Making the change to Datadriven HR
By Gido van Puijenbroek
Many companies are beginning to embrace a data-driven HR approach. However, this shift is not always as straightforward as it may appear. In this piece, you can read a case study in which we successfully transitioned a client to a more data-driven way of working.
Our client is a financial services provider, operating in more than 20 countries. The Netherlands is an important market for this company.
The Dutch branch has around 4,500 employees and more than half of the company’s costs are staff related. The employees are a key to success, but also the company’s major expense.
The organization considers the employees to be of great importance and wishes to make their HR processes more data-driven.
AnalitiQs received the request to analyse the current situation around data-driven HR, to formulate an ambition together with the HR management team, to turn this ambition into a roadmap and to assist with the first implementation phase of the roadmap.
The approach consisted of four parts: creating an overview of the current situation, formulating an ambition, creating a roadmap and implementing the roadmap.
- Creating an overview of the current situation
The first step consisted of desk research. We studied current reports, analyses, data, practices and systems. After that, we conducted interviews with people from Business, IT, Finance and HR departments. The purpose of these interviews was threefold. Firstly, they were intended to deepen the understanding gained from the desk research. Secondly, it was important to describe less tangible concepts such as “support from the management” and “expertise”. Finally, the interviews were used to collect information regarding needs and wishes, business questions and challenges that might be used for pilot analyses.
- Formulating an ambition
AnalitiQs reported all findings from the baseline assessment to the HR management team during a workshop. During this workshop we also presented data-driven HR applications within other organizations and explained the different levels they can be developed at. Ultimately, this led to the identification of some long-term goals.
In order to keep the ambition manageable, we split it up into a few phases. Each phase was linked to a level of AnalitiQs’ HR Analytics maturity model. Phase 1 consists of the ‘the low-hanging fruit’ (maximum impact/relatively easy to reach). We completed phase 1 in detail (activities, timelines and deliverables were all described). In consultation with the client, subsequent phases haven’t (yet) been developed in detail.
- Roadmap implementation
For the implementation of the roadmap, AnalitiQs provided a programme manager, a reporting specialist and a data scientist.
- The programme manager took responsibility for the overall management of the activities in phase 1 and made a substantive contribution as well. This included developing relationships with HR business partners and policymakers, agreeing about certain definitions with the reporting specialist and finding out to what extent new sources could be made available to the data warehouse.
- The reporting specialist built four different dashboards, compiled a list of recommendations to improve the designs of the data warehouse and operational systems and took care of a proper handover to the Finance department, ensuring continuity after the end of the project.
- The data scientist conducted an analysis regarding absenteeism reasons.
The following end products were created during this project:
- Baseline assessment, vision and roadmap report
- 4 interactive themed dashboards: Salary, Absence, Mobility and Recruitment
- List of Change Requests for operational HR system and data storage system
- HR analytics pilot focused on absenteeism
- Training of HR business partners and Learning & Development experts
These final products have assisted HR in their development towards a data-driven organization. We have provided them with new options including:
- Meeting the line managers’ requests to deliver more factual information regarding important HR themes and formulating action steps based on data-driven insights.
- Reducing absenteeism in a focused way, because the causes of absenteeism have become clear and risk groups have been identified.
- Identifying business challenges/opportunities that HR-analytics can assist with and going through the various steps of the HR-analytics process independently.
Starting up the next phase of the roadmap independently.