Wacker Chemie AG wanted to evaluate existing engineering job profiles in regards to the future fit and provide best practices. One of the project challenges was to define future-proven profiles in a mid-term (up to 5 years) and long-term (ca. 10 years) scenario. Moreover, it was important for the client to gain transparency on competitors’ sourcing strategy and availability of skills in the global labor market.
„The big data analyses provided a valuable foundation for our strategic recruiting and development decisions.“
Dr. Silvia Teuber, Director HR Development, Wacker Chemie AG
Questions to be clarified:
Which skills will be relevant for the specific job profiles in the future?
Which impact do trends and technologies have on the current job profiles?
Which skills are key competitors and players seeking?
How do sourcing strategies differ within the chemical industry?
Where are geographical skill hot-spots located?
1. Data infrastructure setup
To perform a benchmarking we setup the data crawlers to access relevant career websites and major job portals. The crawlers captured all published job openings of the defined market players.
2. A.I. and machine learning
Machine learning algorithms of our A.I. engine run on the crawled data to extract and classify relevant information on skills, jobs, locations and other components.
3. Data evaluation
Selection of the relevant companies / industries and visualisation of the data. Algorithms support in detecting insights and future trends relevant to the Telecommunications / IT industry.
4. Insights & recommendations
Based on analysis we determined key areas of improvement to optimize the recruiting and development strategy and recommended necessary subsequent steps.
Key insights & value-adds for the client
Wacker Chemie received acumen about labor market situation, including:
- insights of competitors’ behavior
- implications on recruiting & development strategy
- transparency on the ‘hot’ skills availability and sourcing strategies
- best-practice future-oriented job profiles for optimized recruiting.
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