the audience by leaving them overwhelmed and directionless. In summary, don’t leave your audience wondering what to do.
These principles are a guide to help ensure that professionalism is maintained and the story stays true to the data.
Good stories told well leave the audience with the impression that storytelling is easy. It is not. A well-told story is based on logical, sound construction, which takes time and good planning. Table 17.1 summarizes four techniques for constructing a story. These are not necessarily sequential. They provide simple and effective guidance for the fact-based analytics storyteller. For more ideas, Akash Karia’s book TED Talks Storytelling: 23 Storytelling Techniques from the Best TED Talks (CreateSpace Independent Publishing Platform, 2015) is a helpful reference.
Table 17.1 Techniques for Storytelling with Data
Workforce analytics projects are conducted for a reason, so an essential element of a story is to convey that rationale. This does not necessarily need to be done at the start of the story, but outlining the business situation at some point helps the audience understand why the project was needed. In addition, providing context prevents the audience from being distracted while trying to discern what the project is about.
Context can include elements such as the geographical scope of the project, the business situation, the marketplace, the number of employees affected, the sponsor, or the business units impacted. This is not an exhaustive list, but these examples all help to frame the business situation and set the scene. Figure 17.2 provides an example of this technique in the context of a workforce analytics project on leadership retention.
Figure 17.2 An example of setting the scene.
Andrew Stanton, the scriptwriter for Pixar films such as Toy Story, said in his 2012 TED Talk, “Make me care—aesthetically, emotionally, intellectually.” Effective storytellers of analytics projects create an emotional connection between their audience and the project. Two factors are key to achieving this-making it relatable and revealing detail and intrigue:
• Make it relatable. By describing a worker as the character of your story, you personalize it to your business. This makes the story relevant and real to the audience. Where possible, tell the story from the perspective of a specific (but, ideally, fictitious) worker, whether that is a manager, an employee, a scientist, an administrator, or a call center operator. One way to do this is to create a persona, a technique that marketing and design professionals use to great effect. Give the person a fictitious name and characteristics that bring them to life without revealing the name and details of a real person. A persona could also be an amalgamation of several people in the organization. Figure 17.3 demonstrates this approach in the description of an executive in an analytics project focused on leadership retention.
Figure 17.3 An example of making a story relatable by using a persona.
• Reveal detail and intrigue. Effective stories provide detail that is both interesting and striking. In George Orwell’s dystopian novel Nineteen Eighty-Four, the opening paragraph helps draw the reader in with detail and intrigue: “It was a bright cold day in April, and the clocks were striking thirteen.” Scriptwriter Andrew Stanton also suggests, in his “Clues to a Great Story” TED Talk, revealing information progressively. He describes it as his Unifying Theory of 2 + 2: “Don’t give the audience four, give them 2 + 2.” The theory is that the story needs to be told sequentially with emotional elements that unfold to lead the audience along a journey. In other words, don’t just give your audience the destination; take them on the journey, too.
Figure 17.4 shows how to add detail to a personalized story.
Figure 17.4 An example of adding detail and intrigue.
Although personalization, intrigue, and detail make a story come alive, too much technical detail can reduce the impact of your story, especially if you are communicating with nontechnical people. Michael Bazigos, Managing Director and Global Head of Organizational Analytics & Change Tracking, Accenture Strategy, explains: “Avoid using the language of statistics, even though that’s what underlies the analysis.” Patrick Coolen, Manager of HR Metrics and Analytics at ABN AMRO, agrees: “We always think about how we’re going to present our insights to each different audience. We leave out all of the technical information. We work with strong visuals and add personal details to create the emotional bond.”
All great stories have conflict, whether that is the hero fighting against a villain to save the world, someone overcoming an evil force or natural disaster, or just an individual overcoming hardship with a view to a better life.
In workforce analytics, describing a conflict in the business can similarly enhance your story. Use these kinds of questions to identify your own business conflicts:
• What created the situation that compelled you, as the analytics professional, to undertake the project?
• What is contributing to a substandard business scenario?
• What people factors are holding back the business from growth or increased profitability?
