Understanding the Value of Stories — Success with Data Storytelling

22 February 2023

By: Cameron O’Rourke?

This work is licensed under the Creative Commons Attribution-NoDerivatives 4.0 International License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nd/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

Overview

Despite the availability of augmented ABI tools, the use of data by non-technical business people remains low. By adopting data storytelling as an organizational discipline rather than as a technology acquisition, data leaders can accelerate the translation of data insights into business outcomes.

Key Challenges

• Organizations continue to struggle to translate data insights into business outcomes despite the increased availability of augmented analytics and business intelligence tools, and the expansion of their use across line of business functions.
• Barriers to the realization of data value (which include access to analytic systems, limited data comprehension, and competition for attention) persist with up to 65-70% of employees reliant on prepared insights.
• Attempts to bridge the gap with overhyped audiovisual features and automation have met with limited success, leading to disillusionment around the concept of “data storytelling”.

Recommendations

• Data practitioners must view the barriers to data comprehension and data-informed decision-making as an organizational challenge as opposed to a technical or platform challenge.
• Assign members of your data and analytics team to nurture a storytelling discipline throughout the organization. Focus on building strong narratives that cut through the noise, increase reach and comprehension, and create measurable impact.

Introduction

Catherine, a seasoned and well-respected data scientist, had been working for days (and many nights) to uncover the root cause of the company's waning customer base. She had spent countless hours pouring over data, analyzing trends, and creating undeniable correlations. Her conclusions were air-tight, and her call to action was clear. She was ready to present her findings at the company's quarterly meeting.

However, as she began to present her facts and figures, she realized that her audience wasn't engaged. The senior people at the meeting listened politely, but their attention began to wane. When she finished her presentation, she was met with a simple "thank you" and "we'll take this under consideration." Catherine was heartbroken. All of her hard work had fallen flat. She knew that she had the answer to the company's problem, but no one was really listening.

What Catherine had failed to do was to tap into the emotions of the people at the meeting. She had presented her data without context or narrative, and as a result, her insights failed to resonate.

If she had told a story that put a human face on the data, and had highlighted the experiences of individual customers and their struggles, it would have been easier for the senior people at the meeting to relate to the problem and understand the importance of taking action. By weaving together the facts and figures with a compelling narrative that included relatable characters, vivid imagery, and a clear storyline, Catherine could have transformed the dry data into a gripping story that would have captured the attention of her audience. This would have helped the senior people to see the real impact of the customer losses on people's lives, and why it was crucial to take action to address the issue.

Catherine learned a valuable lesson that day: sometimes, the numbers aren't enough. To make an impact, you have to tell a good story.

Analysis

Barriers to pervasive data-informed decision-making

Despite a multitude of analytics and business intelligence (ABI) tools available to help non-technical business people access data, the use of these tools by employees (as of 2022) is still frustratingly low, with estimates ranging from 30% to 35% on average. (2)

Augmentation (the incorporation of AI into data management and analysis tasks) has been at the forefront of the industry conversation as a way to achieve greater penetration of data-informed decision-making. And indeed, the pool of people generating data insights has expanded beyond just analysts and data scientists, with people across business functions accessing and exploring data on their own. (7)

However, this leaves up to 70% of workers unable to directly access critical data and insights directly. These workers include busy executives (who spend the bulk of their time in meetings or traveling to meetings), people who lack the technical skills needed to query and interpret data, and people who don’t work at a desk. These groups rely on prepared dashboards and reports for decision-making and are often frustrated with the amount and quality of data available to them.

To overcome the gap between data analysts and data scientists who have insights, and the majority of workers who aren’t yet benefitting from these insights, organizations must find ways to break through three barriers:?

• Limited access due to job role. Certain workers are either not able, or not inclined to utilize self-service analytics tools, no matter how augmented they may be. These users need data and insights that come to them, available in their everyday workflows, and placed into the context of their business environment.
• Data literacy and data comprehension. Many workers struggle to comprehend the meaning of data, even when it has been distilled into summarized tables, charts, graphs, and dashboards. Most people who look at raw metrics and statistics can’t understand their significance without context. (19)
• Competing priorities. In today's fast-paced business environment, with a constant flow of information and multiple priorities vying for their attention, it can be challenging to cut through the noise, and get people to focus on the data.

