As information plays an increasingly important role in describing contexts and shaping decisions, data storytelling is being acknowledged as a key practice for innovators and managers. Case studies, visuals, and frameworks for effective data-driven communication are explained in the well-illustrated book by Nancy Duarte, Data Story: Explain Data and Inspire Action through Story.
Nancy Duarte is a communication expert and consultant, and author of bestsellers like Resonate: Present Visual Stories that Transform Audiences; and Slide:ology: The Art and Science of Creating Great Presentations. Her firm, Duarte Inc., is a leading design agency in the Silicon Valley. The book spans 225 pages, and is well-illustrated with charts and figures. Here are my key takeaways from the book, summarised in the four sections below. See also my reviews of the related titles The Power of Data Storytelling and Stories for Work, as well as YourStory’s Changemaker Story Canvas and Pitch Tips for Startups. I. Foundations: from data to decisions “Storytelling makes the brain light up in a way no other form of communication does,” Nancy begins. Stories engage our senses, create connections, evoke emotions, and move us to act. They build common ground with the audience, and bring them into the centre of the narrative via empathy. “Data doesn’t speak for itself; it needs a storyteller,” Nancy emphasises. Storytelling helps audiences recall, retell and even react to the communication. Stories add emotional and human components to factual and objective data. Effective communication for founders and leaders depends on their ability to help audiences explore existing data, explain their viewpoint and recommendations, and inspire action. The task for a leader is to build on analysis and move on to advanced problem-solving with creative and critical thinking, Nancy explains. This calls for creativity and mastery of analytical, data, verbal/written/visual communication skills, which comes only with research and practice. Data can be used in three modes: reactive, predictive and proactive. The kinds of decisions made from analysis are generally discrete, operational or strategic. Nancy also observes that outstanding leaders are known to go beyond data to their own gut instincts in decision-making, such as Steve Jobs and Marissa Meyer; their moves have even come across as counter-intuitive. One chapter focuses on the importance of understanding the behaviours, expectations, and communication styles of audiences. For example, using familiar language works for peers, exhaustive preparation is suited for managers, and brief but logical recommendations are best for top executives. Their preferences vary for presentations, conversations, and online/offline communication. The general outcome of the story should be in line with business priorities of increasing profit/revenue, growing market share, reducing time to market, lowering risk, cost cutting, and increasing retention. Also Read 10 trends that would shape the future of data analytics II. Elements of the data story Data storytelling is about using data, stories, and visuals to present a point of view. It should be communicated through full sentences (in a SlideDoc) as well as bullet points (slides), and explain what is at stake if the recommended action is not followed. Nancy presents results of her extensive analysis on word patterns in speeches, right down to the choice of effective verbs, conjunctions, adjectives, adverbs, interjections, and rhetorical questions. The choice of “process or performance verbs” is connected to whether the recommended course of action is continuity, change or termination. Some actions could even be disruptive in impact. A story has patterns of rise and fall, reflected in its three parts: introduction of the context, the ‘messy middle’ with conflicts and complications, and the final resolution. In the case of data storytelling, Nancy suggests beginning with a description of the opportunity or problem that the data reveals. The middle portion should describe the necessary changes, inter-relations, and impacts. The final resolution should explain the rewards and risks of the proposed recommendation. “Proposing a recommendation that combines the familiar structure of story with the strength and credibility of logic will clarify the decision that you are trying to derive from the data,” Nancy explains. The overall communication should have a tree-like structure of actions and sub-actions explaining the what, why, and how of the decision. Connecting phrases can include therefore, as a result, for this reason, this means, and thus we need to. Assumptions, alternatives, and counter-arguments should be factored in as well. One section of the book explains visual simplicity of presentations in the form of clear titles, framing observations, bar charts (ranked and split), and adjectives and adverbs that describe changing trends. Nancy recommends annotations and overlays onto a chart to make certain data points and trends stand out, eg., highlight, label, bracket, delineate, and explode. Colourful techniques like use of bubble charts may look nice, but can also create too much work for the reader to get to the insight, Nancy cautions. The final design calls for a combination of a number of skills. Explanatory SlideDocs, exhaustive