How data and AI can help, not hinder, strategic workforce planning

Despite funding and training schemes being in place to help the construction industry meet its workforce demands, supply challenges continue. An ageing workforce, lack of investment in talent and a retention gap are just a few of the factors resulting in the skills shortage – often described as a structural crisis.

Beyond just encouraging young people to enter the industry, ensuring talent is recognised and employed strategically from graduate level all the way to retirement will be integral to closing the gap. To do this, construction will need new technology on its side.

New tech can improve what has historically been a difficult process of monitoring current and potential employees and determining where their skills are needed. Owning and maintaining even just basic data on staff requires a significant time investment that could be seen as better spent elsewhere – a frustration for workforce planning managers and boardrooms alike. But where adequate insights are unavailable, projects are more exposed to risk.

Although it may seem counterintuitive to introduce AI as a helping hand for human-oriented issues, this couldn’t be further from the truth. By using AI-enabled software to support the data gathering that can drastically improve strategic workforce planning and development, the industry will be able to place the right people on the right projects at the right time.

For some time, contractors have been reliant on Excel spreadsheets built from data that has been manually inputted and layered on over multiple years. These spreadsheets typically contain standard necessary information on each individual candidate or employee, outlining basics such as name, location and project history.

Software platforms are beginning to gain recognition as a tool that can not only speed up the effective tracking of employee data, but also to simultaneously gather and present richer data sets – ultimately building a more nuanced profile of individuals, noting their strengths, technical competencies, personality types and preferences.  

AI-enabled software can also make recommendations as to which projects best suit employee skill sets, personalities and interests. Such software can provide data that helps workforce planning managers more easily identify current gaps in the workforce and suggest who might be best placed to fill them. No one should leave the planning to the machines: they should aim to use technology to generate more comprehensive data that they can then interpret.

Greater digital fluency and confidence across construction will not just make a workforce planning manager’s life easier (although that is certainly true), it will also have a positive impact on project delivery, employee retention and client satisfaction. Richer data will enrich the workforce itself and bring us closer to solving burgeoning resourcing problems.

Using an AI-enabled workforce planning platform will make it easier to gain full workforce visibility and a deeper understanding of each applicant’s areas of interest and expertise. Having once manually delineated this data, workforce planning teams can now spend the time they have gained back from handing over admin to AI focusing on finding the best fits for each team and project from the get-go.

Personality tests are an increasingly important part of planning, especially when it comes to senior hires who both oversee the architecture of a team and influence its working dynamic.

Colour coding personality types can help balance teams better by using the code to create a visual map of how each team member’s strengths intersect and complement each other. The ability to quickly recognise skills, competencies, personalities and experience (as well as how these could be enhanced) allows the hiring, training and onboarding process to be more sensitively tailored to project and employee need.

Using personality data to inform planning invariably leads to people being placed on projects they are most likely to love or succeed on, so this kind of data is equally helpful to service clients better. But a workforce and the possible strategic combinations within it will evolve based on project type and needs, and no workforce planning manager has enough time in the day to revise, reimagine and reassess the data alone. AI will be a vital helping hand in creating and maintaining these assets as a reference point.

When employees stick, it makes it that bit more justifiable to invest time, money and effort into training and upskilling them. The cycle then continues from here: as career security and personalisation increases, so does employee satisfaction and the quality of output, too.

By using a comprehensive overview of individuals’ strengths and areas of expertise, it will be less likely that anyone would begin to feel stagnant in their jobs and to move on as a result. If more construction companies exploited data-driven employee insights, we’d not only see the skills gap begin to close and retention boosted but also greater project success from having the best people on the job.

Taking a people-focused approach to workforce planning through data is also a boost for business.

Analysis has proven that the most successful projects – those that are completed to standard, on time and under budget – are led by teams with an equal balance of high technical competency, personality types, skillsets and experience. This can all be better determined by insights gathered and mapped during the onboarding process.

Data also provides workforce planning managers with a greater understanding of whether it is viable to bid for new projects, saving time, money and resources by more accurately predicting the success rate. Instead of relying on other projects ending, a data-led strategy can identify opportunities and the strongest available people to put forward for them at each stage.

When used to its maximum potential, data and AI can strengthen human interaction and potential, giving workforce planning teams more time to focus on individuals’ growth – and this is what the construction industry needs.

AI is proving to be a fundamental pillar of workforce planning, not just a nicety to experiment with on the fringes. But while AI can offer next-level visibility, the core data and what is done with it next is still very much human. By increasing retention and employee satisfaction while delivering notable project and performance results, the construction industry will undoubtedly be better off by exploring new technologies.