Your organizational data may hold tremendous amounts of potential value, but not an ounce of realized value can be created unless data insights are translated into business outcomes. If the message isn’t understood and isn’t compelling, no one will act on it and no change will occur. (7)

Business storytelling has emerged as a powerful medium for change

In the last decade, storytelling has emerged as a powerful medium for business leaders to engage, teach, and influence audiences.

Stories help to bridge the gap between hard facts and what truly matters to people, allowing audiences to better explore complex topics, internalize key points, and overcome doubts to make informed decisions. (15) This is because stories tap into the emotional center of the brain, increasing engagement, improving comprehension, and most importantly, motivating people to take action.

However, no matter how compelling the stories may be, they must be backed by facts grounded in research and evidence before decisions with real commercial consequences are made. (15)

Data storytelling then, combines data and visualizations of data, with the necessary context to achieve insight, along with a compelling narrative to bring the data to life and make it meaningful and accessible to a wider range of people. (19)

Vendor focus on data storytelling has been around automation

Data storytelling has emerged as part of a broader movement oriented around data literacy, with the goal of explaining and expressing data and analytics in a consumable, engaging and relevant way. (3)

From technology vendors, most of the focus has been on promoting various audiovisual features and content automation features.

Most ABI platforms now include audiovisual features to facilitate the creation and sharing of easily consumable insights, such as annotated dashboards, infographics, incorporation of multi-media, and slideshow-like features (tabs, drawing features, animation.) (3)

Algorithmic content, sometimes called “robotic content,” has been used for years in the generation of natural language content for news, sports reports and digests of voluminous material. In the past few years, improvements in machine learning techniques, such as deep learning and neural networks, have enabled AI to generate text, imagery, and video and audio content. (1)

However, machine-generated data stories tend to be very fact-oriented, if not uninspiring. They may not even gain traction if they are not relevant, understandable or explainable to the intended recipients. (3)

The vendor hype surrounding technologies and features meant to facilitate "data storytelling" has overshadowed the essential principles of story. It's the human element of storytelling that's critical for engaging, comprehending, and retaining information, as well as motivating people to take action. The skill involved in tapping into a core emotion that can motivate people to action has yet to be replicated by technology. ?

Functional capabilities such as data-connected slideshows, annotated dashboards, and infographics have failed to meet inflated expectations, leading to a period of disillusionment with data storytelling as a concept. (3)

Effective business data storytelling focuses on the story

For thousands of years, storytelling has been an integral part of our humanity. Humans are wired for stories. Even in our digital age, stories continue to appeal to us just as much as they did to our ancient ancestors. (7)

Why is it that, while we might forget faces, names, or numbers, we never forget a good story?

• Stories tap into our emotional center. When you package up your insights as a data story, you build a bridge for your data to reach the influential, emotional side of the brain. (7) In his book, Tell to Win, Peter Guber argues that humans simply aren’t moved to action by “data dumps,” dense PowerPoint slides, or spreadsheets packed with figures. People are moved by emotion. (9)
• Stories improve understanding and recall. Chip Heath, a Stanford professor and author of "Made to Stick," found that students who listened to a series of brief topics, each including an average of 2.5 statistics, could not remember a single statistic after ten minutes 95% of the time. However, 63% of the time they could remember the topics that included stories. (8)
• Stories improve engagement. Researchers have discovered that when listening to stories, people tend to drop their intellectual guard, and are often less critical and skeptical of the material. As mathematician John Allen Paulos observed, “In listening to stories we tend to suspend disbelief in order to be entertained, whereas in evaluating statistics we generally have an opposite inclination to suspend belief in order not to be beguiled.” (7)
• Stories are persuasive. Oxytocin is a brain chemical that enhances feelings of empathy, which can help motivate cooperation with others. Studies have found that character-driven stories consistently cause oxytocin synthesis. (6) This can explain why stories are so effective at changing beliefs.
• Stories drive decision-making. Decision makers often ignore data insights, which can be due to how they are delivered. Even if the data sparks interest, it may lack the necessary context to drive a decision. Data storytelling can help overcome this by adding context and making the topics more accessible, thus breaking down managerial inertia and apathy toward the raw data. (3)

Data Storytelling is a multi-disciplinary skill that must be fostered

Some people consider crafting a story around data as unnecessary and time-consuming, believing that clear reporting of insights and facts alone is sufficient to influence decisions. However, this viewpoint is flawed as it assumes that business decisions are based solely on logic and reason.

