The public sector could sell themselves better to potential candidates in terms of some of the projects it is working in, according to Alison Adams, head of data science capability, Office for National Statistics.
Adams was speaking at the recent Think Data for Government event in London.
“There’s an awful lot of really brilliant initiatives, spanning so many different areas, such as the environment, around health,” she said. “But also, it’s key that we really sell that we do have career pathways, we do have a clear progression. That’s something that we’ve been really keen on within the data science space – building those career pathways, those competency frameworks.
“I think it’s also about being more inclusive in what we’re doing, and having the right role models, especially in this data science space. So [looking] at all sorts of people from all sorts of different backgrounds and thinking, ‘that could be me.’ There’s quite a bit that we could do in order to improve our attraction into the public sector.”
Adams believes those competency frameworks are becoming more consistent within government and the public sector.
“Those in the analysis function have worked very hard to ensure that there are clear pathways for a lot of you know, within the digital and the analytical base. With the competency framework in particular, that we now have, both in the data and analytical space, that they are being used, both for recruitment and also the development. One of the things that we’ve done is obviously developed a learning pathway which then underpinned this competency framework.”
The case for apprenticeships
Joining her on the expert panel was George Burbidge, enterprise account executive at Multiverse, which advocates for apprenticeships to close the gap between demand for skills and supply of talent. He said organisations often try to recruit talent from a finite and homogeneous talent pool of university graduates.
He quoted another speaker at the event, Tom Smith, director spatial data unit and chief data officer at the Department for Levelling Up, Housing & Communities, who said that “talent is equally distributed, but opportunity is not.”
“We have a huge opportunity to change that,” said Burbidge. “We’re working with councils like Westminster, which is creating avenues by which they’re taking on non-university graduates from within their borough. They’re placing them on data science and data analytical apprenticeship programs. And that takes huge investment from them in terms of a cultural mindset shift, in terms of putting those learning pathways and progression in the interface. There’s a cultural piece around line manager engagement, it’s a whole new challenge to what you’re used to. People are going to come in greener, but these people are so aspirational and have so much potential, that if you can channel that in a constructive fashion, you’re going to have a really diverse and representative workforce that’s going to enable you to systematically tackle challenges around capacity into these key roles.”
Burbidge also made the point that when it comes to capacity, organisations are dealing with overstretched teams that are being asked to deliver more with less. This can create some pushback when adopting the apprenticeship approach.
“Why would we look to actually put more work or more burden on our people when instead we could perhaps look at investing in technology or investing in process? But we know that technology and the cost of it is increasing. [The cost to] a council that we are working with this year alone has gone up by £600,000 just to operate the technology that they had last year. And then to actually change the process – you need the people with the skills to do that, that we know are equally hard to attract and equally hard to retain. So how can you as an organisation cascade that message down from the leadership, free up staff and give line managers the confidence to give their teams the time that they need to learn these skills?
“They’re inevitably going to free up capacity in as little as three to four to five months – on average of five months now on a level four data analyst apprenticeship. Learners will be saving five hours a week in efficiency gains. You’ve got that really small window of zero to four months where it is going to be a challenge, but after that you start unlocking significant gains for an organisation at the entry level and also at your existing workforce level.”
More data skills needed in the wider populace
Nevertheless, it can be a challenge to secure buy-in from leadership. Although Richard Browne, assistant director data at Homes England said it is more difficult to get buy-in from the middle tier of leaders rather than the C-suite.
“[This is] because they are the day to day manager leading the teams and they feel you can take we have this problem at the moment,” he said. “We’ve just launched our academy – we’ve got three tiers of offer from apprenticeships, level three, level four and six…what we’re finding is convincing the middle level of management. It’s quite difficult to free people up for six hours on the job training. So, we use data, we use evidence, we use analysis to sell that back to show ‘look at the return of investment you’re going to get from within five weeks or five months.’ It’s trying to permeate that throughout the agency.”
Browne agrees with Adams that government and the public sector needs to be better at selling itself. He also noted that it is positive to have a DDAT capability framework to work from, but he noted: “Even with the greatest framework in the world, it’s how you embed that in your organisation. I think DDAT is focused on digital teams and digital directorates, not focusing on the data skills that we need. We need more data skills in the wider populace in our organisations to be able to bring build capacity in teams, so wider than that.”
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