In 2006, British mathematician Clive Humby declared, “Data is the new oil.” In saying this, Humby implied that data – not oil – would be the primary resource to drive the economy forward over the coming decades. While there is definitely truth to this statement, data – just like oil – is useless in its raw form. Before it has value, it needs to be extracted, refined and turned into something useful. This is where data storytellers come into play. Many techniques found in data analytics play a significant role in helping companies drive innovation and financial performance.
What Is Data Storytelling?
Data storytelling is the ability to craft a narrative by leveraging data, contextualizing it and presenting it to an audience. You can think of a data storyteller as the modern-day equivalent of an oil company that extracts oil from the ground, refines it and ships it to a distributor.
Every data story requires three things: data, visuals and a narrative. Without the data to back it up, even the most compelling data story is just a work of fiction. Without visuals, the data story will be difficult for your audience to follow. And, finally, without a narrative a data story, is just a summarization of raw data that lacks meaning.
The process of turning raw data into a compelling narrative requires five steps:
- Assess the data: Before drawing a conclusion, the storyteller must analyze the data and draw the correct conclusions. This is the most important step in the process.
- Consider your audience: After extracting your conclusion from the data, consider how your audience will respond to this information. How is this relevant to them? Why should they care about the story this data tells? This step is also crucial when determining the best way to present your story so that it’s well received by the audience.
- Find the most effective visuals: A data story is not complete until it has been put into a visual form. Most often, this means a chart, graph, heat map or similar style of data presentation.
- Provide context: To enhance your data story, provide relevant information around the data to give it context. To do this, you can find data from other sources or leverage your own domain expertise.
- Edit and review: Once your data story is complete, step back and collect your thoughts. After a few hours, revisit your data story to make sure it still makes sense and you’re not misinterpreting the data.
These general steps can be applied to an almost endless series of scenarios.
When Are Data Stories Used?
Data stories are used when someone wants to use data to make a change or fuel their decision-making. You’ve likely heard data stories hundreds of times, even if you didn’t quite realize it at the time. Here are a few examples of where data stories are commonly used:
- Business: Business leaders will reference sales data, market research and financial statistics to make business decisions, influence others and provide contextual support for their decisions.
- Scientific research: More than other industries, scientists provide their colleagues with a data story when presenting new findings. Scientists can even expect their colleagues to go one step further and review the data story for errors.
- Sports: Coaches will analyze data to help their players improve as well as outflank opponents. They might also leverage data stories to try and inspire their team.
- Policymakers: Politicians will use data to illustrate the impact of certain policies, highlight social inequalities or make a case for policy reforms. This is done internally with other politicians as well as to sway public opinion.
- War: A data story is behind practically every single military decision. In one famous example, Florence Nightingale analyzed the mortality rates of soldiers and realized that preventable diseases from poor conditions caused more deaths than on the battlefield. This paved the way for improved sanitation conditions in camps.
- Finance: Investors will use data storytelling to identify the potential of companies or in the economy, draw a narrative and make investment decisions.
Telling a Story Through Statistics
One of the most intriguing things about data stories is that anybody can become a storyteller. For example, learning to properly leverage tools like Google Analytics or Google Trends can instantly provide insight into one of the most reliable sources of data: web traffic from the world’s largest search engine.
That said, if you intend to pursue data storytelling as part of your career, it’s worth obtaining an advanced degree. Doing so will help you learn to craft data stories that can be digested by business professionals to help propel your organization forward.
Becoming a Storyteller
In the University of North Carolina Wilmington (UNCW) Master of Science (M.S.) in Business Analytics online program, students learn how to analyze raw data and ideate narratives that will benefit their organizations’ performance and reputations.
This program also offers electives tailored to specific industries, depending on your areas of interest. For example, you can learn to create data stories relevant to digital marketing, healthcare, supply chain, sports, data centers and business in general. Students can complete this online program in as few as 12 months.
Learn more about UNCW’s online Master of Science in Business Analytics program.