Neuroscientists have confirmed decisions are often based on emotion, not logic. USC professor Antonio Damasio found that patients with brain damage in the area that helps process emotions had difficulty making basic decisions. Their decision-making skills were significantly impaired by the lack of emotional judgment. Emotions play an essential role in helping our brains navigate alternatives and make decisions quickly. (7)

Data storytelling as a skill involves practices, and behaviors around how data is socialized and used in organizations, including the crafting of contextualized data narratives. Data storytelling draws on a variety of techniques, including data analysis, statistics, data visualization, and qualitative and contextual analysis, as well as effective presentation skills.

However, many organizations do not have these skills in place, making it important for businesses to focus on developing a culture that values and supports the use of data storytelling to unlock the full potential of their data.

The elements of effective data storytelling

Start with a big takeaway message

Having a clear objective in mind helps to focus your narrative and ensure that your data supports your message. Start by defining the problem that you want to solve or the question that you want to answer. Then, think about the key insights that your data can provide and how these insights relate to the problem or question. Finally, identify the big takeaway message that you want your audience to remember, which should be a clear and concise statement that summarizes the insights and their relevance to the problem or question. (15)

Understand your audience’s motivations

One of the biggest mistakes made when it comes to data-driven storytelling is the assumption that data are the central characters of your story. (15)

Even if the insight you derived is groundbreaking, memorable stories almost always revolve around people. This means that your story should either center around your audience or be highly related to them.

Define your audience by asking the following questions:

1. What is the current situation?
2. What problems are being faced?
3. What are the consequences of the situation?
4. What actions can be taken based on your analysis?
5. What impact will these actions have?

Combining the above questions you can come up with a “story formula”: (18)

As a [persona], I’m in [situation] where I face [problem], leading to [consequence]. Solving it by [action] leads to [impact]

Now, you know what story you need to tell, who the audience is, and how you can help them solve their problem.

Be selective in choosing the right data

The famous quote "Brevity is the soul of wit" by William Shakespeare emphasizes the idea that being concise and to the point is the most impactful way to communicate a message.

Ensuring that your audience is not overwhelmed with information so that they can process and internalize your key takeaways is crucial. ?

Be highly selective in choosing reliable and pertinent data sources that align with your story’s objectives. With an abundance of data available, it can be difficult to determine which is most relevant, and this is where clear objectives and your ‘story formula’ come into play.?

Avoid the common and almost universal tendency to be ‘comprehensive’ in your approach. We all desire to be seen as competent, but too much data, too many slides, and too much talking will undermine your primary goal, to create impact and motivate action. Do not dilute your primary message with extra detail – keep this in reserve for when, and if, more detail is requested.

Focus on really understanding what the data is telling you. Move past surface-level metrics and find the correlations or causal links in your datasets that can provide interesting insights and inspire a more compelling and engaging narrative. By doing so, you can ensure that your data story not only informs your audience but also captures their attention and inspires them to take action. (12)

Leverage domain expertise to add context and meaning to the data

Context is an essential ingredient for creating an effective data story. As we have discussed earlier, data on its own is not as memorable or impactful as a rich story. It's critical to weave context and data insights together to give the audience something relatable. This doesn't just mean providing an overview at the beginning before diving into data visualizations. It means framing the data insights with the business reality and any other relevant information that your audience may not otherwise be familiar with. (12)

Business domain knowledge and experience are crucial to finding the stories within the data. Consult with subject matter experts from relevant areas of the business to supplement your own understanding. Search out and recognize the significance of certain patterns, correlations, and outliers that may be hidden to someone who lacks that expertise.

The relationships and patterns that you unearth during this step will contribute to a more compelling and actionable story and drive real business value.

Choose creative and unexpected visualizations

Now that the story has been set, the next step is to intelligently integrate the right data and insights through visualizations.

Think beyond the standard charts and graphs offered by your ABI platform. Engage your creativity and consider how you can showcase your data using color, shape, size, photographs, animation, interactivity and other visual elements to capture the attention of your audience.

