With ‘data’ increasingly cementing itself as one of the public sector’s favourite buzzwords when talking about digital transformation, we’ve seen more and more initiatives announced across Government that focus on the centrality of data and how the civil service can use it better. This is by any account a good thing, and the longtime champions of public sector digitalisation among us certainly welcome the rising motivation within government to level up data capabilities across the civil service. Just last month, Cabinet Secretary Simon Case announced an exciting initiative that will see all civil servants - across all levels and specialisations - receive at least one day of dedicated data training this year. This comes alongside several other digitally-focused initiatives being rolled out across the civil service focused on building more technical/STEM capabilities into our public sector workforce. These have come as a welcomed response to a critical digital skills gap within the civil service, with the UK Civil Service Digital Skills Report revealing that less than half (42%) of civil servants believe that their department has the tools, resources and skills necessary to utilise technology in transforming the public services they deliver. Yet this does not come at the expense of staff motivation to digitally upskill, with the same report finding that 75% of civil servants say they would like to receive more digital skills training; capturing this motivation and translating it into outcomes is the challenge Government is currently facing head on.

Training days are a welcome and a critical step towards building a civil service equipped for a digital future. This kind of initiative reflects a mindset which understands that data skills are no longer just a DDAT (Digital, Data and Technology Profession) responsibility, but that data should be seen as an asset for everyone to use to deliver better services, more efficiently. Particularly for leaders across the civil service, empowering them to be able to both work with data directly (analysis, manipulation, predictive modelling etc.) and to draw actionable insights from data will become essential to all steps of the decision-making process.

All this in mind, data skills alone cannot build a truly data-driven civil service for the future. Even if we made every civil servant an expert in how to manage, analyse, and draw insights from data, we’d be left with an unfinished picture of a modern, data-first civil service. The impact of boosting data skills could fall short without also supporting agencies to create a conducive organisational context that maximises how staff apply their skills within daily practice.‘Organisational culture’ plays a critical enabling role in the success of any type of digital upskilling. This is the underpinning context government leaders cannot afford to delay improving, let alone ignore altogether. If the goal is to build a civil service empowered by data, embedding a ‘data culture’ alongside the necessary skills training from the start must be non-negotiable. So what does a ‘data culture’ look like in practice?

‍A 'data culture' describes an organisational environment where people possess top-class data skills, and are ready, willing and enabled to apply those skills to their fullest potential. Technical upskilling addresses the skills component, but must also be accompanied by action to shift the norms, values and practices of an organisation to leverage those skills in a way that delivers organisational objectives connected across teams and departments. To ensure government’s workforce is empowered to apply its data competencies, we suggest six complementary initiatives:

‍

1. Upskill leaders to review and reset organisational data culture.

‍Using data poses knotty challenges for any organisation setting out to maximise its value. Leaders across government must be given live,    interactive training opportunities to make sense of how each layer of their organisational context - culture, behaviours, partnerships, spaces, and processes - play a role to hinder or enable stronger data practices. Leaders must be equipped and empowered to pull the levers required to understand and facilitate the conditions for success across these layers, and in so doing, their teams.

2. Identify knowledge and skills gaps and rebuild job descriptions where required

‍Through the same learning and workforce discovery, gather insights into the current job descriptions of individuals who are expected to utilise data in new ways. This type of discovery will reveal where practices and skills can be upgraded, where job descriptions may need to be adapted, and where new data staff need to be brought in. Adapting to new tools may require rebundling job tasks into the jobs of the future.

3. Link individual practices and job task expectations to performance development metrics and organisational goals

Use learning and workforce discovery to analyse job tasks of all individuals and build demonstrative data capabilities into performance development metrics. Further to this, link individual performance development metrics for data to wider organisational data goals. By doing this, a direct connection is forged between individual behaviour and practices and desired organisational data outcomes, creating a foundation for effective incentivisation.

4. Undertake learning needs assessment, and monitor learning outcomes

Ensure data users’ learning requirements are well identified – and targeted to desired performance outcomes – in order to facilitate effective and efficient training outcomes for all data roles. For new data competencies, learning-oriented user research adopts a practical and behavioural approach, personalising learning and minimising training time, while allowing digital transformation leaders to effectively monitor performance outcomes related to training.

5. Optimise data workflows to be user-centred

Data-enabled digital transformation should begin with end-user research to understand the criteria staff use to make decisions and how they interact with information and intelligence via available tools. For instance, testing users’ preferences for consuming insights and applying them to new decisions is important. In social care settings for example, agencies have begun to share data through AI-generated text, rather than directional data visualisations, as this was found to improve data understanding and utilisation.

6. Embrace innovative technologies

Departments and agencies across the civil service should foster a ‘test and learn’ culture that evaluates, experiments with, and pilots new data technologies - such as Privacy-Enhancing Technologies (PETs) - alongside building a data-equipped workforce. When done responsibly, embedding systems which encourage testing innovative technologies can not only unlock new efficiencies and capabilities, but more broadly supports the mission of building a digitally-empowered civil service of the future.

‍

‍

‍

To find out more about how PUBLIC supports public sector organisations to embed a data culture which serves their organisational objectives, reach out to Elina, our Deputy Director of Learning and Workforce Transformation (elina@public.io) and Mahlet, our Data Services lead (mahlet@public.io) for a chat!