To accurately understand data literacy rates across an organisation is incredibly important, but also difficult to achieve. Data leaders need to understand that certain teams will not use data as much as others, and some teams will only focus on a very specific part of the data available for their needs. DataIQ has created a free Data Literacy Indicator which can help data leaders accurately assess the levels of literacy across their organisation.
A majority of DataIQ members (64.8%) stated that data literacy across their organisation would be considered moderate – where skills are developing within certain stakeholder functions. Only 2.8% of respondents described their organisational data literacy levels as very high, with 16.9% describing their level as developed. At the other end of the spectrum, 2.8% responded that their organisational data literacy level is poor with no formal usage or skills.
When asked to highlight challenges surrounding the effective consumption of data, DataIQ members identified poor data literacy as the second biggest challenge after a lack of senior leadership buy-in to data. Arguably, improved data literacy at the senior level of an organisation would bolster the buy-in and support data teams receive, so these two challenges do operate some amount of overlap.
How to improve organisational data literacy
A data leader needs to know where there are gaps in data literacy to be able to address them effectively and efficiently. This is easier said than done, particularly if there is not a close working relationship between the data team and other areas of the organisation.
“The best organisations give data a strategic importance across functions: using it to drive efficiency in their existing workflows and identify new opportunities,” said Sophie Ruddock, chief operating officer, Multiverse. “Getting it right offers huge potential for return and getting it wrong is costly. We discovered in our joint research with DataIQ that one in every 11 minutes of company time in the UK is spent attempting data tasks unproductively and 8.5% of annual revenue lost on average because of poor data literacy.”
Once data has been cemented as a tool with strategic importance in an organisation, it becomes easier to identify where data literacy skills need to be improved. Sophie continued, “But leveraging data requires more than just the tools, it requires people that have the relevant skills, working in the right places. It is not enough to buy a data tech stack: you need people who can use it.” There are a couple of ways that this can be achieved.
“Outsourcing talent is costly and ineffective,” said Sophie. “We advocate for organisations to turn to reskilling and upskilling initiatives that happen on-the-job to fill talent gaps. There are two reasons this works. Firstly, those already in an organisation are already in role, they know the business and they can ramp up quickly and use data in their existing role. Secondly – and the reason it is important the training happens on the job – is that there is simply no better way to deliver the right training than through applied learning. We often say that the future of learning is working, and it is because learning that happens in real-world settings is hyper-relevant and teaches exactly what both the business and the individual needs.”
However, there is often a difficulty in receiving funding and support for these types of reskilling and upskilling initiatives for CDOs. It has been well-documented that there is a disconnect between decision makers understanding the value of data and assessing its return on investment outside of a financial metric. To combat this, improved storytelling from the data leadership team is required to galvanise support for time and financial investment in data literacy skills programmes for businesses.
“The benefit is clear to organisations,” said Sophie. “In 2022, we measured half a billion dollars return on investment from apprenticeships run by our partners. But there is also a huge benefit to this sort of upskilling to individuals: 69% get more responsibilities after they complete training with us, and they get access to skills that will give their career longevity and access to higher paid, more senior roles.”
There is an ongoing recruitment crisis within the data world as the number of niche and tech-heavy data roles outweigh the number of available and capable candidates, which is driving a bidding war for talent. This has then led to a retention issue where data specialists will find themselves hopping from one business to another as their skills and expertise are in great demand. A part of the solution for these two difficulties is to upskill and reskill existing talent. By investing in individuals, teams and concepts, businesses can be better prepared for recruitment bottlenecks and improve their staff retention by investing in existing staff.
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