The key here is to find a way of communicating the data that is unexpected, but also very clear. Try approaching the data from different angles, looking for patterns or relationships that are not immediately apparent. Experiment with metaphors and analogies to represent data in a relatable way – for example, you could represent a company's revenue as a water flow that can be channeled and directed to different areas. Also, involving others in the process, such as co-workers or subject matter experts, can lead to fresh perspectives and ideas.

Craft a human-centric narrative

Data storytelling is more than just creating an infographic or a visually appealing chart. A narrative must be established, beginning with a question or a conundrum, setting the context, and establishing meaning, relevance, and clarity around the data that leads to a resolution.

One critical thing to keep in mind is to maintain focus on the human element of the story. People connect with stories that evoke emotions and experiences, so it's important to incorporate those elements into the narrative.?

Another important part of storytelling is the creation of a story arc that builds tension and keeps the audience engaged. There are various story frameworks that you can learn about to give your story a recognizable structure such as the Hero’s Journey or Freytag’s Pyramid, but all good stories have one or more of these common elements:

• Curiosity — creating a ‘valley of the unknown’ between what your audience knows, and what it wants to know. This is where you draw your audience’s attention and keep them glued to your words. Once you establish curiosity successfully, your audience will give you their 100% attention to find out the answer to the unknown.
• Characters — Make your story more relatable and connectable by introducing characters. Humans love humans. We seek a human element in everything we come across. The characters don't have to be perfect, but they should be relatable and likable. By doing this, you can build a strong connection with your audience and make your story more effective. (10)
• Tension and Conflict — In order for a story to motivate a desire to change, the story must first sustain attention—a scarce resource in the brain—by developing tension during the narrative. (6) Tension is created by introducing a problem, which sets up a question that the audience wants to be answered. As the story progresses, the tension increases as the problem becomes more complex or as obstacles arise that prevent the characters from resolving the issue. Tension can evolve into conflict, providing an opportunity for characters to struggle, change, and grow, creating a sense of emotional investment in the audience. By introducing tension and conflict, the storyteller is able to guide the audience towards a particular resolution or message, providing a more impactful and memorable experience.

As you build your story, remember to layer your information into the narrative. Audiences gain knowledge incrementally. Every new piece of information should be layered onto something we have already learned before. In terms of story, this can be achieved by compounding builds in visualizations or by sequencing different types of visualizations, or by drilling deeper into the data.

Also, remember to conclude your story with actionable insights or decisions that the audience can immediately act upon.

Recommendations

Here are practical tips to keep top-of-mind as you implement a data storytelling discipline within your organization:?

• Start small with great examples: Begin by identifying a small group with a passion for storytelling and the right combination of skills who can deliver a few great examples and set a high standard. The first few stories will require more time and effort before tools and processes are set.
• Select a passionate storyteller: Whether your story is presented live, or via a recorded video, find a narrator that is not only well-versed in the domain, but that has a clear and engaging speaking voice who can effectively command and direct attention to the key points.?
• Build momentum by feeding curiosity: As others see the impact of these early efforts, assign champions to help drive learning and repeatable processes.
• Remain focused on the audience and their needs: Effective data storytelling is about presenting data in a way that resonates with your audience. This might require some surrender of individual ego and personal ambition. Think first about how to best serve your audience and the broader organization.
• Don’t settle for standard off-the-shelf charts: Aspire to reveal something unexpected during your presentation. Engage visual designers and subject matter experts from other disciplines for inspiration.
• Embrace good storytelling techniques: Data storytelling involves more than just presenting numbers and facts in an engaging sequence. It's about telling a human-centered story supported by data. Borrow storytelling techniques from the world of entertainment, such as creating a narrative arc, incorporating characters and conflict, and using emotion to make your data story more compelling.
• Measure the impact of your data stories: To demonstrate the value of data storytelling, it's important to measure its impact. Establish metrics for success, such as increased engagement or better decision-making, and track these metrics over time.
• Continuously improve and iterate: Data storytelling is an iterative process. Continuously seek feedback from your audience, analyze the impact of your data stories, and look for ways to improve and refine your approach.

Summary

Many well-researched, bold, and incredible data insights will fail to propel business decisions and actions if not successfully molded into data stories. (7) Uncovering key insights is one skill and communicating them is another—both are equally critical to deriving value from the data your business is now amassing. Data storytelling represents an exciting, new field of expertise where art and science truly converge.

