'We want employees to spend more time with their supervisors'

Within Workday, users can build new applications. "We are at the forefront of developing these applications within the Workday ecosystem. The apps we build ensure that HR, managers, and employees have a better experience in Workday, and that processes become more efficient with the help of AI," says Leunisse.

AI as a sparring partner for feedback

Leunisse and his team recently built an intelligent system for setting goals and obtaining feedback. "Everyone sets new individual goals each year that fit the organization. What we see is that it helps a lot if you use AI as a sparring partner. You can describe goals and then get advice from a GenAI application on how to formulate them SMART, and whether they align with the feedback you have received." Leunisse and his team are now helping a client integrate this system into their organization.

"The advantage is that GenAI understands text very well, and it doesn't matter if it's poorly written or only five sentences long. You can always get suggestions on how to write things better. If employees only type a few keywords, they receive advice. If you look at the feedback an employee has received, this app can investigate what someone still needs to develop. You get tailored advice for a concrete goal, based on all the data." 

When people work in different teams, this goal-setting application is also useful, says Leunisse. "At this organization, staff often work on different projects. If a supervisor doesn't know the teams well yet, it's nice to be able to view an employee's development over a long period. If all that ends up in a filing cabinet somewhere, the development of your staff has less priority."

Using AI to improve e-learnings

Leunisse is also working on a model that makes e-learnings for staff even better. "E-learnings often consist of the same type of questions. With GenAI, it's possible to ask more dynamic questions. It's an application that ensures they can quickly develop new questions, but we can also alternate with unique open questions. And it shows which parts of the training you already understand well and where you still need to work."

According to Leunisse, these e-learnings provide much more relevant feedback. "It's still scalable because it's entirely done by AI. No teachers or trainers are involved in checking the homework, and you can ask new or much better questions that way. So you also have the guarantee that people really have to absorb the material." 

Tailored sickness and absenteeism policy

For the sickness and absenteeism policy of organizations, Leunisse and colleagues have devised a more efficient process. "If someone is sick for a long time, as an employee and employer, you have various obligations to ensure that someone can reintegrate as quickly as possible, such as a clear action plan. We have now fully facilitated that through the system, so organizations don't have to think about it."

Leunisse continues: "AI helps us predict absenteeism faster based on data. This gives organizations a better prognosis of when absenteeism will rise, allowing risk factors to be identified more quickly. That's a real example of machine learning. We then look at the data to see what the impact is."

'Community of solvers has broad expertise' 

The solutions that Leunisse and his team come up with require a lot of knowledge. "We work with a creative team that can anticipate the client's problem well. Our community of solvers has broad expertise. Within PwC, we have a lot of knowledge about things like labor law, payroll tax, and personnel policy, allowing us to quickly integrate an efficient application via Workday."

"We also try to build that kind of expertise into our applications. What sets us apart is that we like to think along. The solutions we have now devised largely consist of new technologies."

Leunisse ultimately wants these applications to lead to employees talking to their supervisors about their development more quickly. "We even want to encourage them to do so because that way we ensure they are more focused on how they can contribute to the organization's strategy. Ultimately, employees should spend less time in the systems and more with their supervisors because they are now better supported by technology."