The HR department of the Federal Public Service Justice had a specific request: "Can you help us digitise and optimise some of our processes using Microsoft Power technology?" This posed a challenge due to both the specificity of the requested app and the complexity of the numerous processes that could be optimised. Our colleagues at Roboest took on the project and brought in Humain to assist from a strategic perspective, ensuring a clear outline of opportunities before taking action.
We gathered comprehensive input on how the processes were handled and, more importantly, why they were handled that way. Public Services often have strict rules and specific procedures that need to be followed, so it was crucial to understand the full context and manage all associated risks. This fundament was important to reduce the implementation time as much as possible within the complex structure that is Federal Public Services.
We began this project by conducting interviews and organising workshops, which helped us identify a key area for optimisation: the recruitment process. This process relied on a central Excel document, managed entirely manually, containing information for over a thousand job vacancies. Additionally, numerous linked Excel files held even more data. This led to many inefficiencies and inconsistency issues. At the end of the road, Roboest and Humain created a scalable and extendable platform containing various applications that digitally support core HR service processes.
The biggest challenge was managing the various stakeholders and preparing our target audiences for change. The steering committee consisted of many higher-ups, resulting in a lot of visibility throughout the entire organisation. A clear business case, well thought-out roadmaps, and detailed timlines were essential to support the vision of the Federal Public Service and this project. We supported Roboest in developing these applications by managing stakeholders, conducting user tests, and preparing employees for the new tool. We used agile and iterative methods to obtain feedback quickly and minimise total implementation time.
