Just hearing the word “data” is intimidating. Being honest, only 21 percent of global workers are confident in their data literacy skills — and that number might be high.
With some of the best places of higher learning in the world, why is the United States not better at data literacy?
“Often, we take data for granted,” Biro said. “We assume it’s all we need to answer a question, and then realize we don’t really know if it really answers that question.
“Data is its own language,” she said. “We need to acknowledge that to start reading it and using it.”
One of the challenges is keeping data pristine.
“We allow too many biases to enter, which complicates the picture and mess even more,” Morrow said. “This is why data literacy is an imperative, not just a nice to have.”
Amid the emphasis on data, people get lost in the shuffle.
“We don’t mix data with the human element,” Biro said. “We say, well, the data says this, so that must be it. But we know there’s more to the story. Result: We scrap the data.”
For Morrow, this is an example of misplaced priorities.
“For far too long, a reliance on tools and software took the key spot, all the while forgetting the human impact,” he said. “We are now seeing this change and reverse. Humans and learning are at the top.”
An element of conflict avoidance, people think data collection is complicated. So, they avoid it.
“Very good point,” Morrow said. “The topics and ideas can be seen as intimidating versus just becoming comfortable with it.
“All of us — the organization and individual — are responsible to make employees more data literate,” he said.
A chair for everyone
Individuals in the workplace might put up barriers toward data and literacy, fearing they aren’t good with numbers or data. They leave it up to others such as finance or technology teams, trusting that their numbers will make sense.
“We need everyone’s skillset at the table,” Morrow said. “By only letting certain groups help and run data, we miss so much. Plus, we don’t need everyone to be a data scientist, just comfortable with data.”
Leaders need strategies to help their organizations better achieve data literacy.
“Organizations must drive a top-down and bottom-up approach,” Morrow said. “Leaders have to buy in, and all must be invited. People have varying talents, and that must be addressed.
“For instance, we are very good at descriptive analytics, but few are good at diagnostic analytics,” he said. “We have to do more customized learning, not a one-size-fits-all approach.”
Morrow would have companies move beyond just a data visualization and turn it into insight and business decisions.
“Far too often we are enamored with Level 1 analytics, which is descriptive, when there is so much more to be done,” he said. “Speaking the language of data is key. That allows people to discuss data and analytics, instead of giving a deer-in-the-headlights approach.
“I know companies that are making data literacy a job candidate requirement,” Morrow said. “This speeds up the process even more.”
Success hinges on raising the status of data speak.
“We need to champion data literacy among our workforces,” Biro said. “If we want to be data-driven, it’s time to close the gap with training.
“Find out how many people in your organization can have a conversation around data,” she said. “Find out how many want to. Start there.”
Rather than one or two specialists, data literacy should be a team effort.
“Don’t silo data analytics or data-driven decision making,” Biro said. “Get everyone involved, and bring data out into the open. Democratization is essential.”
Titles without skills
Interestingly, the fact that people are data scientists doesn’t necessarily mean that they are data literate.
“Plus, data scientists should have the ability to communicate and work through the business side of the organization effectively,” Morrow said.
Groups need more than numbers, trend lines and dashboards.
“Yes,” Morrow said. “If it doesn’t move the ‘business needle,’ why are we building a pretty dashboard?”
Scientific processes as the standard norm for conducting business and running the show must be achieved. This will incorporate the wisdom gained by data and its interpretations.
“I think we lose sight of this,” Morrow said. “The scientific process is central to using data and really running deep analytical projects. It isn’t just about data visualization. We need some who can do the advanced work.”
As with any changes, it falls upon leaders to build a data-driven workforce.
“Leaders make it a goal to have the workforce be able to speak data — like a second language — then provide constant access to learning,” Biro said.
“That entails education, training, but fun,” she said. “Have gamification, team building around learning data literacy, quizzes and pulse check-ins with a data question. Then it’s not all — yawn — PowerPoint presentations.”
Those in charge must lead the way.
“Leaders should start by being data literate themselves,” Biro said. “Incorporate data into meetings, discussions — lead by example, and encourage those data-literate to step in and coach and mentor.
“How can leaders not build a data-driven workforce, given the business case?” she said. “Losing up to 73 percent of our enterprise data to ignorance is costly.”
Everyone from the top down needs to be on board.
“Start by really incorporating leadership buy-in,” Morrow said. “If the leaders aren’t bought in, how is this going to work? Then, assess the workforce, allowing for customized learning. But always, always start with ‘Why?’
“Also, start with a strong data and analytical strategy, not a software or tool investment,” he said. “Recognition and gamification are key elements to build a successful data-driven organization.”