Since their inception, analytics and business intelligence tools have been primarily focused on business reporting, which provides information on the performance of the business to managers and employees. Because there is so much emphasis placed on automated reports and dashboards across these two data-related disciplines, people have become engrained with a reporting mindset.
As psychologist Abraham Maslow once stated, “If all you have is a hammer, everything looks like a nail.” Based on this cognitive bias known as Maslow’s hammer or the Law of the Instrument principle, we humans often reach for a familiar tool even though it may not be appropriate in all scenarios. I have seen this occur with data storytelling as well. People assume they can approach it the same way they have approached reporting—in fact, many feel storytelling can just be sprinkled into their reports or dashboards like pixie dust. This is not true.
Having worked in both fields of analytics (Omniture/Adobe) and business intelligence (Domo), I have built and deployed my fair share of reports and dashboards. Most of the organizations I’ve consulted with have vast collections of reports and dashboards spread across their businesses. I’ve seen organizations that are happy with the greater transparency that reporting has provided their leaders and teams. However, I’ve also seen many executives and teams deeply frustrated with poor reporting.
Recently, I’ve seen strong statements claiming that “dashboards are dead,” and some people have even indicated that data stories will replace dashboards. While there are many poorly designed dashboards that are filled with irrelevant data, part of problem might also come from dashboards being used as hammers—for scenarios that they aren’t well suited. A hammer is a very useful tool but not when you need to tighten a loose screw or cut a piece of wood. Just like a carpenter, you need more than one tool in your analytics toolbox to be effective.
Rather than pitting dashboards and data stories against each other, I see them as serving different purposes and being complementary—not conflicting. To help clarify the relationship between reporting and data storytelling, I developed the following Insight Funnel diagram.
At the top of the Insight Funnel, you will use reports and dashboards to extract relevant, meaningful information from your raw data. From the metrics and dimensions that you strategically choose to monitor in your reports, you begin to “frame” the potential stories that can emerge from the data. At this Storyframing stage, the information is more exploratory in nature as you can interact with the dashboard (filters, drilldowns) to discover potential insights. Alternatively, when you make an interesting observation in a report or dashboard, it may also spur you to do further analysis in other analytics tools or across different parts of the organization to understand why something happened.
Once you uncover a meaningful insight in the data, you may be able to act on it independently if no one else’s buy-in, support, or input is needed. In these situations, a data story is not needed. However, when you have an insight or a set of insights that require a decision or actions that will involve or impact other individuals or teams, that’s when a data story often makes sense as a communication approach. Storytelling is explanatory in nature as you’re helping others to understand the meaning and value of the insight(s) you’re sharing.
Based on the Insight Funnel, dashboards and data stories are complementary. Yes, you don’t necessarily need to start with a report or dashboard before you begin analyzing data. However, often our analyses are triggered by something unusual or interesting we spot in a report or dashboard, which then leads to questions and the need for further discovery.
Now that you understand the two stages of the Insight Funnel and where reports/dashboards and data stories operate, I’d like to compare subtle variances in their approaches. There are at least six ways in which reports/dashboards and data stories are fundamentally different. As you recognize the tactical differences between reporting and data storytelling, it becomes clearer why a reporting mindset will hamper your ability to tell data stories effectively.
Reports and dashboards are primarily focused on describing what has happened or what is about happen (forecasts). Typically, they won’t explain why certain things happened or explore potential contributing factors. On the other hand, data stories are entirely explanatory in nature and are focused on helping people understand the “why” behind the “what.”
Reports and dashboards are usually designed to be comprehensive and provide information on everything that happened. For example, they will provide results for all five business units (regions, product lines, functional areas, etc.) regardless of whether there is anything unusual or extraordinary in the data. In contrast, data stories are fundamentally selective. A data story will focus on the specific metrics and reasons that explain the underperforming business unit—and not include any details about the other four business units that are operating as expected.
Due to their comprehensive coverage, reports and dashboards are primarily focused on summarizing the results at a high level. Sometimes, you can drill into more detail directly within them, but the breadth of the reporting often creates limits on how in-depth you can go. In contrast, the targeted nature of a data story means it may start high level in a specific area but then can go into greater detail to better explain what’s happening.
Reports and dashboards are typically delivered on a recurring cadence—a daily, weekly, monthly, quarterly, or annual basis. Regardless of whether there’s anything compelling to share, an update will be provided at each periodic interval. Meanwhile, data stories are created on an ad-hoc basis whenever there’s an important insight to share. As a result, you could have two data stories in the same week and then none over the next four weeks. It completely depends on you what you find in the data and how urgent or valuable it is to share the insights with others. Unlike dashboards that are constantly refreshing with new data over time, data stories are curated and often limited to a single use. While they can be archived for future reference, they have a limited shelf-life in terms of their actionability.
Reports and dashboards are designed to be factual without any emotion or potential bias. As a result, the data is left to the audience to interpret for themselves without external guidance. The information targets the head only, not the heart. In contrast, data stories are meant to be persuasive and appeal to people’s logical and emotional reasoning—they target both the head and the heart. With the help of narrative elements, data stories engage audiences on a much deeper emotional level, which is an influential aspect of decision-making.
Reports and dashboards are focused on providing information—not insights. Psychologist and author Gary Klein defined an insight as an unexpected shift in the way we understand something. Reporting will mostly generate interesting observations (e.g., our sales increased 200% last week) that can then lead to questions and curiosity about why something happened. It’s extremely rare that a report or dashboard alone will generate insights that “shift our understanding” without the need for deeper data exploration.
On the other hand, data stories contain more than just observations. At the core of every data story is at least one insight. An effective data story will ensure the audience understands the insight and how they should move forward with it. The primary goal is not just to inform the audience but influence a decision, drive action, and inspire change—that’s where the combination of data, narrative, and visuals can be powerful.
If you want to become a better data storyteller, it’s important to recognize the differences in the approach between reporting and data storytelling. While they’re complementary, they require unique skills and distinct approaches. In Marshall Goldsmith’s popular book, “What Got You Here Won’t Get You There,” he talks about making adjustments to your professional style or approach in order to be successful at the next level in your career. Similarly, what made you successful at building reports or dashboards may hinder your ability to become a good data storyteller. Managing this mindset shift will be critical to your future success with data storytelling.
Effective Data Storytelling teaches you how to communicate insights that influence decisions, inspire action, and drive change.