When working to instill an enterprise-wide data-driven culture, your workforce’s data literacy levels can either serve as a stepping stone or a setback in the process.
Often, companies that are struggling to become more data-forward are not lacking the tools or funds. As with most business initiatives and achievements, success hinges on the people.
Accenture’s 2020 The Human Impact of Data Literacy report found that 75% of surveyed employees are uncomfortable working with data, so much so that one-third have even taken a sick day due to headaches caused by working with data.
As your organization’s data strategy leader, the responsibility of shifting this mindset begins with you. In order to truly build a positive culture around data and analytics, employees need adequate resources and education to empower them to use data in their decision-making.
How can you scale a literacy program that not only addresses employee resistance toward data, but also allows them to feel confident and even enthusiastic about generating insights?
Here’s how enterprise data leaders are making it work at their organizations.
Gauging your company’s knowledge level
You can’t begin to address data literacy without first knowing where your workforce’s abilities and knowledge lie.
A survey conducted by software company Qlik found a clear gap between the perceptions of executives and the reality of employee capabilities when it comes to data literacy. While over half of 1,200 executives felt confident in their workforce’s data literacy levels, just 11% of employees agreed.
In contrast, some employees may overestimate their abilities, according to Emma Alexander, Head of Commercial Investment and Analytics at Samsung Electronics.
“Everybody initially thinks that ‘I’m data literate, and I understand data.’ But often when you test the waters, you realize this isn’t the case. We need to build individuals’ confidence back up and show them that they shouldn’t be frightened of data,” Emma says in The Human Impact of Data Literacy.
To combat this uncertainty, the first step in your literacy journey should focus on determining individual skill levels. This can be achieved by administering a data literacy skills assessment, either developed by your own organization or from an external source such as The Data Literacy Project.
Starting small
Once you’ve assessed the level of your enterprise’s knowledge and you’re ready to pilot a literacy program, many data leaders suggest starting small.
McDonald’s Vice President and Chief Data Analytics Officer Craig Brabec recently shared this advice during a Data Board panel discussion on leading a data cultural transformation.
“Don’t try to do everything at once. Start small and then scale,” Craig says.
Craig suggests beginning with personas — think through the individual needs of your senior leaders, those doing data entry, and those directly working with customers, among other business units.
He also shared a lesson learned when trying to scale data literacy too quickly. McDonald’s began running data boot camps for its North American finance team, which Craig says were extremely successful. Based on a push from business leaders, they scaled the program for their European team and quickly discovered the datasets didn’t work.
“I had to reset and refresh,” Craig says. “Really go into the personas and the parts of the business to start to raise their acumen and capability in the programs.”
Finding your data lovers
Despite a lack of self-confidence in some employees’ data capabilities, for many, the eagerness to learn is there. Qlik’s survey found that 59% of employees want to become more data literate.
Chris Gifford, Chief Data and Analytics Officer at USAA, found these employees with an appetite for data and leaned on their enthusiasm when scaling data literacy. He explained this process during the Data Board panel.
“Find the cohort of people out there who are in the business. They’re like closet data nerds, and they just love data,” he says.
Chris calls this group, “data influencers,” and they’ve helped launch enterprise-wide discussions on data. These data leader-led sessions are called Let’s Talk Data and host between 400 and 600 employees. The hour discussion covers topics such as the cloud or natural language processing.
Chris explains the feedback from their employees who expressed a desire to continue the events.
“We found a lot of really good inroads into the businesses to really generate that bottoms-up demand for these kinds of things.”
Programs like USAA’s data talks or McDonald’s boot camps not only hold the potential to increase data fluency but also drum up internal excitement around data and analytics.
Iwao Fusillo, Chief Data and Analytics Officer at General Motors, recently spoke about this idea on The Data Chief Podcast.
“Passion, when it comes to data and [data] literacy is really important,” he says. “That’s why we put the GM analytics academy course out there — to not only build the literacy itself but just the passion in having a core competency around analyzing and presenting data in a compelling way to make decisions.”
Learning by doing
Each employee will benefit from a different learning style so it can be helpful to employ a variety of training tactics: boot camps, videos, self-paced training, workshops, and follow-up assessments.
Jennifer Battista, Vice President of Data Strategy at Shaw Communications, told the Data Board she believes heavily in learning by doing.
“It’s very hard to learn something just by hearing about it or just by seeing it,” Jennifer says.
Based on this thinking, Shaw Communications provides employees with forums to help them learn by doing, with the general goal of meeting them where they’re at, in terms of skills and knowledge. They also leverage formal data courses, but the real growth comes from providing opportunities for people to do the work.
Benchmarking your success
Benchmarking the success of your data literacy program can be a challenge, but follow-up assessments can be an effective tool for measuring progress.
There are a number of data literacy resources available such as DATAVERSITY or Data Literacy. It can also be useful to benchmark data literacy strategies with other industry experts in a leaders-only community like the Data Board.