Evidence

(1) David Pidsley and James Richardson, Data Storytelling: Analytics Beyond Data Visualizations and Slideshows (Gartner, 19 July 2021, G00744079)

Focuses on automated story generation.

(2) David Pidsley, Market Guide for Augmented Analytics (Gartner, 11 O ctober 2022, G00755258)

(3) Peter Krensky, Hype Cycle for Analytics and Business Intelligence, 2022 (Gartner, 14 July 2022, G00770971)

(4) Shaurya Rana, Communicate Insights Effectively With Augmented Data Visualization and Storytelling (Gartner 16 November 2021 - ID G00757349)

Has sections on choosing visualizations, choosing the right metrics, and some data literacy basics (under the heading of ‘Data Types and Correlations’). Also see ‘Plotline for Analytic Data Storytelling’.

(5) Akshay Jhawar, Philip Allega, Ed Gabrys, Storytelling for Enterprise Architecture: How to Persuade Leaders of EA’s Value in Decision Making (Gartner Refreshed 31 January 2023, Published 20 February 2020 - ID G00466751)

See ‘Use a Simple Three-Act Storytelling Structure to Increase Your Persuasion Power’

(6) Paul J. Zak, Why Your Brain Loves Good Storytelling, (Harvard Business Review, October 28, 2014) https://hbr.org/2014/10/why-your-brain-loves-good-storytelling

(7) Brent Dykes, Data Storytelling: The Essential Data Science Skill Everyone Needs (Forbes, 2016) https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/

(8) John Zimmer, Making it Stick: Tell stories (Blog: Manner of Speaking, October 13, 2009) https://mannerofspeaking.org/2009/10/13/making-it-stick-tell-stories/

(9) Jonathan Gottschall, Why Storytelling Is The Ultimate Weapon (FastCompany, May 2, 2012) https://www.fastcompany.com/1680581/why-storytelling-is-the-ultimate-weapon

(10) Jeremiah O’Brian, 5 C’s Of Storytelling (Emerge, June 18, 2022) https://emergeglobal.us/5-c-of-storytelling/

(11) Brian G. Peters, 6 Rules of Great Storytelling (As Told by Pixar) (Medium, March 21, 2018) https://medium.com/@Brian_G_Peters/6-rules-of-great-storytelling-as-told-by-pixar-fcc6ae225f50

(12) Thoughtspot, How to Tell a Story With Data: Steps, Tips and Examples for Leaders (Thoughtspot, January 11, 2023) https://www.thoughtspot.com/data-storytelling

(13) Lindy Ryan, 5 Steps to Visual Data Storytelling to Make Data Easier to Understand (Database Trends and Applications, June 7, 2016) https://www.dbta.com/BigDataQuarterly/Articles/5-Steps-to-Visual-Data-Storytelling-to-Make-Data-Easier-to-Understand-111512.aspx

(15) Data-Driven Storytelling: 6 Steps To Explore, Enchant and Engage (Unscrambl.com, June 8, 2021) https://unscrambl.com/blog/data-driven-storytelling-guide/

(16) Bronwyn Fryer, Storytelling That Moves People (HBR, June 1, 2003) https://hbr.org/2003/06/storytelling-that-moves-people

(17) Margaret Atwood, Writing 101: What Is the Hero’s Journey? 2 Hero’s Journey Examples in Film (MasterClass, September 3, 2021) https://www.masterclass.com/articles/writing-101-what-is-the-heros-journey#what-is-the-heros-journey

(18) Sunil Sharma, How to Create Data Stories in 4 Easy Steps (Gramener, January 6, 2020) https://blog.gramener.com/easy-steps-to-data-storytelling/

(19) The Importance of Data Storytelling (James Cook University, June 16, 2022) https://online.jcu.edu.au/blog/the-importance-of-data-storytelling

(20) Laurie Gilbertson, How To Do Effective Business Storytelling According To Former Prosecutor (Talaera, April 11, 2022) https://blog.talaera.com/business-storytelling

(21) Kai Tomboc, The Power of Business Storytelling: Hear Ideas From 9 Experts (Piktochart, March 16, 2022) https://piktochart.com/blog/power-business-storytelling/