• What is negatively impacting customer satisfaction? And what are people doing to improve the customer experience?
• Why is market share declining? Why are competitors seemingly doing better?
Christian Cormack from AstraZeneca provided a good example of conflict earlier in this chapter when he talked about challenging the long-held notion that low attrition is always desirable. In contrast, he proposed that insufficient turnover could actually suppress innovation.
Figure 17.5 shows another example of conflict in the ongoing example of the leadership retention project. This example highlights conflicting business objectives.
Figure 17.5 An example of creating conflict in storytelling while still retaining emotional attachment.
Paul Yost, an associate professor at Seattle Pacific University, summarizes the purpose of conflict well: “You need context, your character, a villain, and a main message. Create emotion in how you are going to defeat the villain. Present an inflection point for a compelling argument—for example, if we don’t do it now, the industry will pass us by.”
All good stories have a clear point: a short and memorable message for the audience to retain. In the TED Talks Storytelling book mentioned earlier, this is called the “takeaway,” and it is preceded by the “spark” and the “change.” The spark is what happens when characters realize they can overcome the conflict. The change is what the characters must do to resolve the conflict—they must change their circumstance or their actions. And the takeaway is the point of the story.
Thinking about the spark, change, and takeaway for workforce analytics stories can help you construct your message. Consider the spark as the main insight and the change as the recommendation. Then leave the audience with your main message, the takeaway—and the compelling reason to act on the outcomes of your project. In Figure 17.6, our leadership retention example shows how to outline a call to action using a memorable message.
Figure 17.6 An example of creating a call to action with a memorable message.
When creating your call to action, consider the following questions to help clarify your takeaway message:
• What was the most illuminating insight from the analysis?
• What is the business question, and was it answered?
• Were your hypotheses proven or disproven?
• Overall, if you had to summarize your findings in 20–30 words, what would those words be?
• What one recommendation overall would you make to your chief executive officer if she or he asked you about this project?
Finally, if you need to, get help defining your key message from other people inside or outside the analytics organization, such as internal communications professionals or marketing experts, or from external consultants. Peter Hartmann, Director of Performance, Analytics and HRIS at Getinge Group, takes exactly this approach: “When I need to prepare analytics stories and presentations, I work closely with the corporate communications team, who have the expertise to shape the messages effectively.” You might also want to follow the advice of Simon Svegaard, Business Analytics Manager at ISS: “I connect with people uninvolved with the project, often over lunch, to test out the story and to see whether the messages are clearly understood.”
“As a company, we have distinguished ourselves as the most effective organization at developing technical talent for our competitors.”
A gasp filled the room. Mark Berry, Chief Human Resources Officer at CGB Enterprises,1 paused. He had opened his discussion on retention to the executive committee with this statement. He went on to explain, “We are a training ground—we are the best at bringing people in, training them … and then they go to competitors. We are an exporter of talent to our competitors.”
About three months earlier, Mark had commissioned a project to look at why talent was leaving the company. When he arrived at CGB Enterprises, Inc., he had asked why people were leaving, who was leaving, and how many people were leaving. The executive committee knew that there was a problem, but nobody had any facts or insights from which to make decisions. Mark’s project focused on a well-defined business problem, had a clear hypothesis, and was completed with effective analysis using both existing and new data gathered from employees leaving the business. When he was ready, Mark took a steady and thoughtful approach to telling the story. And he effectively articulated his entire project into that one sentence.
The insights were clear: “Technical talent was leaving the company to go to competitors.” The recommendations were also clear, and although the details of the recommendations were articulated later in his presentation, the implication was well communicated: “We need to invest in technical talent.” Finally, Mark’s communication approach of using storytelling emotionally captured the attention of the executive committee.
Mark explained why he chose this approach: “Taking provocative positions when I know I’m right (based on the data) gets the audience emotionally connected and engaged with what I’m talking about. It gets them thinking about the issues the way I want them to think about them.”
One sentence was all it took, Mark says. “After I said that statement and people gasped, I knew the project had been a success.”
