Even though data literacy is a critical skill for the 21st century, the reality is most professionals do not yet “speak data.” This reality will limit an organisation’s success in the coming years if the data literacy gap doesn’t close. To try to remedy the data literacy shortfalls, Gartner predicts that 80% of organisations will have training programmes in place by 2020. I have helped countless organisations address their data skills deficiency, and as part of this work, I have encountered many barriers to better data literacy. In this article, I what to share the biggest obstacles to data literacy that organisations need to overcome if they want to compete in today’s increasingly data-driven world.
One barrier to an organisation achieving better data literacy is its culture. First, all leaders must practise what they preach and lead with a data-first approach. If the leaders don’t require data to be used in meetings, in pitches for new products or services or to back-up decision-making, there is little incentive for employees to adopt a data-first approach.
A data-first approach requires acceptance of change and the willingness to take action to make change happen. This can be challenging for people. Some might have an “if it’s not broke, why fix it” mentality that holds back adoption of new skills to improve data literacy. This mentality is likely fuelled by a lack of awareness of how data can be used to the company’s strategic advantage. If they can’t see the benefits, they might resist the change. In addition, they might misunderstand what is required of them to be data literate.
Fear might also be holding your company back. Some individuals might fear that they “aren’t data people” and they put up roadblocks to acquiring new skills, such as procrastinating or avoiding training sessions because they have other work to do, for fear of failure. They might fear being replaced by others who are more data literate. While counter-intuitive, this fear of being replaced could hold them back and paralyse them from acquiring new skills to be more valuable.
Data literacy doesn’t require every member of an organisation to have the knowledge a data scientist does, but some people might misunderstand what is expected with data literacy programmes. Be sure to communicate and help employees understand that they just need to learn to read, interpret and critically evaluate data.
Data Literacy Focus and Stages
Another barrier to data literacy is the progress an organisation has made on the journey to data literacy. They might not have prioritised it above other initiatives and are moving more slowly than other organisations. Some companies are still focused on collecting data rather than training how to evaluate and use the data they have to their business advantage. Others are still trying to determine the tools they should invest in to get everyone access to review, consume and manipulate data to discover new things from it. It is really important that data literacy is improved gradually and in sequential stages.
Another barrier to data literacy is the data itself. Organisations might be collecting data, but if they aren’t collecting the right data or if the data is compromised in some way, it won’t be able to inform decisions the way it should. Just because there is a vast amount of data available today doesn’t mean that all data is equally valuable to an organisation.
Increasingly, when it comes to data, diversity is crucial. It often makes sense for organisations to go beyond the data that is immediately available from primary operations or that’s the easiest to collect because insight can be found in unexpected places. In healthcare, breakthroughs in technology enable diagnosis via robot thanks to data streams from handwritten doctors’ notes and medical scan images. In marketing, rather than just looking at sales revenue, some companies are extrapolating insights from how products are talked about and photographed on social media. Unstructured data makes up more than 90% of the data generated worldwide, so it’s more important than ever to examine it as part of your company’s data strategy.
Aside from the dashboards and reporting tools required to allow employees in every business sector access to data, there are analytics tools that can help humans glean deeper insights by using technology to their advantage. Augmented analytics, where artificial intelligence automatically takes data from raw sources, scrubs and analyses it in an unbiased manner and then communicates it to humans via reports, can give companies more in-depth insights than they would be able to gain without the aid of artificial intelligence.
Companies will need to develop ways of overcoming the most significant barriers to data literacy—company culture, prioritising data literacy as an initiative and the data itself—in order to close the data literacy gap. If you would like to discuss how to improve the data literacy in your organisation, just get in touch.