Covid-19 brought to the fore many innovative and creative examples of how to use data effectively.

From identifying where to send medical supplies and channel financial support to businesses to allowing food banks to connect with families in need of supplies – combined with good judgement and expert knowledge, data can give organizations the insight to act with accuracy and speed.

But even before the pandemic turned our world on its head, it was clear that many businesses saw data among their most valuable assets. It’s a vital tool for success. What has become even clearer is how important it can truly be in creating competitive advantage.

However, while many want to improve their data quality and become data-informed, a lack of the right skills and resources within their organization is significantly hampering their chances of executing a successful data strategy.

This is not an easy fix, as right now there is a data skills shortage. There are more data roles to fill than qualified candidates to take those roles, resulting in a frenzy for data talent. This is exacerbated even further because some of the bigger brands in technology dominating the recruitment of new and existing talent.

Four in five (86%) data leaders report difficulty in hiring talent in the sector, and almost half believe that skills shortages pose the greatest challenge to delivering value within their organization.

And it’s not just the roles most commonly associated with data that is posing a challenge for businesses – one overlooked area is the handling and processing of data effectively.

The conversation around skills usually gravitates towards data scientists, but the organizations need to have data that has been cleaned and is fit for purpose. There needs to be more focus on how we get data to the point that scientists can use it effectively.

The UK Government’s new National Data Strategy outlines its ambition to establish the country as a world-leading data economy, specifically highlighting data skills as one of the focus areas to reach this goal. But achieving this will continue to be an uphill struggle if the talent pool remains at its current level.

The data industry can play a crucial role in changing this. Here are some thoughts on some approaches to help bridge the gap.

1. Looking at data skills through a national lens

Any discussion about digital skills often focuses on what schools and universities are doing, highlighting the need for more data related subjects to be taught. But we need to broaden our perspective if we’re to tackle the shortage.

The National Data Strategy offers the opportunity to look at data skills through a national lens. This will enable government and industry to identify which skillsets are missing and where, and to be far more strategic about their development.

Collaboration between organizations and universities is key. By understanding the needs of the business, more emphasis can be placed on what vocational courses can be offered to not only give students the best chance of employment post education but give businesses the right skills that’ll allow them to achieve their strategic goals.

Identifying centers of excellence for the development of key data assets, technology or skills that can enable the ecosystem to grow should also be considered, along with partnering with regional universities. This can create a substantial footprint in the UK’s major cities and towns that will allow today’s students and tomorrow’s employees to develop and enhance their data skills.

By fostering these collaborations, the Data Strategy could help ensure institutions are developing the data skills needed by local employers through workplace training, upskilling, or retraining. This would boost productivity, support local job creation, and make sure that the strategy’s benefits are felt up and down the UK and at an individual level.

2. Future-proofing the UK’s workforce

But it’s not just about cultivating the right data skills within educational institutions. Businesses also have a role to play in future-proofing the UK’s workforce by equipping their workforce with the essential skillset to manage data.

They must place a renewed emphasis on building data capabilities amongst their existing employees at all levels. Failure to do so could see data knowledge concentrated in the hands of a few, who are then relied upon to support the entire business. This is unsustainable and can lead to issues if these people move elsewhere.

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 and drive success.

One organization tackling this issue head-on is Marks & Spencer. In 2018 the retailer partnered with Decoded to create the world’s first Data Academy in retail. The program aims to support the business’s digital transformation by building the necessary skillsets from the ground up. Employees can enrol in an 18-month in-work data science skills program, where they learn to adopt and apply data analytics tools and technologies such as machine learning.

More recently, this program has expanded even further with the launch of a new entry-level Data Technician course that teaches employees how to manipulate, scrutinize and then translate that data into valuable insights.

3. Improving diversity in data 

But education at one stage or another is not the only key to data skills – increasing diversity will also help. While the discussion around diversity and inclusion often focuses on gender and ethnicity, there is a strong case for improving neurodiversity within organizations. For example, Asperger’s can be an advantage in certain jobs, particularly those involving data analytics.

But conventional recruitment practices work against those with the condition. In a world with growing skills gaps, and a desire for employees with creativity and potential to innovate, it is even more critical that these policies and processes give all types of people an equal chance to succeed.