Having pictures, or visualization, as part of a workforce analytics story is fundamental to effective communication. Our brains are hardwired to interpret visual information. As James Zull says in his book, The Art of Changing The Brain (Stylus Publishing, 2002), we can cognitively process graphs and images faster than text, which is why visualization is such an efficient means of communication. However, visualization should not replace the story; it should be used to enhance the story, draw attention to data, and more deeply influence some kind of behavior.
Many books and articles delve into visualization with data. Recommended are any of Edward Tufte’s books, although his first book, The Visual Display of Quantitative Information (Graphics Press, 1984), is an excellent and often-quoted text. In addition, the outstanding book Storytelling with Data, by Cole Nussbaumer Knaflic (Wiley, 2015), is a helpful contemporary reference with dozens of tips for effective visual aids. This section does not repeat what those books articulate. Instead, we summarize Edward Tufte’s main elements for graphical excellence and provide a three-step model to help you create visual aids in the context of workforce analytics.
Edward Tufte is known for his pioneering thinking and writing on visual communication of information. His guiding focus is that all visual communication of quantitative information should be characterized by three elements: restraint, simplicity, and impartiality.
• Restraint. Data visualization design should not be dictated by how the visualization can be produced. The design should be conceptualized first, before creating it with technology. This is especially important today, as visualization technology claims to automatically present data in new and exciting ways without the need for any input from analytics practitioners. Be careful not to rely on visualization technology alone. Take time to conceptualize and design the visual on paper first, to keep your message honest.
• Simplicity. Avoid unnecessary visual elements in graphics—what Edward Tufte calls “chartjunk.” An example of chartjunk is gimmicky icons or ornate backgrounds on presentation or report pages. The point is that clean design reflects clear thinking. Do away with unnecessary aspects that distract the audience.
• Impartiality. In addition to simplicity, visual aids should accurately represent the data. Avoid distorting the visual chart or graphic with elements that fail to represent the data properly (for example, misrepresenting data by skewing the axis of a chart unnecessarily). Such elements are not only distracting, but they also misguide the viewer.
Eric Mackaluso, Senior Director of People Analytics, Global HR Strategy & Planning at ADP, provides additional simplicity to Edward Tufte’s advice with his Four C’s technique for preparing communications materials (including graphics) for workforce analytics:
• Make it concise.
• Ensure that it looks clean.
• Be sure it is clear.
• Produce it in a captivating way.
As a final point on graphical excellence, Edward Tufte warned in a 2003 article in Wired that PowerPoint is overused as a tool to represent data: “PowerPoint is a competent slide manager and projector. But rather than supplementing a presentation, it has become a substitute for it. Such misuse ignores the most important rule of speaking: Respect your audience.”
Effective visualizations can bring your story to life. Ineffective visualizations can be distracting and get in the way of clear communication of your message. Producing effective visualizations takes time and effort. The simple three-step model in Figure 17.7 enables a more considered and effective route to building relevant and impactful visual aids.
Figure 17.7 Three-step model for constructing visualizations.
The first step in constructing effective visual aids is to decide on your key message. What key point do you want your audience to take away from this visualization? Make sure the message is clearly reflected in your visualization for the intended audience. The visual aid should accelerate the understanding of your intended message.
The second step focuses on constructing the best visual chart, graph, or diagram for communicating your message. Consider three elements in this design step: selecting the presentation medium, selecting the visualization style, and emphasizing contrasts and similarities.
You need to decide what medium to use to display the visualization and what form the visualization will take. By medium, we are referring to whether the visualization will be viewed on paper or presented on a screen. Furthermore, if it is screen based, consider whether it will allow a viewer to actively explore by scrolling, zooming in and zooming out, or drilling in and drilling out to give greater numerical detail at different levels of analysis (for example, from organizational-level insights down to divisions and teams). You might even have multiple visualizations presented in a dashboard, as in Figure 17.8, which shows levels of employee sentiments and trending topics amalgamated from social sentiment analysis (adapted from Shami, N.S. et al, 2014).
Figure 17.8 Multiple visualizations presented as a dashboard.
