Research shows that data-driven organizations are more successful, but employees often lack needed Data literacy skills.
According to a 2020 survey by Sapio Research, 80% of decision-makers believed opening up access to data has a positive impact on their organizations and 74% said employees have access to the data they need. But 53% of respondents reported employee resistance to using the data.
Meanwhile, research has consistently shown that data-driven companies are more successful. A 2019 survey by McKinsey & Company, a management consulting firm, showed that companies where employees consistently use data in decision-making are one-and-a-half times more likely to report revenue growth of more than 10% in the past three years.
The difference comes down to Data literacy.
"It is crucial in today's world where data is omnipresent," said Shreeni Srinivasan, director of enterprise analytics and applications delivery at Sungard Availability Services. "Data literacy can empower employees to make fact-based analytics decisions that are more grounded in reality than the ones made on instincts or gut feeling."
According to the same McKinsey & Company survey, the share of executives at high-performing organizations who understand data concepts is 44% higher, the share of managers who understand data is 39% higher and the number of frontline employees who understand data is 12% higher than other survey companies.
However, there are significant obstacles to achieving data literacy. According to Gartner, 50% of organizations lack sufficient data literacy skills to achieve business value, and 35% of chief data officers said poor data literacy is one of the top roadblocks to the effective use of data and analytics, just behind cultural challenges and lack of resources and funding.
Data literacy is the ability to write and comprehend data similar to how we view literacy with reading. This can include an understanding of where data comes from, communicating information derived from data to others and knowing where to use different analytical tools and methods. "When enterprises have more data literate employees, they understand that data is no longer just the domain of the data team," said Andrew Stewardson, data manager at Farm Credit Services of America, a credit provider to farm and ranch operators based in Omaha, Neb. "Having a higher level of data literacy means that we can better serve our customers." Stewardson's organization took an unusual approach to data literacy training by creating an internal persona, Walt, to answer data-related questions from employees. "The key to encouraging data literacy training was making Walt relatable to various people within the organization," said Michael Meyer, data engineer at Farm Credit Services of America. "We also created a blog where users could ask questions about all things related to data." That took the pressure off the data teams to drive change, he added. "Just putting data into the hands of individuals in an organization doesn't automatically increase data literacy and make an organization data-driven," Stewardson said. In fact, rolling out data projects without paying attention to data literacy can be a costly mistake. For example, Penny Wand, director of technology at West Monroe Partners, a management and technology consulting firm based in Chicago, was working on a project for a manufacturing firm to roll out pricing strategy analytics. "People just rejected it," she said. "They didn't understand the results." The project was a failure, and not only did the company lose the time and money it spent on creating the analytics, it also lost millions of dollars in lost opportunities, Wand said. "It cost them money because they couldn't optimize their pricing strategy," she said. "They lost money by not being able to put into action what they learned with the data.
