Data storytelling bridges the gap between the ‘what’ and the ‘why’ that’s often hidden under the surface of your data.
To maximize the potential that data has to offer, most companies have identified the need to democratize data throughout their businesses. The goal is to make it easy for anyone in the organization to access the key metrics they need to make better decisions. In a recent survey of 500 executives and data professionals, Exasol found 90% of respondents said that data democratization was a priority for their companies and were actively taking steps to achieve it.
The most common way of sharing data with employees has been through dashboards and reports. In the Exasol study, 82% of respondents reported “regularly using dashboards to share and communicate insights with colleagues at every level of the business.” Unfortunately, more than half (53%) also reported that dashboards were often being disregarded due to the time it took to interpret them. At the organizations that struggled with using dashboards effectively, respondents indicated the top drawbacks with dashboards were inadequate context (61%), information overload (54%) and a lack of customization to individual user needs (46%). Unfortunately, these issues cannot be easily remedied with just better technology or design.
In the common scenario where people lack the skill or time to interpret complex dashboards, Exasol’s Chief Data and Analytics Officer Peter Jackson says, “That’s where data storytelling skills make a difference—data storytelling helps communicate insights to everyone, regardless of where they fall on the data literacy spectrum. It bridges the gap between obtaining insights and interpreting them.”
These survey results highlight some of the major limitations of dashboards, especially when it comes to communicating specific insights rather than just general information. Dashboards can be effective exploratory tools, but they only offer limited explanatory capabilities. Dashboards are not data stories. They can help cover the ‘what’ but can rarely explain the ‘why.’ For example, a dashboard can help you notice when a particular marketing campaign isn’t generating enough leads, but it won’t be able to pinpoint or clarify why it’s underperforming without further analysis or research. Without ample doses of ‘why,’ the full benefits of data democratization will always be incomplete and never fully realized.
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