The data on which the visualization is based might not be static, but instead gathered from a live data feed. In this situation, you have less opportunity to control the message you want to convey. If exploration of the data is the top priority, then dynamic visualizations make sense. However, if the idea is to convey a specific point, you might prefer static visualizations.
Even with the prevalence of screen-based visualizations, do not discount the paper option. Admittedly, you have fewer opportunities to explore the data, and you might even be limited to a black-and-white presentation (as we are in the print version of this book), but sometimes a simple black-and-white chart is all you need to make your point.
The visual style you select should be informed by your variables. If you have geographical data, some form of map visualization might be appropriate, such as the one in Figure 17.9. This particular figure shows the geographical representation of employee privacy preferences in 24 surveyed countries (light = low privacy preference, medium = moderate privacy preference, dark = high privacy preference).
Figure 17.9 Visualization using a geographical map.
On the other hand, if you have time series data, you might show changes in sales performance, for example, plotted as a function of time. Such a representation would see the time points plotted on the horizontal (x) axis of a graph and sales performance plotted on the vertical (y) axis of the graph.
Figure 17.10 provides an example of a visualization showing a time series model of sales performance for five teams. This reveals variability in performance across the teams but an overall increase in average sales performance over time.
Figure 17.10 Example of a time series visualization.
Note that, with two variables, such as in Figure 17.10, relationships are relatively easy to visualize. The relationships among three variables can be visualized with 3D representations, but more than three variables can be difficult to represent. Analysts often revert to summarizing multiple variables into just two or three variables using the techniques in Chapter 5, “Basics of Data Analysis,” or alternatively, presenting the relationships in tables or correlation matrices.
Many of the most striking visualizations emphasize contrasts or similarities. Continuing with the example of employee privacy preferences, one observation from the original data was that considerable variation existed among countries, in addition to considerable variation within countries. Figure 17.11 shows a visualization that illustrates this, highlighting the difference in worker privacy preferences between India, where workers report being willing to share their personal data for workforce analytics, and Germany, where workers report being less open to sharing their personal data for workforce analytics. This visualization shows the contrast between the typical levels of willingness to share information between people in India and Germany. The graph also clearly highlights the different levels of variation within each country and the area of commonality. Germany has considerably greater variation in willingness to share personal information than India. Graphing the extremes to show ranges in this manner often highlights the point you want to convey in an impactful way.
Figure 17.11 Visualization emphasizing contrasts and the area of commonality.
Finally, after you’ve created your visualization, you need to test it to see whether your intended message is being received accurately. The best way to do this is to solicit feedback about the visualization from people with similar backgrounds to your ultimate audience. At this stage, open questions such as “What message do you take away from this visual?” are a good way to proceed. Answers that match your desired key messages will confirm that you have achieved your objective.
Developing a visualization that successfully conveys your intended message is often an iterative process. If you receive feedback that the visualization is not conveying the message you intended, you need to make amendments and seek feedback again.
Fundamental to the success of your workforce analytics story and the effective use of visualization is understanding your audience. All good communications should be tailored to the audience, and workforce analytics is certainly no exception. Your communications, whether delivered as a story, as a presentation, or in written format, need to be aligned with the motivations and preferences of the audience receiving it.
To align your message to your audience, you need to understand their perspectives and expectations. To do this, think about your audiences in two dimensions: people who have experience with analytical methods and techniques, and people who have experience with the specific project or business issue being analyzed (see Figure 17.12).
Figure 17.12 Types of audience for workforce analytics communications.
• Master. This type of audience has knowledge of both analytics methodologies and techniques, plus a good understanding of the specific analytics project in question. With this group, it is worth sharing more details of the project, as well as insights and recommendations. Furthermore, you can arm them with visuals and stories so they can advocate for the project.
• Enthusiast. This type of audience is knowledgeable about the project but has limited experience with analytics. In communicating with these people, limit the details and use storytelling to create impact. Give an overview of the insights, recommendations, and actions.
• Scientist. This type of audience involves you in a deeper discussion of the analytics methods and techniques used. Limit storytelling and expect statistical discussion on techniques and methods instead of the outcomes. Focus on visuals instead of the story.
