Staff planning is a bit like Tetris. Except that the blocks are constantly changing shape, sometimes disappearing suddenly or doubling in size. And someone calls out from the side: ‘Can you please wait until next week to place the green block?’
This is exactly how it feels for many companies when they try to coordinate their employees on construction sites, in service assignments or in shift work. It's a constant juggling act with Excel spreadsheets, requirement profiles and unplanned absences – and usually under considerable time pressure. Increasing skills shortages and rising wages are making resource planning harder than ever before. The McKinsey study "Intelligent Planning: How to solve workforce planning challenges with AI" shows that traditional manual planning methods have long since reached their limits.
The good news? Artificial intelligence can solve these problems! This is possible because AI and cloud technologies have advanced significantly in recent years: they have become more powerful, cheaper and more versatile. AI-driven resource planning thus offers companies the opportunity to take their workforce planning to a new level of efficiency. In short, workforce planning is at a turning point.
Why workforce planning is so difficult – and what factors make it complex
As much more efficient as AI may be than any manual planning, the McKinsey study makes it clear that resource planning is one of the most challenging optimisation problems of all. Why? Because several factors interact, overlapping each other and making planning highly complex.
Let's take a look at the various factors:
◾️ Work phases:
It is not uncommon for jobs to consist of several steps that must be completed one after the other. A construction project, for example, cannot continue until the previous phase has been completed.
◾️ Staff allocation:
Often, a single employee is not enough; a team with the right qualifications is needed. For example, a job may require a bricklayer and a foreman at the same time – so planning must ensure that the right people are available and can work together as efficiently as possible.
◾️ Fluctuations in demand:
Some industries experience predictable demand, such as mining, where the workload is determined in advance. Others, such as the construction industry, are heavily dependent on external factors – weather, seasons or permits can change demand at short notice. This makes planning a real nail-biter.
◾️ Shifts:
Shift schedules can be fixed or dynamic. In some companies, staffing changes from week to week – for example, in the construction industry, where staffing requirements can vary greatly depending on project progress or material availability.
◾️ Mobility:
In many areas – for example, in field service or on construction sites – employees have to travel from one location to another. Travel times and distances make planning even more challenging and have a direct impact on productivity.
What makes the whole thing so complex
In reality, these dimensions constantly overlap. A construction company, for example, works in several phases, has to coordinate the qualifications of its employees, experiences fluctuating demand, changing staffing requirements and is dependent on working at different locations. And then there are the everyday spontaneous changes: an employee calls in sick, a customer needs immediate support, or a project is delayed.
All these conditions must therefore be taken into account and mapped simultaneously – and it is also necessary to respond to changes as quickly as possible, which requires constant updating. This is precisely what makes personnel planning one of the most challenging areas for optimisation.
Why AI is the future of resource planning – McKinsey provides the evidence
Precisely because personnel planning is so complex, there is no way around AI-supported resource planning. The McKinsey study clearly shows that AI-supported resource planning offers advantages precisely where manual systems fail:
🔹 Less idle time: AI schedules employees in such a way that their working time is used optimally and there are fewer unproductive breaks.
🔹 Higher productivity: Resources are deployed so that they are available exactly when they are needed.
🔹 Faster planning: AI creates new plans in a short time – even in the event of spontaneous changes.
🔹 Less administrative work: AI takes care of routine tasks such as shift comparisons and rescheduling, so planners don't have to monitor every detail manually.
The McKinsey study uses the example of a US electricity and gas supplier to show how this works in practice. This industry combines a number of factors that all have an impact on resource planning at the same time, making it an ideal testing ground for intelligent planning. The supplier tested an AI-supported planning solution for six weeks – and the results were impressive:
◾️ Interruptions (emergencies that disrupt the schedule) fell by 75%.
◾️ Order delays fell by 67%.
◾️ False starts (when orders do not start or finish on time due to a lack of resources) were reduced by 80%.
◾️ Total working hours increased by a full 29%.
These figures speak for themselves: AI in workforce planning is not a nice extra, but a real game changer.
AI-powered workforce planning – how Vanillaplan makes it a reality
We have seen that AI in resource planning is highly complex – but also highly useful. That's exactly why we at Vanillaplan have tackled this difficult problem – and we've developed a solution that works!
While McKinsey describes how companies could theoretically proceed, we have taken the step into practice. Our AI is not a concept on paper, but an innovative technology that addresses everyday problems – from spontaneous sick leave to fluctuations in demand to team planning.
🔸 One click to the optimal result – skills and co. always in view
Goodbye Tetris! Our AI creates deployment plans in seconds that take relevant factors into account.
🔸 Spontaneous changes – no problem
An employee calls in sick in the morning? The AI adjusts the plan. Three additional orders come in? They are distributed live.
🔸 Not a PowerPoint vision, but real software:
While many talk about AI, our customers are already using it – every day, in practice.
The result: less stress for planners, less chaos for employees, less waiting time for customers.
Conclusion
McKinsey makes it clear: AI is the future of personnel planning. We would add: the future has already arrived at Vanillaplan.
Yes, resource planning with AI is one of the toughest optimisation problems there is. But that's exactly what we're working on – with success, because our software already solves what many are still discussing as a vision of the future.
👉 Curious? Then we should talk. We'll show you what AI-supported resource planning looks like in practice!
