Samenvatting

Since the start of the COVID-19 pandemic, organisations have drastically started to reformulate the functionalities of their offices. The trend hybrid working has caused office buildings to have considerable low occupancy rates, as employees rather perform certain tasks at home and do not feel like the office and its workplaces optimally supports their work activities anymore. Here, the work activities remained the same, but the needs and preferences of employees have changed. This calls for a shift in workplace concepts. One of these concepts is called activity-based working. Herein, facilities like concentration rooms, leisure areas, meeting rooms and collaboration spaces are designed to provide the optimal space for employees to perform their desired work activities. However, many organisations cope with the issue that these rooms are not being used according to their purpose. This is mainly caused by the fact that employees are not sufficiently involved in the design phase. With this mismatch, office space is not being used optimally. In combination with the surplus many organisations experience due to hybrid working, the potential of technology, in particular big data technologies and its side constraints, have been researched to improve this usage of space and create a better match between the organisational goals and needs and preferences of employees regarding the concept of activity-based working. The main findings were that organisations determine the characteristics of their workplace concept in diverse ways. However, all respondents mentioned that room were being misused, as employees perform individual online meetings or concentration work in large conference rooms. Organisations experience difficulties when measuring these activities and predicting the usage of rooms in the future. Possible big data technologies that provide a solution are sensorics. These gather objective occupancy data that give more insights into how frequently rooms are being used and which are more popular that others. But these cannot measure the actual activities that are performed within these rooms. For this reason, qualitative big data tools are also necessary to draw a complete picture of the usage of workplaces. These qualitative tools can be utilized to question employees multiple times a day about where they are located, what activity they perform and to what extend that workplace optimally supports their work activity. By combining these insights, an organisation can identify the misuse of rooms and assess the needs and preferences of employees, which allows for an optimization of functional space. However, these technologies do come with considerable side constraints. Firstly, the height of necessary investments is relative to the degree which the organisation wants to apply this technology, where simple occupancy sensorics are more affordable than the combination with qualitative tools and analytical dashboards which interpret data. Necessary skills and competences of employees that can correctly analyse and interpret data are also an investment. Secondly, data has to be collected, stored and analysed in an anonymous way to guarantee the privacy of users. It can be concluded that big data technologies may improve the management of activity-based working, given that the implementation and the goal of the application is considered thoroughly. It is not a onesize-fits-all solution, so one must examine the exact workplace issues and its underlying causes. It is advised to involve users in the design phase of activity-based working by using qualitative tools like interactive survey apps, which ensures the adherence of employees’ needs and preferences. This can be paired with applying sensorics in the form of pilot phases, which allows the users to gradually adapt to a new workplace environment, while simultaneously objectively measuring occupancy and collect feedback from users through qualitative surveys. The combination of