• Newcomer. This type of audience knows little about the specific project or about analytical methodologies. Use storytelling to provide emotional attachment. Focus on actions and the business impact by providing context and highlights.
When you have identified the different types of audiences, you can customize the story accordingly. Eric van Duin, Manager of HRIS & Analytics at PostNL N.V., explains: “Look for the insights that will help business or HR executives themselves. It’s really important to keep in mind who you are doing it for and why you are doing it.” Giovani Everduin, Head of Strategic HR, Communications & Change at Tanfeeth, is one of many others to support this point of view and recommends the following approach: “You should pitch the same analytics case differently to different people. It is about tailoring the message effectively.”
Not only the content of the story should be tailored to the interests and motivations of different audiences; the communication style can also be adapted. Consider visual, auditory, and kinesthetic communication preferences and adjust your presentation accordingly. Auditory communication includes the tone and volume of your voice, plus the use of video and music to demonstrate messages. Kinesthetic communications can include using 3D objects created as visualizations for the audience to physically handle something.
You can even ask your audience members for their preferred communication style. Kanella Salapatas, HR Data Manager and Reporting Service Owner at ANZ Bank, offers her audience a choice: “At one point, the CEO asked for some monthly workforce information. Rather than just supplying a report, we gave him three reports of the same information: a traditional PowerPoint presentation, screenshots of data and metrics, and an infographic.” The CEO chose the latter and has since become more engaged on content.
Many workforce analytics practitioners have stressed the importance of tailoring content to the time available. For example, if you only have a few moments in the metaphorical elevator, you had better give your audience the main message quickly.
Antony Ebelle-ebanda has been an analytics professional at several organizations. His mantra for presenting to executives and leaders is, “Make it minimal, make it meaningful.” Regardless of the time allocated, getting your audience interested very early in the allotted time is always a good idea: “The person has maybe 2 minutes to get interested—if you don’t have them hooked in those 2 minutes, you’ll lose them.”
Tailoring your communication to your audience also includes considering who can best present and tell the story. Ralf Buechsenschuss, Global HR Manager of People Analytics & Transformation at Nestlé, says that, in certain meetings with executive stakeholders, he prefers not to have presenters who focus on too much detail. In Ralf’s experience, if those individuals join those meetings, the conversation tends to move away from the insights, recommendations, and actions, and instead stalls on the statistics and analysis. This can disrupt meetings and draw attention to the input instead of the output.
Conversely, in some meetings with certain audiences (for example, the master audience in Figure 17.12), having a statistician join is highly recommended. The skill that these experts can bring adds credibility to the depth of analysis that leads to the conclusions.
Fundamentally, it is important to get the right presenters for your audience. Al Adamsen, Founder and Executive Director of the Talent Strategy Institute, advises: “Understand the needs of your customer, how they consume information, and when they consume it.”
One way to ensure that an executive presentation goes well is to “think like an executive.” Considering what keeps executives awake at night, what business pressures they face, and why this project is relevant to them can build the interest needed for success. Thinking about your executive in the following ways should help:
• Treat your executives like your best customers—understand what they need from you.
• Understand the business from their perspective; workforce issues might not be at the forefront of their minds.
• Try to find out the most important item on their agenda this week, this month, and so on.
• Check their schedule to see what meetings they will have both before and after yours; this can tell you a lot about what might be on their minds.
• Find out about them—learn what makes them tick so that you can personalize your story.
Jonathon Frampton, Director of People Analytics at Baylor Scott & White Health, knows his executives are big Harvard Business Review (HBR) readers, so he developed his HBR theory of communication. He emulates the clear, well-structured, and highly professional content of that journal: “Executives read HBR—they like the style. Good communication is not only about the ability to make it clear; it is also about the listener’s ability to understand. So if we make it HBR-like for executives, then they will understand it.”
This chapter has covered a great deal of material about crafting stories, providing effective visualization, and tailoring your communication to different audiences, but the final word has to be about the importance of keeping things simple.
