How does ML6 predict its hiring needs using HR data?

04.08.2025

In our latest webinar, we were joined by Julie Plusquin, Talent Partner at ML6, to explore a challenge that every recruiter will recognize: how do you know in time how many people you will need? Especially in a project-driven organization like ML6, where there is no fixed recruitment plan, estimating future hiring needs is anything but straightforward.

Yet ML6 succeeded in fundamentally changing the way they plan their workforce, thanks to a self-developed tool that combines sales and delivery data into one concrete metric: “FTE needed” per month.

Julie gave us an open look into that journey: how they got started, which data sources they combine, what the biggest challenges were, and most importantly, what benefits this approach delivers in practice.

The challenge: a continuous need for talent, but exactly when?

ML6 operates entirely on a custom basis. Rather than offering standard products, the company develops AI solutions tailored to each client. This makes their work exciting, but also unpredictable. After all, how do you know when you will need specific profiles and skills?

In the past, the recruitment team relied on annual budget exercises as the foundation for their hiring plans. While this provided some direction, it did not always reflect reality. As a result, they were sometimes informed too late about major projects, causing them to miss out on candidates or forcing them to recruit under significant time pressure, which did not always benefit quality.

The trigger for adopting HR analytics was the realization that opportunities were being missed because the organization was reacting too late. At the same time, they knew that the necessary data already existed within the organization—it simply was not yet being combined in a smart enough way. This led to the idea of a more predictive way of working, powered by data from different teams.

The model: Staffing sync + hiring sync

ML6 combines two perspectives to create a well-founded recruitment plan. Each month, they bring these together in what they call the staffing sync and the hiring sync.

1. Staffing sync: how many people do we need?

This first step is based on two data sources:

  • Sales data from HubSpot: which projects have a high likelihood of being sold? How large are they?
  • Delivery data from Teamleader: who is working on which project? How much capacity is still available? Which employees are (temporarily) unavailable?

This data is automatically consolidated into an Excel sheet. Based on this information, ML6 calculates the number of FTEs needed for each month. This figure turns out to be surprisingly valuable, as it highlights peaks in demand, staffing shortages, and unexpected workload increases months in advance.

It helps us identify when we need to step things up. It’s a tool that provides guidance.

2. Hiring sync: who exactly do we need?

The number generated during the staffing sync serves as a starting point, not an end goal. During the hiring sync, the recruitment team and hiring manager discuss:

  • Which profiles are behind this number?
  • Are we looking for senior, junior, or functional profiles?
  • What budget and business context are associated with these hires?

This turns an abstract number into a concrete hiring plan. And even more importantly: it becomes a topic of discussion. Because at ML6, one principle is clear: Data provides direction, not instructions.

What makes this approach smart (and what should you watch out for)?

ML6 demonstrates that, with relatively simple tools and strong collaboration, it is possible to gain remarkably clear insights into future hiring needs. What makes their approach so powerful?

  • They work with what they have. No sophisticated BI dashboards, but an Excel sheet into which data from HubSpot and Teamleader is automatically imported.
  • They apply weighting factors. For example, sales teams tend to overestimate when deals will actually start, so those projections are adjusted accordingly.
  • They continuously evaluate. For instance, Julie and her colleagues initially included early-stage sales opportunities in their forecasts, but these proved to be too unpredictable. Over time, the focus shifted towards more realistic scenarios.
  • They involve multiple perspectives. The output of the staffing sync is only a starting point. Context remains essential and is gathered through discussions about profile types, project complexity, and planned events.

But this approach also requires discipline. The biggest challenge for ML6? Keeping everyone involved and accountable. Data can only provide meaningful direction if it is accurate, and maintaining that accuracy requires ongoing effort in stakeholder management, communication, and continuous reinforcement. As Julie aptly put it:

A tool can be built perfectly, but if there is no adoption, it has little value.

The conclusion: what value does predictive HR data deliver?

The staffing sync has become an indispensable part of how ML6 operates. It helps them respond more quickly, make better-informed decisions, and collaborate more closely with the business. Recruiters know where to focus their efforts, can better anticipate upcoming peaks in demand, and feel more confident in discussions with hiring managers.

In short: it does not provide predictions with absolute certainty, but it does offer a strong compass for making timely adjustments and better workforce planning decisions.

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