Introduction
Telling stories is an essential element of the human experience. From the earliest days of the oral tradition to modern films, stories have been central to the way information is conveyed. Yet, in today’s business world, data storytelling has often taken a back seat to raw data. In PowerPoint presentations, whiteboard meetings, and elsewhere, the need for speed and efficiency often results in the mere delivery of facts, often incomplete and without context. This, in turn, leads to misunderstanding of data, inevitably resulting in poor decisions and faulty strategies.
Storytelling doesn’t have to come at the expense of productivity. It’s the key to a more effective business model. With modern data management and conditioning, creating stories that draw real meaning out of vast stores of data is proving to be a crucial component of digital transformation.
What is Data Storytelling?
Data storytelling is the art of visualizing insights from data using a narrative form. Traditionally, data visualization comes in the form of a dashboard or a chart, which provides the viewer with an easier way to digest information than digging through raw numbers on a page. The storytelling component is added when we provide context to data, giving a more complete picture and understanding. Context can be added by presenting data in an ordered fashion (chronological or otherwise), adding digestible explanations and viewpoints around what data shows to aid comprehension or suggesting steps to be taken to drive action.
Data storytelling does not have to be overly complex. It can be as simple as two charts side by side, or it can be a lengthy series of interactive graphs, connected text, varying versions of the same chart, comparative images, and a host of other elements. The goal remains the same, however: to guide people through a narrative to reach a more informed conclusion.
The key difference between data storytelling and data visualization is this added context. This context should provide the connecting tissue between each presentation whether pictorial, graphic, or alphanumeric which helps both the viewer and the presenter focus on the broader message being conveyed.
A good way to think of it is as a history lesson. If you ask students to simply memorize endless names of people and places, dates, and events, they will come away with only limited knowledge about the past. If you combine all of these things into an engaging and explained story, students gain a much deeper understanding of what happened, why it happened, and what lessons they can take into their lives.
In a business setting, we can see how visualization can convey a limited message based on relevant data: “All our offices met their goals this month; therefore, we can open a new office.” Using a storytelling approach, however, we can add necessary context, such as: “Every office reached its goal this month after we launched the new incentive program. These were our last expectations and these are the results. We can now open a new office and this is how much growth we anticipate once it is up and running.”
Sure, data storytelling is not suitable for every data presentation. For people who track particular data frequently or daily, an operative dashboard would still work the best.
Maximizing Storytelling’s Benefits
Storytelling has a critical advantage over visualization: without context, information becomes hard to digest, particularly among numerous and diverse audiences. Even in a visual form, data is still data, and can be understood differently by different people. The best use of data storytelling is for audiences that may not be familiar with the presented data or business context. Storytelling is also useful in the current environment of home offices and asynchronous meetings.
Most business intelligence and data visualization platforms are very good at data visualization, but they lack the capacity to place all of the data they present into a cohesive model of understanding. An important aspect is that usually reporting can’t be disseminated across an entire organization. Each business unit tends to pull what it needs in order to satisfy its own mandate without giving much thought to how their use of data affects other units or whether it is helping guide the organization as a whole to a successful outcome.
With a narrative-and-explanation approach, data is placed into a broader and more accurate context in which all viewers can see the beginning, middle, and end of the function that the data supports. Also, additional information about reasoning or next steps creates a greater level of understanding. Knowledge workers are then able to make not just better-informed decisions but decisions that help propel the story the whole story forward.