The focus of this thesis is to study how organizations can develop their Human Resource (HR) analytics in order to better their readiness to provide valuable insights to support management decision-making. To strengthen its strategic role in the company, HR function must, instead of continuing to base their decisions on former experience and intuition, become more evidence and data-based. The HR function has to expand its offerings from simple reactive reporting to more advanced and predictive analytics.
This paper is a case study conducted on a large, Finnish based, multinational company, operating in the industrial goods and services –industry. The study embraces a qualitative research approach and the objective is to identify the factors effecting and also hindering the development of HR analytics maturity. Moreover, the paper seeks to figure out the current status of HR analytics in the case organization and to provide suggestions on focal areas requiring attention and actions in order to increase the HR analytics maturity.
In order to be able to produce insightful analytics from HR processes, the case organization should, first and foremost, strengthen the data culture among its HR population. Furthermore, the company should decide what it wants to accomplish with its analytical capabilities. Only after that, based on the clarified needs, the firm should start to build a HR analytics team consisting of people with different backgrounds and skills. The individuals in the team should be enthusiastic about the topic, have good intuitive skills, and be able to detect patterns in the information. At the beginning the team may conduct descriptive analytics to describe the current situation at the company. Once the team becomes more experienced and skilled it can move on to more predictive analytics to guide management’s decision-making. Additionally, alongside with the assembly of analytics team, the organization should also pay attention to its data governance. In order for analytics process to function efficiently, data governance cannot be ineffective. Thus, the case organization should establish practices to guarantee the quality of data inputs used in HR analytics
