“ You can have data without information, but you cannot have information without data”.
Plato once said those who tell the stories rule the society. In a world that is getting increasingly data-driven, this statement holds especially true. It is only when we apply the art of storytelling to the science of data do we create visualizations that deliver business value.
In 2016, Forbes called data storytelling the “essential data science skill everyone needs.” Why? Simply because stories, since time immemorial, have been the most effective tools to transmit experiences. It is only when we use a narrative that we develop context and insight into a situation and gain the capability to interpret a situation. Data storytelling is no different. While businesses have zealously embarked on the data bandwagon and go about mining gigantic volumes of data with ‘potential value’, the fact remains that the true value of this data can only be created when it helps businesses unlock insights and translate the same into business actions.
In a 2009 interview Google’s Chief Economist Dr. Hal R.Varian has stated, The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades. Jump to 2018, and we realize the importance of this astute statement.
What is Data Storytelling?
Often data storytelling is confused with visually appealing data visualizations presented in the form of charts and graphs.
However, what data visualization essentially does is present complex information in a format that is easier to understand to answer ‘what is the data telling you’ part of the equation. However, what visualizations do not answer comprehensively is ‘why’ is the data telling you what it is expounding. Delving into this ‘why’ demands context. It needs someone to interpret results, articulate the insights and the business opportunities that lie ensconced within that data. What data needs is a narrative, one that explains what is happening with the data and purposefully draws attention to a specific insight or insights to create a data story that has the capability to drive change and inspire action.
To put it quite simply, data storytelling is the narrative that gives more meaning to data visualizations. Data storytelling is becoming a vital component in Business Intelligence tools since data is only getting bigger and more complex each day. With a sea of data at our disposal, having the capability to tell a compelling story becomes more important than ever before.
James Richardson, research director at Gartner stated, “The ways in which organizations deliver business analytics insights are evolving, notably in the rising use of what is called data storytelling…This trend is an extension of the now-dominant self-service model of business intelligence (BI), combining exploration data visualization with narrative techniques to deliver insights in a way that engages decision-makers in a compelling and easily embraced form.”
Data storytelling explores and explains the changes in data over a period of time. It is usually linked together using a series of visualizations through a narrative flow.
How data storytelling impacts an organization
In 1854 during the cholera outbreak in London, Dr. John Snow managed to convince the city council to take action based on the data story he had created. Snow spoke to the local residents and presented his findings, his data story, to the council stating that the cause of the illness was contaminated water supply. His data story contained the data points of location, time, volume, significance and proportion. And like any story, it had a plot and a hero.
A data story holds the capability to broaden the understanding of data analysis. It helps people relate to the story, helps them understand it, and relate better to it. The world is moving towards becoming more self-service, there is a rise of BI tools that allow people across business domains explore and access data on their own, and there is also an increase in the number of people generating insights expand beyond data scientists. It has become evident that unless an insight is understood, it will not be able to communicate any change. Data storytelling is becoming vital to business since it helps explain what’s happening with the data, why a particular insight is important and engage an audience by combining the right visuals with the narrative and the data to influence change.
How can you be a great data storyteller?
Data storytelling has become a critical skill set for data scientists. As data gets more complex, storytelling brings more simplicity – that is what makes it a vital business intelligence tool. Some of the basic skills needed to be a great data storyteller can be highlighted as follows:
- There is no one-size-fits-all in data storytelling – Data storytellers have to have the capability to tailor data stories to meet the sensibilities and the level of understanding of their audience and also fulfill the business need
- Have the capability to understand a business problem as in the absence of that the data scientist will not be able to add context to the story
- A data storyteller has to be able to field all questions generated as a result of the story
- Have the capability to identify and use the right data to create a credible story
- Have the capacity to present the data story in an engaging and visually appealing format with a tight narrative.
To end this blog lets dive into another story.
Ignaz Semmelweis, a mid 19th-century obstetrician, discovered that hand washing could save countless lives. But he failed to communicate his findings effectively to a skeptical medical community. Not only were his findings ignored and his life-saving idea rejected but he was also discredited by the community.
As we step further into a data-driven world, some of the most incredible insights will face a similar end if they are not molded into successful data stories that deliver transformative insights.