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Dynamic workforce planning gains ground in more turbulent economy

Some organisations are developing dynamic workforce planning approaches to cope with increasing economic turbulence and change – the South Central Ambulance Service is one

Market uncertainty and the acceleration of both internal company and external market change are encouraging at least some employers to explore the possibilities of using dynamic workforce planning to gain competitive advantage.

Workforce planning in its guise as headcount management, where demand for labour is matched to supply based on a given budget, has been an established practice in the manufacturing industry and its wider supply chain for many years. Over time, it has also expanded into other markets, including retail, technology, telecoms, energy and hospitality.

Helen Poitevin, vice-president for human capital management at market research and advisory firm Gartner, says that to date, workforce planning has predominantly remained a niche function that is staffed by a small team of specialists in organisations with 5,000 employees or more. While these larger organisations tend to use workforce planning applications, smaller players more often rely on manual spreadsheets to do their calculations.

But Poitevin estimates that 5-10% of the market is now either adopting, or is ready to adopt, its more sophisticated cousin – dynamic workforce planning systems.

This approach involves automating the creation of strategic workforce plans that can be adjusted quickly based on different data inputs to align with operational requirements. The idea is also to continuously monitor the effectiveness of these plans and make adjustments in order to respond to changes in talent demand or supply, as required.

“The more dynamic you go, the more you need relevant skills and appropriate data, which can be hard to find as HR systems are sometimes inconsistently implemented across geographies,” says Poitevin. “But while most organisations will know which job categories exist and how many people they have, querying skills data is where it’s really challenging.”

The problem here is that collecting and validating skills data is a very labour-intensive process and such information tends to go out of date quickly. This means that the downsides of going down this route have traditionally outweighed the benefits. The situation has also not been helped by under-investment in data analysis and modelling skills in a more general sense.

Understanding skills gaps

But it is this ability to understand skills gaps in order to act on them more effectively that is currently most appealing to many employers. As a result, this element of dynamic workforce planning is the one most likely to drive the adoption of such systems more widely, says Poitevin.

“Many organisations are experiencing high attrition rates and so need to retain their employees and continue to upskill and reskill them,” she says. “In addition, as organisations invest more in skills development and skills data, they can also use it for dynamic workforce planning, which means the two processes feed each other.”

Betsy Summers, principal analyst for the Future of Work and Human Capital Management at market researcher Forrester, agrees. She sees dynamic workforce planning as being of particular interest and value to employers that “have lost market share and are trying to regain a competitive advantage through talent in a more strategic way”.

“Maybe their CEO is asking ‘what skills and capabilities do we need to have internally so we can meet our goals?’ and the HR or people leader doesn’t have a good answer,” she says.

The advantage of using a dynamic workforce planning system in this context, says Summers, is that it helps them “connect the dots between business strategy and skills and roles, and translate that into different cost scenarios to help answer questions like: how much would it cost and how long would it take to buy or hire those skills? Build those skills by upskilling or reskilling? Borrow those skills using contingent labour or consultancies, or ‘bot’ those skills by outsourcing them to technology?”

Read more about workforce planning

A key challenge at the moment, though, is that there are few options available on the market that can do everything, while at the same time “helping to bridge the gap between finance and HR”, says Summers. “Most tools are designed for only one of those users.”

Poitevin is also of a mind that the market for such technology is immature. She sees it as currently being divided into two key areas: startups, such as TechWolf, which focus on helping employers understand their skills make-up using artificial intelligence (AI) to undertake predictive modelling; and traditional workforce planning tool suppliers, where the skills modelling piece is more limited.

However, Summers believes the secret to getting dynamic workforce planning right does not necessarily lie with any “singular tool”.

“Investing in talent intelligence and skills ontologies to feed into workplace planning efforts will result in a scalable approach to understanding skills gaps and choosing ways to close those gaps,” she says. “Investment in people analytics tools to answer hard questions like ‘why are people leaving?’ or ‘what do our highest performers have in common?’ will also help better inform workforce plans. So it’s about the health of the entire ecosystem.”

