Work time allocation

This case study regarding work time allocation and salary calculation from a large construction firm illustrates how an organisation can turn complex regulations and calculations into understandable and automated decisions.

Download case

Which challenges did the client face?

The construction company employs a large number of people, and is subject to various Collective Labor Agreements (CLA). When the employees register the hours they have worked every month, the company needs to match the registered work time with the corresponding CLA of the employee, and calculate the required compensation the employee is entitled to.

The company’s biggest challenge was maintaining the CLAs. There was no central system to interpret them. Instead, the company owned several hour registration systems in which the agreements were interpreted and automated differently. This not only lead to a lot of confusion when calculating the monthly compensation of the workers, but also to frequent miscalculations. These miscalculations needed to be traced and fixed manually in a separate Microsoft Excel spreadsheet; a very time consuming and error prone endeavor.

How did we solve this?

The first step to undertake was to create one central hour registration system, which would interpret every Collective Labor Agreement.

This was achieved through decision modeling in Avola Decision. Each CLA was modeled: the specifications made into business rules and the business rules gathered into a decision model. These models were then automated through Avola Decision. Now, when a worker registers his or her working hours the system will assign them to the correct CLA and the calculations will be made automatically. No manual corrections are needed anymore, and the complete calculation is logged so that it is clear why this outcome was reached.

The company needed this system to be easily adaptable and manageable. The business itself needed to have the capabilities of adding another CLA, or to adapt the present ones if regulations called for it. This is where the versioning and governance of Avola Decision comes in. Avola Decision allows a client to build different versions of a decision model, and to run the different versions at the same time. For the company, this meant that one CLA could easily be adapted and transformed into a different version. They could then run both the old and new version of each CLA, allowing them to not just use both systems but to predict and simulate how a change in a CLA would affect the company as well.

Which results did the construction company observe?

The construction company modeled each CLA in the central system and automated it. Did it have the desired effect on the challenges the company faced?

As the interpretation of every Collective Labor Agreement was now automated, the HR employees no longer needed to fix mistakes in the compensation calculations manually. The system vastly increased the efficiency of the company, as it saved the HR employees a significant amount of time (the department reduced 14 FTE within 6 months of the Go Live). Due to the clear structure and audit trail of the CLA in Avola Decision, the construction company could easily trace a decision back, and see which rules had led to the amount a certain worker received. This increased level of traceability made the work time allocation more transparent and easy to audit.

Lastly, the construction company is now fully in control of its work time allocation. The HR users have the ability and knowledge to adapt each CLA in the central system, and to create an additional one when necessary. This adaptability ensures that the system will grow with the company, and is not limited by it.

In short, the company observed an increase in efficiency and traceability while maintaining full control over the work time allocation system. In total the company saved 14 FTE within a time frame of 6 months after Go Live.

Do you want more information about this success story?

You can contact us by filling in the form below! We'll get back to you as soon as possible.