In recent research commissioned by the Data Literacy Project, just 21% of the 9,000 people surveyed described themselves as fully confident in their data skills – i.e. confident in their ability to read, understand and question data.
When it came to working with data, 74% said they feel overwhelmed or unhappy, 36% find an alternative method to complete a task without using data and 14% avoid the task entirely.
Let’s stop and think about that a minute. Hypothetically speaking, that means that nearly three-quarters of employees in each organisation are not just uncomfortable, but overwhelmed by dealing with data. This scale of data illiteracy, and discomfort, has huge implications for organisations looking to use data-driven strategies to emerge stronger from the global pandemic.
Individuals across product management, sales and customer services functions are simply not confident enough to interrogate the data in front of them and not sufficiently empowered to be efficient, increase profitability and provide a better customer experience.
So how have we got here?
I think it is largely explained by two trends.
Firstly, most organisations have limited the power of true data-driven decision-making to a specialist data analyst function rooted in the IT department, or the CEO’s office – a "data ivory tower". As a result, the majority of business professionals within an organisation have little exposure to how strategic decisions are reached, and individuals make decisions based on opinion and gut feel, or reject data purely because it doesn’t match their understanding of the world view.
Secondly, investment has continued to focus on new ways of gathering customer data and the latest technology platforms. Organisations have understood the data challenge as a technology- and IT driven change. They have failed to see the need for all employees to develop a basic level of data skills, failing to become truly data-enabled as a result.
Covid as catalyst (again)
Understandably, the demand for data professionals has increased significantly in the last 12 months. Business leaders, caught off guard by Covid-19, want to ensure they have the in-house data analyst skills to enable true data-driven decision-making going forward, and to be able to understand the real implications on the bottom line of every “what-if” scenario, whether investigating new product lines, adjacent markets or business continuity modelling.
Data engineers and data analysts that can confidently scrutinise data and ask questions that lead to insight-driven actions are much in demand. And will continue to be so. Microsoft predicts that by 2025, we will need an additional 340,000 data analysis, machine learning and AI jobs as well as an additional 430,000 cloud and data roles.
Where are all these data gurus going to come from?
As with the wider tech talent challenge, the answer is not simply hiring in new talent. This flawed approach will, once again, create a situation where highly skilled individuals move from employer to employer commanding a premium at every stage while the overall talent remains static.
Instead, we need to start by building data skills as standard across all of our teams, in every organisation, from SME to global brand. Whatever the scale of the training challenge, there is a solution. QA runs a number of public schedule courses specifically designed to build data confidence and data literacy. My colleagues and I have also built bespoke programmes for high street retailers and global FMCG brands. While large in scale, the programmes typically start with a team, or pilot group. Starting small is sensible. But you have to start.
We also need to proactively build data analyst skills in-house. Data apprenticeships are a great way to do this.
At QA, we offer a range of digital apprenticeships in data, from our Level 4 data analyst programme to our degree-level MSc in Digital and Technology Specialist programme, which offers a specialist pathway in data and analytics, and a Higher Apprenticeship in Artificial Intelligence (Ai) Data Specialist.
Levy-funded apprenticeships can be used to hire in new talent and to upskill your existing workforce, which makes apprenticeships a great way to build data skills among career switchers and upskillers, as well as under 25s.
The tech is here. Data analytics tools, such as Microsoft Power BI, are today more powerful and accessible than they’ve ever been. But for these tools to work effectively, organisations need to establish a solid foundation of data literacy amongst the people using them.
David is a learning and transformation consultant with 20 years' experience in creating technical and learning strategies for emerging technology and digital transformation.
Currently leading QA’s Practices in Data and Digital Transformation across learning, consulting and apprenticeships, he has developed and launched capabilities and portfolios in agile engineering, design thinking, DevOps, data science, engineering and AI during his time with QA.
David possesses significant experience developing talent and transformation programmes at scale, which support executive leadership and L&D teams in talent development objectives. He has deep experience across public and private organisations, including sectors such as finance, health, telecoms and government for clients including MOD, DWP, Natwest Group, PA Consulting, Microsoft, AWS and Google.
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