Why and how is data storytelling revolutionizing emotional design?

“Data StoryTelling is about using numbers and facts
to transform them into stories that everyone can read.“

 

Dataviz reports play a strategic role in a company. Among other things, they allow decision makers to make quick decisions. But in reality, decision makers are saturated with information, tables, graphs and figures. The most important indicators to remember are drowned in a mass of information.

A dataviz report that is difficult to understand and requires control and verification phases, the whole report is called into question. So, what to do? How should we proceed to make reports more effective in the eyes of managers and decision makers?

Integrate emotion through Data storytelling!

Emotion is the key to anchor your dataviz messages in the memory of your hierarchy and your employees.

Data analysis is changing. Data alone is no longer enough, emotion must be integrated to help management make decisions. Data storytelling makes it possible to improve the performance of dataviz communications and to make the data stand out from the batch through a narrative approach.

« A story is 22 times better retained than a statistic »
Jennifer Aaker, psychologist and professor of marketing at Stanford

Turn your data into readable stories

The art of telling a story with data and indicators is to use storytelling methods in an interactive storytelling framework: sequences, linearity, captions, explanations, explicit and implicit causalities, message intensity, emotions and expected reactions.

How to implement Data Storytelling? We have listed for you 5 simple phases to take into account in order to produce detonating dataviz reports based on the Data Storytelling approach:

1. Understand and talk to a target
   Viewing, understanding, analyzing… everyone interacts with data in a different way. That’s why you have to listen to users and adapt to their level of data usage.
2. Select coherent data
   This means understanding the context and nature of the data, and its life cycle.
3. Build a scenario according to the data and the target
   To find a relevant story that speaks to the user.
4. To select the coherent data
   And therefore define and choose the indicators that have the most value for the end user.

Formatting the data. In conclusion, indicators have a purpose and must deliver a message. Because the user must accept and interpret the indicators that are displayed.

Example of emotional design

Here is an example of a very common customer case:

“I am a manager whose need is to use an understandable and operable dataviz report to make good decisions quickly.”

Problem: The data displayed is confusing and inconsistent.

Solution: Implement Data Storytelling to produce a report that communicates a compelling story:

• Is the story optimistic or pessimistic?
  • Is the balance sheet positive / negative?
  • Does the gross margin match the objectives?

• What will be the outcome of the story?
  • Is the actual in line with the forecast?
  • What is the health of my company?
  • Will I have to take economic measures

• Understand the most significant moments, the strongest in history:
  • What does this peak in activity correspond to?
  • Why was there such a large inventory during this period?
  • In terms of data, how did the merger and reorganization of services affect our financial results?

• What are the most important facts of the story for me to remember?
  • We have a 15% shortfall versus last month on industrial equipment sales
  • The July reorganization boosted the financial results by 22%.
  • I need to contact the CEO to strengthen our sales force based on the data I am seeing.

Discover DataStorytelling at JEMS

Alexandre GABILLET – Lead UX Designer