As the amount of data continues to grow year on year, a business’s ability to compete will increasingly be driven by how well it can extract insight, apply analytics and implement new technologies. That’s key to stay competitive in today’s ever-changing
economy, leveraging rich datasets to get a deeper understanding of their customers, operations and the markets they operate in.
Dealing with an increased amount of data requires an adaptive, agile approach. The organisations that succeed are those that can make sense of the data, spotting the opportunities and assessing ideas quickly. But, before data can be used, it needs to be
interpreted and understood properly.
With the data skills gap still a well-reported issue, it’s easy to rely on the advances in technology to address a lack of expertise to effectively work with data. This, however, would be the wrong approach to take, as it’s hugely unlikely that any skills
shortfall will be filled by machines, rather new jobs being created to support data architecture and data insight strategies. The need for data expertise in your organisation will, if anything, become greater.
The best way to enable fast discovery and deeper insights is to disperse data science expertise across the organisation. That, combined with easy access to analytics, can empower non-data scientists with a more purposeful tool kit for the task at hand. In
most businesses, data scientists are required to complete the most basic of data related task. By creating a culture where sharing data knowledge and tools is the norm, these responsibilities can be distributed across a data-literate workforce, freeing up
valuable time for your data specialists to be truly innovative.
Hitting the wall
Recent research from the Data Literacy Project revealed that whilst organisations are shifting day-to-day analysis away from the data experts, they’re hitting a wall when finding that only 21% of employees are data-literate, despite 65% claiming that they
need to read and interpret data on a regular basis. Only 25% of employees felt fully prepared to use data effectively when entering their current role.
So, what’s stopping organisations from unlocking the insights held within their data? A lack of confidence in the data could be a factor, with only 37% trusting data-informed decisions over gut feeling. This is even more common at senior levels with around
60% relying on pure instinct.
The research also suggests that 74% feel overwhelmed or unhappy when working with data. 36% try to find a way to get a job done without using data, while 14% avoid the task altogether. And 61% say feeling overwhelmed with data has contributed to workplace
Although daunting, a more data literate workforce gives you a chance to transform a business for all the right reasons. The challenge is finding an effective way of integrating the new behaviours, processes and roles that are required to be successful, embedding
them into the heart of the operation.
Building a data literacy strategy
The most innovative companies in the digital age are using data and technology to build superior, hyper-personalised experiences for customers and make the most relevant decisions based on that information. It stands to reason that if innovation relies on
data, then organisations who have a data literate workforce will thrive.
To support these ambitions, the Data Literacy Project has identified five key steps organisations need to consider when planning a data literacy strategy.
- Set your data expectations and link to tangible value.
- Create a roadmap. Key parts of this are to assess individual levels of data literacy, understand current availability and adoption of key tools for each type of user, define key data and ensure access via a strong governance structure.
- Invest in technology and data.
- Close the skills gap.
- Culture of co-evolution. Regular reviews of data toolkit, identifying the right training for users in different roles.