Much has already been written about the role of Artificial Intelligence (AI) in financial services. […]
Human history has proven the power of storytelling, forming an important brick in building large societies (Quest, 2014). There are various theories on how you can make an impact with storytelling and how to reach the audience in your own personal way (Mouton, 2015). That being said, how capable are we of telling compelling stories when data is involved? Translating data into an understandable story is not an easy task due to the increasing size and complexity of data. This is becoming a common challenge as people and organizations use data more frequently.
As we all know, there are many insights hidden in the large amounts of data available these days. The value of this data comes with translating it into relevant insights. According to Stephen Few: ‘These numbers have an important story to tell. They rely on you to give them a clear and convincing voice.” Deloitte has developed a framework to help you gradually guide your audience through your insights, building from single insights to a holistic understanding. When done properly, storytelling with data facilitates fast and easy interpretation. It invites the audience to engage with the story, activating the brain to remember the story long afterwards.
“These numbers have an important story to tell. They rely on you to give them a clear and convincing voice”
Start with the end in mind. Begin with investigating who your audience is – what they are interested in, what triggers them, what is their background? The audience plays a central role in storytelling. The story gains value when the audience is interested or has an information need in a certain topic. A story is well written when your audience understands it, trusts it and when it triggers an emotion with them. Therefore, turn your perspective 180öº when designing your visual story with data, and think from your audience’s viewpoint.
Once you understand your audience, start with analyzing and deriving insights from your data. While analyzing your data, always keep in mind your audience and their interest in the topic. Many different stories are hidden in the same data set. It is up to the person analyzing the data, to ask the right questions and select the relevant insights for his or her audience.
Storytelling with data is only effective when you present the main insight(s) and avoid information overload. Avoid telling your audience about every single outcome of your analysis. Take a step back and define the key message you would like to bring across together with the purpose of the story. Storytellers often provide too much information that confuses, rather than engages, their audience. By defining the key message and purpose, you can validate every element in your story and see whether it supports the key message or not. If not, simply leave it out. Limit complexity at first by gradually exposing your data and variables, reveal as needed.
In order to bring your story to life, you always need to make sure your story contains the following elements (the 4 Cs): context, character, conflict, and conclusion. Structure your story in a way that introduces the context and character, builds towards a conflict, and finally provides a conclusion. The trick is to reveal information gradually, so that the understanding of the storyline is built step by step.
Once the storyline has been defined, it is time to go back to your data and insights. Use them to solidify and substantiate your story. Provide evidence for your arguments, which will help to make your story trustworthy to the audience. It might sound obvious, but always stick to the facts. With great storytelling comes great responsibility. Do not misuse the power of storytelling, and make sure to present the data in a clear and unambiguous way that leaves no room for (mis)interpretation.
“This is my favorite part about analytics: taking boring flat data and bringing it to life through visualization.”
This leads us to the last, but not least important step: design your visual story. A picture says more than a thousand words. Data visualization has proven its power in bringing across insights from data in an engaging, clear and memorable way. A well designed visual story will invite your audience to interpret it. As John Tukey said: “This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization.”
There is far more than meets the eye when it comes to storytelling. It can uncover insights from your data that you might have missed. In this blog we’ve elaborated on the process of building up your story when data is involved. Click on the framework presented below and find an overview of the topics discussed in this article. This framework is developed by the data discover and visualization team of Deloitte and provides support in structuring the process of telling stories when data is involved.
More information? You may want to see this Storytelling with Data.
*) This article was written in co-operation with Suzan Janssen.