January 28, 2020
A new report from Qlik and Accenture, titled “The Human Impact of Data Literacy” and conducted on behalf of The Data Literacy Project, claims that while most organisations understand the incredible opportunity of data, a gap has emerged between organisations’ aspirations to be data-driven and their employees’ ability to create business value with data. The report argues that data is a ‘gold mine’ that can fuel a culture of innovation and growth as part of a data strategy. However, when employees struggle to make sense of data, productivity and business value can be affected.
The survey of 1,000 UK employees found that each year companies lose an average of almost an entire working week (34 hours) per employee each year due to procrastination and sick leave due to stress resulting from information, data and technology issues. This is costing British firms over £10 billion in lost productivity every single year.
The research identified how the data literacy gap is impacting organisations’ ability to thrive in the data-driven economy. First, despite 81 percent of UK workers recognising data as an asset, few are using it to inform decision-making. Only 17 percent of surveyed employees believe they’re fully prepared to use data effectively when going into their current role, and the same number report being confident in their data literacy skills — i.e., their ability to read, understand, question and work with data. Additionally, only 34 percent of employees trust their decisions more when based on data, and almost half (46 percent) frequently defer to a “gut feeling” rather than data-driven insights when making decisions.
Second, a lack of data skills is shrinking productivity. Two thirds (67 percent) of workers report feeling overwhelmed or unhappy when working with data, impacting their overall performance. Some overwhelmed employees will go to further lengths to avoid using data, with 19 percent stating that they will find an alternative method to complete the task without using data. Almost half (47 percent) report that data-overload has contributed to workplace stress, culminating in one quarter (25 percent) of the UK workforce taking at least one day of sick leave due to stress related to information, data and technology issues.
“No one questions the value of data – but many companies need to re-invent their approach to data government, analysis and decision-marking. This means ensuring that their workforce has the tools and training necessary to deliver on the new opportunities that data presents,” said Sanjeev Vohra, group technology officer and global lead for Accenture’s Data Business Group. “Data-driven companies that focus on continuous learning will be more productive and gain a competitive edge.”
Empowering the workforce to thrive with a data strategy
To succeed in the data revolution, business leaders must help employees become more confident and comfortable in using data insights to make decisions. Employees who identify as data-literate are nearly twice as likely as data-illiterate peers to say they feel empowered to make better decisions. Furthermore, one quarter (25 percent) of UK workers believe that data literacy training would make them more productive.
Jordan Morrow, Global Head of Data Literacy at Qlik and Chair of the Data Literacy Project Advisory Board added, “Despite recognising the integral value of data to the success of their business, most firms are still struggling to build teams who can actually bring that value to life. There has been a focus on giving employees self-service access to data, rather than building individuals’ self-sufficiency to work with it. Yet, expecting employees to work with data without providing the right training or appropriate tools is a bit like going fishing without the rods, bait or nets – you may have led them to water but you aren’t helping them to catch a fish.”
In the Human Impact of Data Literacy report, Qlik and Accenture share five steps organisations should consider when planning their data literacy strategy to build a data-driven workforce, including setting clear data expectations and creating a culture of co-evolution.
Image by Gerd Altmann