Why plot-driven data storytelling is important and how to create it
August 6, 2020
Data storytelling can yield significant benefits in informational analysis, but it requires skill and expertise. Learn some tips from data experts to get the most out of the experience.
The age-old problem with data analysis is making the best use out of the information obtained by carefully parsing it for conclusions. It’s not an easy task, so there’s a reason data storytelling has become such a popular and lucrative career. Separating the wheat from the chaff is a fine art honed by extensive experience.
I spoke with Keelin McDonell, general manager of business intelligence and integrations at Narrative Science, an artificial intelligence (AI)-powered software startup that turns data into stories – and Jolene Wiggins, CMO of Gravy Analytics, a data analysis organization. Bill Hewitt, CEO of Aternity, a digital experience management solutions provider, added some thoughts to the conversation, too.
Scott Matteson: What are the challenges companies face in their ability to quickly act on data?
Keelin McDonell: Companies are dealing with more data than ever before. The size of our data universe doubles every two years. We’re now sifting through so much data that it’s almost become meaningless because companies today don’t have the context they need to understand what their data is telling them.
Companies need to act on data faster than ever before. Data depreciates fast, and everyone in the business—from data analysts to sales, marketing, and customer success teams—needs to be able to receive, understand, and act on insights from data in real time. This lets them get ahead of their competitors and stay nimble in a landscape that’s always changing. Spending too much time puzzling over charts, graphs, and other data visualizations is time that could be spent making the next major business decision to get ahead.
There are a number of business intelligence tools that have tried to tackle the data problem (the market is worth about $30 billion and grows 15 percent each year). But many of these tools are designed for people with data analytics backgrounds, so they’re not easy to use for people in other departments who rely on data to make major business decisions every day.
According to Gartner, at a typical company these data analytics and business intelligence tools only have about 25 percent penetration, suggesting that three-quarters of employees find them too difficult, too time-consuming to use, or don’t have the skills to use them at all.
Jolene Wiggins: The biggest hurdle between data collection and analysis that keeps companies from acting on data in a timely manner lies in the organization’s data structure. To get the most holistic view, companies need to pull data from several internal and external sources, which can be a very time-consuming and tedious process made more complex by different data formats and management systems.
Scott Matteson: How can those challenges be addressed?
Keelin McDonell: We think the easiest way to help companies act faster on their data is by presenting it through stories and language. That means providing plain-English stories about what the data is telling you, as opposed to a bunch of scatter plots and pie charts.
There are a variety of benefits to doing it this way.
- Meet and exceed goals faster. Because you can devote more resources to where they will have the biggest impact, and ambitious goals become more realistic.
- Democratize data for the entire company. By presenting data in the form of a story, literally anyone in the business can understand what the data is telling them without having to pore over complex charts and graphs. What’s more, research shows people remember information better when it’s in the form of a story.
- Make decisions faster. When you know exactly what the data is telling you, you can confidently make major business decisions without having to worry if you’ve read a chart or dashboard wrong. Meetings can be spent discussing what really matters as opposed to asking the room to read your pie chart.
- Get everyone on the same page. Charts and graphs are open to interpretation by the person reading them. By presenting data as a story, you reduce the chance that two different departments are arriving at two different conclusions from the same data visualization.
- Improve resource allocation. Spend less time reading data, and more time on tasks that move the needle, like drafting a new marketing email or putting more money behind a social media post.
Jolene Wiggins: Overcoming roadblocks to acting quickly on data depends on data integration: Combining data originating from different sources into a single location with unified processes. Also, companies need to fundamentally find a way to make data part of the culture of the organization at every level. This culture is much easier to cultivate when the collection and structure of data is unified across organizations, making it quick and easy for the right people to access regardless of team. When companies have the right systems in place to provide access to data, and the right resources to analyze and pull learnings from that data, then data can become central to operations and decision-making.