Numerous organizations are leveraging analytics to transform the massive amount of enterprise data into useful business insights.
Many of the visuals, charts, dashboards and graphs presented fall short of their intended audiences. Sometimes, it’s just about overwhelming recipients with too many data. Other times it’s about not understanding how to create a compelling narrative that resonates with recipients.
Data storytelling is a skill that has been developed for the age of big data. Experts differ on how they define data storytelling. They describe it as the ability not only to communicate data in charts or numbers but also as a story that people can understand.
A data story must have a beginning and a middle. It must be presented with no bias, and with the right empathy and context to allow business users to absorb the insights and make better decisions.
“If you want people to make the right data decisions, then you have to get inside their heads in a way they can understand. Miro Kazakoff, a MIT Sloan lecturer, said that stories have been the best way of telling stories throughout human history. He teaches Communications & Data Storytelling as part of the Masters of Business Analytics program at the school.
Kazakoff explained that data storytellers who are interested in becoming data storytellers will be taught how to predict the audience’s response to their analysis. Students are taught how to organize their presentation and plan to address the needs and wants of specific audiences, Kazakoff said.
This is not always possible with analytics dashboards that alert business users to a particular change, such as a drop in sales or spikes in customer support calls. They don’t provide insight into the whole story.
“It is hard for a dashboard to narrate why something happens.”
Communicate with context
Glassdoor has ranked data scientist third in the U.S., with over 6,500 open positions. Data analytics is not only for those with PhDs in statistics or mathematical modeling. Techies who are fluent in languages such as R and Python are also required.
Effective communication is crucial to communicate the insights and understand the perspective.
J.T. said that data analysts and data science professionals don’t often have the same skill set. Wolohan is the author of “Mastering Large Datasets with Python” and has worked with data scientists in the private sector.
Wolohan stated that data scientists are often able to point and shoot, but can’t explain their actions. They have difficulty working backwards, translating questions into business solutions. This is the real missing skill.
Data storytelling is the ability to communicate information clearly and without bias. Kazakoff stated that data storytellers must be meticulous editors to avoid the temptation to alter data to fit preexisting stories and to make sure the data is presented in a way that appeals to the audience.
“The art of data storytelling is to remove the noise and focus people’s attention upon the key insights,” said Brent Dykes, a consultant in data strategy and author of Effective Data Storytelling, A Guide to Driving Change.
Dykes stated that part of the skill is to build narratives and reveal data in the right order and sequence. The visualization piece is another.
He said that data storytellers who are skilled at presenting data visually have a good sense of how to do so. They also know how to distill the findings down to a core set visuals that conveys the message in the most concise and direct way.
Kazakoff stated that empathy is perhaps the hardest skill in data storytelling. It allows you to understand the audience and the parts of the analysis they will react to.
A sales executive and a head of software development have often had opposing worldviews. This means that when they share the same data, their reactions will likely be very different. It is crucial that the person who will be responsible for data analysis can interpret and present the relevant material according to their viewpoints.
Wolohan stated, “It’s going to not be a black-and-white answer — It’s very much an translation task.”
What job skill?
Businesses should create data storyteller positions or train their workforce to fill this gap. This will give everyone the foundational skills necessary to work with and analyze data. Experts agree that organizations should do both.
Dykes stated that data storytelling is an essential skill for the wider workforce to succeed in what he called “the final mile of analytics.”
Kazakoff was also in agreement.
Kazakoff stated that being literate with data is just as important as being able explain the stories it tells. It’s not a job function. It cuts across all levels and functions in a company.
Like communications, certain roles require deeper understanding than others. However, Kazakoff stated that no one who is informed by data can avoid the need to explain and understand it to others.
Althea Davis is the enterprise data governance manager for Etihad Aviation Group. She agrees that data storytelling is an essential enterprise skill. However, she said she would love to see a role in place to balance out the many roles within a data analytics organization.
Davis stated that data literacy is a difficult skill to master for businesspeople. They need to be molded and mentored in a way they can absorb. It would be so much easier if we had data storytellers who were really good.