documents, and persuasive presentations are some of the communication forms that can be used. They should be structured like magazines or books, beginning with title, table of contents, and executive summary. Panels can summarise key takeaways in each section, slide, or page. Important text can be made to stand out via attributes, highlights, grid breaks, large quotes, and boxes. Also Read Why enterprises must learn to love data III. Relating to data An outstanding section of the book dwells on humanising data points and making them relatable. “Many of the numbers we use today are unfathomable in a tangible sense to the human mind,” Nancy explains, referring to the frequent use of millions and trillions. Numbers should be made relatable to common perceptions of size, distance, time, and speed; weight and height are particularly tricky to understand intuitively at scale. Nancy cites relatable examples for length (card, car lane), area (fields, courts, states), volume (shipping container), time (work hours, time to make popcorn), and speed (road speed limits). For instance, Steve Jobs would hold objects close to his face during presentations so that people could grasp their size. He pulled the MacBook Air out of an envelope to show how thin it was, and compared the iPod to the size of a pocket. Apple showed that better packaging would halve the cargo shipping requirement in terms of number of trucks reduced. Cosmologist Fred Hoyle described astronomical distances in terms of number of hours taken at different driving speeds. The moon can be reached in 4,000 hours if one were to drive up at 60 mph, and the sun in 177 years at 65 mph. IV. Tying it all together: data storytelling American novelist Kurt Vonnegut describes a range of rising and falling emotional arcs in story patterns. For example, stories ending in good fortune can have three arcs: rags to riches (steady rise), man in a hole (fall-rise), and Cinderella (rise-fall-rise). Conversely, stories ending in ill fortune can have the following arcs: tragedy (steady fall), Icarus (rise-fall), and Oedipus (fall-rise-fall). Stories humanise situations by bringing out human elements of heroes and adversaries. The hero could be a customer, employee, partner, donor or patient; the adversary can be a competitor or even a mindset, Nancy explains. She classifies five types of story conflict, depending on whether the heroes are in conflict with another person, society, technology, nature or even themselves. These play out in scenarios like customers not upgrading their devices, where the adversary is poor technology, feature unavailability, or lack of self-confidence. Also Read Ratan Tata posts a startup pitch deck template for entrepreneurs (and other top stories of the week) As another example, sales could be down because the sales team is facing adversaries of poor tools, leadership, or competition. Conversations with stakeholders and research into their contexts can reveal insights about their desires, motivations, and opinions, beyond what data may reveal. Hidden data can be unveiled in a matter that evokes surprise or even suspense. The book ends with a handful of examples illustrating these frameworks in action, though many more examples would have been ideal. For example, MIT’s Rosalind Ricard showed the health benefits of wearables and AI in a TED talk. She humanised the data through real-world stories of children and doctors, and made the audience the hero in her story by showing them how they can bring about positive impacts by using the technology. Al Gore’s documentary on the environmental crisis, An Inconvenient Truth, effectively used slides of data. The use of a scissor lift during the presentation to show how high data points were rising was particularly effective. Scott Harrison, CEO of clean water non-profit The Well, showed how the subscription model for donors was better than an annual donation model. His slides revealed a fall in number of people impacted during a lean year for annual donations, but a pickup once the subscription model was introduced (Cinderella arc). Scott also used relatable models to explain how many people benefitted by comparing their number to the population of cities like New York and San Francisco. Profiles and stories of individual benefactors also humanised the data points. In sum, the book is a valuable guide to the use of data and stories for effective communication. “We rely on data to tell us what has happened, and stories to tell us what it means,” Nancy sums up. The book is packed with a number of inspiring quotes, and it would be apt to end this review with the sample below. Tell me the facts and I’ll learn. Tell me the truth and I’ll believe. But tell me a story and it will live in my heart forever. – Native American proverb An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem. - John Tukey A designer is an emerging synthesis of artist, inventor, mechanic, objective economist, and evolutionary strategist. - R Buckminster Fuller Good design is good business. - Thomas J Watson, IBM Inability to make decisions is one of the principal reasons executives fail. - John Maxwell We need a new generation of executives who understand how to manage and lead through data. - Marc Benioff, SalesForce.com
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