Dynamic pricing and the race to the bottom

Meanwhile, Iain Fisher, future of work and customer experience lead at technology research and advisory firm ISG, believes another market driver for dynamic workforce planning systems will be “the rise of the contingent worker”, an area where he is already seeing the emerging concept of “dynamic pricing”.

This idea, which is being explored by some gig worker hiring platform startups, centres on paying workers based on peaks and troughs in demand. This means they receive higher pay when the labour market is competitive and given skills are in short supply, and lower pay when their availability is high.

Fisher says a similar approach is also being introduced by some of the big IT outsourcing suppliers that provide helpdesk and managed services, where margins are often tight.

“Where they’ve got level one back-office helpdesk and services support, it’s cheaper to use robots,” he says. “But when they’re looking at level two and three costs, some are using workforce planning systems to predict what they need and putting in dynamic pricing models.”

But there are risks in such an approach, says Fisher. For example, although there are wage protections in place under UK law, the same is not necessarily true in other countries, which creates the danger of a “race to the bottom”.

One organisation that has introduced a dynamic workforce planning approach – minus the dynamic pricing element – is the South Central Ambulance Service NHS Trust.

Case study: South Central Ambulance Service NHS Trust

South Central Ambulance Service NHS Trust introduced a dynamic workplace planning system about four years ago to help it cope with ever-increasing demand, not least from an ageing population.

The trust covers the counties of Berkshire, Buckinghamshire, Oxfordshire and Hampshire and needs to schedule the activities of about 3,500 employees across 29 sites each day, which means rostering is complex. It had previously used three large spreadsheets to do the job, copying and pasting data between them.

But as Steve West, director of the organisation’s planning and performance directorate, points out, doing so “brought in the risk of error and there being different versions, with different people looking at different numbers”. He adds: “The operational planning sheet had grown so much, it took 15 minutes to open and five minutes to do a calculation, which no longer worked for such complex operational models.”

Another driver for change was that the organisation was keen to enhance the basic forecasting capability offered by its spreadsheets in order to make the process more dynamic. As a result, it opted to implement Anaplan’s cloud-based workforce planning applications and its PlanIQ AI-based forecasting and scenario modelling module.

The aim was two-fold: to enhance the Ambulance Service’s day-to-day resourcing over a six-week planning cycle, and to improve its strategic business planning over a two-to-five-year period.

The benefits of better workforce planning

“It’s made our forecasting much more accurate as it’s now very dynamic and changes in demand are reflected very quickly in our workforce requirements,” says West. “When you’re trying to drop an ambulance in seven minutes to an emergency after someone’s called the switchboard, you have to have the right staff there when you need them – that’s the problem we’re trying to solve.”

But more accurate forecasting also saves money, which can be pumped back into front-line services. Every 0.1% of improvement generates a £70,000 saving out of an annual overall resource budget of £150m. As West points out, “small variances in that environment have huge benefits”. Implementing PlanIQ has so far boosted forecasting accuracy by 1.7%, leading to “significant” financial benefits, he says.

The workforce planning system now handles more than one billion records a month and pulls in live data every 15 minutes from sources, such as electronic staff records, financial applications and a third-party big data store from Amazon, which includes weather and crime information to give a better understanding of the wider societal context.

“We can now see on a live basis what the resourcing profile is every hour over the next few weeks and years, so we have all the information we need at our fingertips,” says West.

This capability proved invaluable during the worst of the Covid-19-related disruption as the system “made us far more agile, which meant we remained the best-performing service throughout the pandemic”, he adds.

“Everyone started ringing 111, so we got really busy and it tended to peak in the evenings. But we picked the situation up very quickly and immediately created more shifts in our workforce management system, which had a direct impact on the resource we had available – so the system was key.”

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