Jobs sit at the heart of delivering the changes required to support improvements in customer experience. How they are designed in the public sector is critical to harnessing talent and skills across organisations and systems, ensuring inclusion, accessing talent, developing people and planning for the future.
The way jobs and skills are currently organised and managed across many local authorities is a barrier to public sector digital transformation. So much so that, according to EY, “governments won’t be able to provide a 21st century citizen experience and better citizen outcomes with 20th century skills and working practices”.
Across many local authorities, the current process for creating, organising and governing jobs is manual, inefficient, inaccurate, resource-intensive, and poor quality, and this is why the need for digital transformation is so critical for delivering a 21st century service.
AI has a huge role to play in digital transformation in the public sector, as underlined by the recent announcement of the government’s AI Opportunities Action Plan, which aims to use technology to drive efficiencies in the public sector.
The plan states that the public sector ‘should rapidly pilot and scale AI products and services…this will drive better experiences and outcomes for citizens and boost productivity.’
Traditional ways of working need to be improved, and there’s a need for greater digital transformation across the public sector. Those using public services have very different expectations about how they access services, compared to five or ten years ago.
This government initiative is potentially a significant step toward modernising the public sector and delivering more efficient local government services, and enabling public sector staff to focus on providing better service for the public through automation of admin tasks.
AI has the potential to transform how local authorities manage jobs and skills. Under this initiative, AI-powered tools will be deployed to streamline job descriptions and automate key processes, ensuring greater consistency across councils and public sector bodies.
An approach to jobs and skills using AI can enhance talent mobility, improve employee engagement, and ensure that councils can respond effectively to changing community needs.
However, this approach has to take into account the current state of the public sector. Data on jobs and skills can often be disorganised and inconsistent, created by different teams and stored in a range of formats.
Before councils and local authorities can implement AI for recruitment and a skills-driven approach to workforce planning, they must first establish a strong foundation, which includes the standardisation of job descriptions, the creation of a skills taxonomy, and the centralisation of jobs and skills content.
For some local authorities, there is also a need for data transformation to ensure data is digitised and accessible, as well as change management to equip HR teams with the knowledge and skills to use AI tools effectively.
For all local authorities, digital transformation and the use of AI to enhance and automate processes can bring a range of benefits.
Current systems require accurate job structures and job titles in place before implementation. The mistake many organisations make is simply loading in what exists already, which is likely to be outdated, rigid, and not fit for purpose. If jobs are not organised and up to date, this will hinder the value organisations can get from their technology investment.
AI can streamline the surfacing of skills within public sector organisations by automating skill identification, mapping, and analysis.
Skills inference using natural language processing (NLP) and machine learning can enable the surfacing of skills from sources such as job descriptions, employee profiles, and training records.
This enables local authorities to identify internal talent, match employees to new opportunities, and pinpoint skill gaps. By reducing manual effort and improving visibility, AI helps public sector organisations build a more agile, skills-based workforce.
For many platforms used by local authorities, the job structure powers the recruitment workflow. Without a clear structure in place for jobs, and centralised job descriptions, HR, Hiring Managers and Recruiters can waste a significant amount of time writing duplicate content or using out-of-date job descriptions that don’t accurately reflect the role.
Automation of the job description process creates greater efficiency, and ensures that job data is standardised and up to date, and more accurately reflects the skills needed for each role.
This centralisation and standardisation of job descriptions ensures that jobs remain up to date in terms of skills and responsibilities, enabling the public sector organisations to adapt more effectively.
With increasing pay equity legislation being introduced, along with the requirement to report on equitable pay practices, an accurate job framework is fast becoming a critical tool for local authorities to implement, monitor and govern pay equity strategies.
With a standardised job structure in place, pay equity analysis is made significantly easier, removing the management discretion around jobs and pay.
Having accurate up-to-date job and skills content is critical to objective setting and performance management. When this is working well, job content flows seamlessly from the recruitment process to the performance management process. If job content isn’t accurate, and doesn’t reflect the realities of a role, this can lead to employee attrition.
Research has shown a direct link between accurate job descriptions and attrition; 43% of employees who leave within 90 days state the reason for leaving is that their day-to-day role wasn’t what they expected.
An approach which focuses on skills has the same effect, improving job satisfaction for employees, and increasing retention rates.
Many organisations are moving to a skills-based approach and redesigning their operating models and strategies to have skills at their core.
This enables them to become more agile, to have higher levels of employee engagement, to encourage innovation and to show faster rates of growth.
A clear, streamlined job structure, with data available on the skills contained within the organisation enables possible career paths to be mapped out and communicated to employees. This opens up training and development opportunities and career paths up and around the organisation.
Employees will have clear visibility of roles and skills across the organisation and can identify possible roles in different teams and departments rather than simply focusing on movement within their current team.
From an organisational perspective, this enables greater succession planning, as skills can be identified internally to fill upcoming gaps in capability.
Planning your workforce around the skills that are needed now and in the future is a critical task that all local authorities need to undertake.
Skills data enabled by AI improves workforce planning and analytics for local authorities by identifying skill gaps, forecasting future workforce needs, and optimising talent allocation.
AI can be used to analyse employee skills, predict shortages, and recommend targeted training. It also supports data-driven decision-making, helping councils align talent with evolving public service demands.
Automation of workforce analytics enhances efficiency, reduces hiring costs, and ensures local authorities have the right skills in place to meet future challenges and deliver better public services.
Where to start
As a starting point for any organisation, technology can fast-track the harmonisation of your organisation’s job and skills data, reducing the process from years or months to just weeks, giving you the scope to start transforming jobs across your council or local authority.
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