When you have dedicated weeks or even months to detailed data gathering and analyses, it is tempting to share all that effort with your audience. Don’t. Laurie Bassi, CEO of McBassi & Company, says: “Do not share everything you’ve learned—executives don’t care. Less is more.” She always tries to condense her analytics work to one slide: “No matter how complex the study, I condense insights down to one slide, with one graph that people can immediately understand.”
Thomas Rasmussen, Vice President of HR Data & Analytics at Shell, has had a lot of experience presenting to a variety of audiences. His method for simplification is based on the practice of writing abstracts: “Think of an abstract in a journal. Condense your analytics work down to an abstract. When my team does this, I say, ‘Great, now give me the abstract of the abstract,’ and keep doing that until the message is succinct and clear.”
Making your presentation simple and getting to the point might take some time. Many analytics practitioners say that communicating and preparing for presentations often takes much more time than expected. Whatever time you allow, it is worth doubling the time you think it will take. As the French philosopher and mathematician, Blaise Pascal, wrote in the 17th century, “I have made this letter longer than usual, because I lack the time to make it short.”
Salvador Malo, Head of Global Workforce Analytics at Ericsson, appreciates the time it can take to create great communications: “I tell my own team members to spend as much time on the communication as on the analysis itself. I can spend time making ten versions or more of the communication before I deliver it.”
Practitioners and scholars have been researching the art and science of storytelling for many years. One such scholar is Paul Yost, Associate Professor at Seattle Pacific University. However, he came to understand the value of storytelling not just from his research, but from his own practical experience.
Before his days in academia, Paul was the manager of research and was responsible for, among other things, the employee engagement survey at The Boeing Company.2 There he had two very different experiences with the chief executive officer (CEO) that strongly influenced his approach to storytelling. “One year I went to see the CEO to discuss the employee engagement results. I took a presentation with 35 pages full of charts.” Paul remembers the CEO selecting two charts. He looked at only those two and omitted the rest of the information. “He saw the data and selected those pages that supported his opinion. The rest of the story was lost. I had failed to communicate the results clearly enough for him to pick up the story I was trying to tell.”
The following year, Paul did not want to repeat the same mistake: “The next time, I took just one slide up front.” He said to the same CEO, “I have a limited perspective on the organization; I do not know all about the operations, the finances, etc. But I do know about employee engagement. I am going to show you three things from the data that are important for Boeing.”
Paul learned how to tell the story that he wanted to communicate clearly and simply. The key messages from his presentation had no ambiguity because he signposted them clearly at the beginning: “I am going to show you three things… .” He did not rely on his audience to work out the story behind the 35 slides he was presenting. Paul presented the story, not just the data.
The art of storytelling and visualization with data requires technique and practice. Effective storytelling increases the retention rate of the messages and the likelihood that action will be taken as a result. Visualization helps to create an understanding of the insights and recommendations, and a good understanding of your audience helps you tailor communications to maximize impact. For these reasons, storytelling and visualization are skills that workforce analytics practitioners should practice. Following are the main points this chapter emphasizes:
• Ensure that your stories follow these principles: Educate, don’t fabricate; enlighten, don’t overwhelm; and convince, don’t confuse.
• Create effective workforce analytics stories by providing context, creating emotional impact, revealing the conflict, and conveying a memorable message.
• Construct visualizations that show the intent of your analytics by clarifying the message of your visualization, designing it appropriately, and testing it before you use it with your selected audience.
• Understand the different types of audiences (newcomer, enthusiast, scientist, or master) and tailor your communications accordingly.
• Get help from others in preparing your communication materials if you need it, and strive to keep things simple.
1 CGB Enterprises, Inc., is headquartered in Louisiana and is a privately owned company. It provides an array of services for grain farmers, from buying, storing, selling, and shipping of the crop, to financing and risk management. It has global operations and more than 2,000 employees, and was founded in the 1970s (www.cgb.com).
2 The Boeing Company, headquartered in Chicago, is the world’s largest aerospace company and the leading manufacturer of commercial jetliners and defense, space, and security systems. A top U.S. exporter, the company supports airlines and U.S. and allied government customers in 150 countries (www.boeing.com).