What is the challenge?

Recruiting or staffing has the task of providing the company with a workforce that meets its needs in terms of quality and cost. Often, an unbalanced composition of employees leads to more expenses, for example for the renewed search for suitable candidates or through intensified onboarding. Such imbalance arises, for example, from a lack of match between applicants and the company or from a lack of benchmarks for qualifications, performance and salary.

What data can help?

  • Personal data of employees and applicants
  • Market data as comparative values for salary and compensation payments
  • Key performance indicators
  • Data from surveys, for example on employee satisfaction
  • Data from social media channels (status or connections to people or institutions or user behavior on online channels)
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Use case category: recruiting

How can companies use their data?

Recruiting can be optimized by using data in various ways, such as better placement of job ads on online channels, more efficient initial contact with candidates, pre-screening of resumes, and matching between applicants and jobs. Social media platforms uncover new connections and increase the application pool through “Active Sourcing” (direct approach to potentials). At the same time, relevant criteria for specific jobs can be filtered out. This allows for a more targeted approach and better filling of the position. By analyzing employee and application data, it is also possible to achieve a balanced lineup of employees in terms of qualifications, gender, age and origin (non-discriminatory selection). The analysis of market data as well as evaluation data from internal surveys can be used for a fair distribution of salary and bonuses and extended performance measurement.

Where is this use of data already being applied?

The sporting goods manufacturer Adidas uses data analysis to promote gender parity within the company. The results are incorporated into recruiting and strategies for attracting new male or female employees.

Medical technology company Heidelberg Engineering uses Personio software to automate previously manual recruiting processes. The advantages lie primarily in the central database. This means that application documents can be easily accessed internally from various locations, which speeds up processing. The company has seen a time saving in recruiting of around 20 percent. 

The Swedish municipality of Linköping uses data to pre-select applications. The applications are scanned automatically. Data analysis is used to make automatic pre-selections and send invitations for personal interviews.

The online mail order company Amazon trains algorithms with data from previous hires of new employees. New applications are automatically pre-screened based on criteria identified as relevant.

How does this use of data contribute to value creation?

The use of data analytics in recruiting can make the value chain in human resources management more efficient and cost-saving. Above all, the fit between job and applicant and thus making the right personnel decision saves costs (e.g. for high fluctuation) and increases employee satisfaction in the long term.

Aim of data use

Sources: Adidas (2016), Personio GmbH (2020), Savola, H. & Troge, B. (2020), Reuters (2018)