Can an algorithm have empathy? Solving the WFM preference puzzle

AI has been part of our daily lives for quite some time now. We trust algorithms to curate our music and map our commutes. But there is a significant psychological gap between trusting a machine to recommend a song and trusting it to manage your team's livelihood.

When it involves Sarah's childcare needs or John's burnout, "trust me" isn't a good enough answer. At Quinyx, we believe that for AI to be a force for good, it must move beyond mystery. It has to be transparent, controllable, and, above all, human-centric.

That is why we are launching The Black Box Project. Throughout this series, we'll tear down the walls of our technology to show you exactly how it makes decisions. We're starting with one of the most debated topics in WFM: Can an algorithm actually handle the human complexity of a living, breathing workforce?

The myth: "Work is too complex for a cold machine."

The most common concern we hear from operations leaders is that automation strips away the "human touch." Many managers fear that by handing scheduling over to an algorithm, they are trading empathy for efficiency. The myth is that AI is a rigid taskmaster, focused solely on business math while ignoring the personal needs that keep a team motivated and loyal.

The mechanic: Quinyx Optimise engine

Let’s crack the lid on that "Black Box." How does the Quinyx Optimise engine actually work?

To allow for varied scheduling needs, our backend is fully configurable. Depending on a company’s specific setup, shift preferences aren't "one-size-fits-all", they can range from neutral data points to weighted goals or, in rare cases, fixed requirements. This flexibility ensures the engine aligns perfectly with the company's unique business rules.

Once these parameters are set, our AI processes millions of permutations in seconds to find the perfect intersection where business objectives meet personal lives. While a human planner might unintentionally overlook a request, the algorithm never forgets.

By defining the "weight" of preferences within the Quinyx system, you effectively dial up the priority of employee requests within the mathematical model. This is what we call "Empathy at Scale." The algorithm ensures every preference is weighed objectively and fairly, removing the unconscious bias that often leads to friction in manual planning.

The reality: Human in the loop control

We know that trust is earned through transparency. That's why we’ve built our AI to be "Human-in-the-loop." The Black Box isn't a vault, it's a tool that gives you more control, not less:

• Objective fairness: The algorithm doesn’t favour any party. Reducing human bias in scheduling ensures equitable treatment and improves employee satisfaction. It promotes fairness and transparency in shift distribution, strengthening trust and engagement across your team.
• Time to lead: By reducing the "puzzle work" of scheduling by up to 80%, we give managers back the one thing they need to lead with empathy: Time. Time to coach, time to listen, and time to truly support their staff.
• The master key: You always have the final say. You can override, adjust, and tweak any suggestion. The engine then learns from your expertise, aligning future schedules with your unique management style.

Quinyx Optimise goes beyond headcount by factoring in skills, availability, and employee preferences. By ensuring the right people are assigned to the right tasks, it improves service quality and engagement, driving better outcomes for both your people and your business.

Why this matters

It's okay to be sceptical. In an era of rapid tech advancement, demanding accountability from your tools is essential. We aren't asking you to blindly trust a box. We're inviting you to see how that box is built and how, by removing the guesswork, we can make work-life better, fairer, and more human for everyone.

Take command of your workforce logic. See how the Quinyx Optimise engine gives you the granular control to prioritise employee preferences without compromising service levels.