As a company grows, it becomes more challenging for founders and recruiters to maintain company culture and value-matching throughout the recruitment process. The founders must rely on internal HR or recruiting agencies, and formal requirements must be expertly defined to guide a successful recruiting process. Traditional degree-based and skill-based recruitment approaches cannot always fulfill conventional positions and may result in a higher turnover risk. Therefore, a value-oriented recruitment tool has been developed to support the analysis and matching of the company's, employees' and candidates' values.

A prototype of a value-oriented recruitment tool has been developed using "no-code" principles, and its evaluation has been carried out in an experiment. The experiment includes an actual case study, where the prototype is integrated into the recruiting process of a startup. A series of semi-structured interviews have been conducted with the startup's decision-maker and three candidates and evaluated with a qualitative analysis. The focus of the interviews has been on whether the prototype has the potential to improve company culture, as well as eventual suggestions for improving the prototype and value-based recruitment.

My study demonstrates a lack of tools in this area and highlights that people are essential in creating a positive company culture. The developed prototype aims to improve company culture by optimizing the pre-selection phase during recruiting. The prototype supports HR people by providing an additional data source about a candidate's cultural fit. This data influences the final decision on whether a candidate should be invited to the interview or not. The prototype's qualitative evaluation indicates that decision-makers and candidates see potential in such a tool to facilitate recruiting process. There have been several suggestions on how to improve the prototype: filtering of candidates in the dashboard; possibility to set weights for value dimensions; differentiation of the value scores of various departments; optimization of charts; and visualizing data of candidates in a more comparable fashion, to name a few. In the following steps, a spin-off is planned to be founded by the student, and findings and suggested features will be implemented before the launch of the prototype. Further studies will be conducted at FHNW to evaluate the product-market fit and affordances in diverse industries.