4 Approaches Everyone In HR Analytics Should Be Using
We are being asked regularly what kind of analysis we perform in our predictive HR Analytics projects. For that reason, we made a short overview of the 4 most common approaches or methodologies that we use over and over again.
Our 4 approaches have differences in emphasis of course, and we use different techniques in the background, but we generally repeat two key features: 1) all projects combine data from multiple sources (people and business/organization) and 2) we start with a pressing people/business/organization issue that need to be solved (or better understood).
Approach 1: Clustering
With this approach, we are investigating hidden group patterns with the help of clustering techniques.
- Which common people characteristics can predict better sales performance?
- Which cluster of recruitment sources can predict better people retention?
Approach 2: Driver analysis
With this approach, we try to understand hidden relationships. Most of the time, we use the word ‘impact’ to explain relationships between events or people/business characteristics.
- What is the impact of poor engagement on client satisfaction?
- What is the impact of sales training on business revenue development?
Approach 3: Risk analysis
With this approach, we try to understand probabilities or the likelihood of occurring events.
- Which high performers are at risk to leave in the next 24 months?
- Will the reduction of training investments increase the risk of employee turnover?
Approach 4: Forecasting
With this approach, we try to understand future trend lines, based on historical patterns.
- What will be the employee turnover in the coming 3, 6 or 12 months?
- What will be the typical first six months time-to-productivity trend line of a call center newcomer without call center experience?
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Interested in using these 4 HR Analytics approaches as a key component in your people or business strategy? Get in touch with CEO and co-founder Luk Smeyers for more information (mailto:firstname.lastname@example.org or via Google+). Or follow iNostix on Twitter and/or Facebook for exciting international articles on HR analytics. And don’t forget to register for this blog!