Within Workday, users can build new applications. This allows us to lead the way in the development of 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.
AI as a sparring partner for feedback
Recently, we developed an intelligent system for setting goals and receiving feedback. Organisations set new appropriate individual goals each year. AI can help as a sparring partner. It offers the possibility to describe goals and then receive advice from a GenAI application on how to formulate them SMART and whether they align with the received feedback. Our team is currently helping a client to integrate this system well into their organisation.
GenAI understands text very well, regardless of whether it is poorly written or consists of only five sentences. It always offers suggestions for improvements. When employees type in just a few keywords, they receive advice. The app can also analyse the feedback an employee has received to determine what someone still needs to develop. Based on all the data, tailored advice is given for a concrete goal.
When people work in different teams, this application for setting goals is also useful. In organisations where staff often work on different projects, it is helpful if managers can view the development of employees over a longer period. This way, the development of staff gets more priority.
Use of AI improves e-learnings
A model is being developed that further improves e-learnings for staff. E-learnings often consist of the same type of questions. With GenAI, it is 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.
These e-learnings provide much more relevant feedback. The system remains scalable because it’s entirely done by AI. No teachers or trainers are needed to check the homework, and new or better questions can be asked. This ensures that people really have to absorb the material.
Tailored sickness and absenteeism policy
For the sickness and absenteeism policy of organisations, the team have devised a more efficient process. If someone is sick for a long time, both the employee and employer have various obligations to ensure that someone can reintegrate as quickly as possible, such as a clear plan of action. This process is now fully facilitated through the system, so organisations don't have to think about it.
AI helps by predicting absenteeism faster based on data. This gives organisations a better prognosis when absenteeism will rise, allowing risk factors to be identified more quickly. That’s a good example of machine learning. We then look at the data to see what the impact is.
'Community of solvers has broad expertise'
Our creative team can anticipate the client's problem well. The community of solvers has broad expertise. Within PwC, there is a lot of knowledge about matters such as labour law, payroll tax, and personnel policy, allowing an efficient application to be integrated quickly via Workday.
The team also tries to build that kind of expertise into our applications. Additionally, our team distinguishes itself by thinking along. The solutions that have now devised largely consist of new technologies.
The goal of these applications is for employees to talk to their supervisors about their development more quickly. This is even encouraged, so employees are more engaged in how they can contribute to the organisation's strategy. Ultimately, employees should spend less time in the systems and more with their supervisors because they are now better supported by technology.
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