The attention to people analytics has increased enormously over the last few years. Many organisations have established people analytics teams, and several promising start-ups have developed software that can help HR with people analytics
“People are very interested in finding out if they can use objective measures to identify who is going to work well in their firm.”
The assumption is that if we have access to the right data, if we have the right analysis tools and clever people to interpret the data, we will be able to predict human behaviour – and that these predictions will be used in a sensible way in organisations. It is time to have a closer look at the psychology of people analytics. MBA programs in Bangalore
Implications for people analytics:
- Many people want to please their boss, and probably people analytics people are no different.
- PA has emerged alongside a cluster of related terms describing digital innovations for modelling and optimising organisational human capital.
- Trends in terminology reflect evolving priorities, methodological and technological innovations, communities of practice and rebranding.
- The PA literature is multi-disciplinary, extending beyond HR or management, with the data and computer sciences playing an increasing role.
- Gaps in training exist and ethical issues are rarely considered, despite risks to employees and organisations.
People analytics in online search trends
None of the terms Manpower Analytics, Personnel Analytics or Staff Analytics was found in Google trends since records began in 2004.
Objectives of PA
The most popular objectives and practices were performance assessment and development and employee lifetime values; onboarding, culture fit, and engagement, and workforce planning. the analysis yielded four additional categories – employee collaborations; diversity and inclusion; people risks, and inter-organisational relationships. The emergence of these categories illustrates the rapid development and diversification of the field.
“An HR practice enabled by information technology that uses descriptive, visual, and statistical analyses of data related to HR processes, human capital, organisational performance, and external economic benchmarks to establish business impact and enable data-driven decision making”.
Considerations in relation to PA practices, some of which are covert or reach beyond the boundaries of organisations themselves. Examples include the monitoring of personal social media or email activity, which have implications for privacy, the use of algorithmic decision making for recruitment or promotion, which has the potential to introduce bias and discrimination, and the digital abstraction of personality and ability profiles from real-world data without the need for psychometric testing, which raises issues for transparency and consent.
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