Human resources management is experiencing an evolution in which it has gone from offering historically focused solutions to helping businesses get business results through people. This is in contrast to the past when it was inexact, backward-looking and unpredictable. An example of this being in recruitment where the traditional method was hiring through interviews but it has since been realised that the interview method is not the best way for getting talent.
HR has since embraced technology and analytics by linking HR initiatives to business objectives in order to analyse, understand and predict business outcomes. This has brought about the use of a spectrum of tools including predictive analytics, people analytics, machine learning and automated systems such as performance management, psychometric testing, and job evaluation systems. These tools combined with the existing frameworks for understanding work, people and organisational cultures have led to the advancement of HR from art to a science.
The main objective of science is to describe, explain, predict and control the behavior and processes of situations. Human resources has adopted this and now uses data to make better people decisions. It uses data and analytics to inform all its people decisions, from choosing benefits options, promotions, and hiring. HR has thus become forward-looking using predictive science. With most of the important areas of HR involving predicting future behavior as a result of present actions and interventions, people analytics plays a big role. This is because HR can have a much greater business impact if it is future-focused.
This scientific approach focuses on HR actions and resources so that they produce the maximum direct, measurable impact on business results. This is in line with most business strategies. This has shifted the focus from tactical HR problems to solving broad strategic business problems.
Under the scientific model important people, management decisions are made based on evidence. Decisions on the most effective approaches for hiring, performance management, development, and incentives are based on the latest available data. Scientific HR places emphasis on experimentation to test more effective approaches utilising machine learning and AI to identify areas that may be missed by humans.
The old approach in the short term emphasizes using data for continuous improvement. And in the longer term, it becomes obsolete because of the continuous and dramatic changes in business and technology.
Fadzai Danha is a consultant at Industrial Psychology Consultants (Pvt) Ltd a management and human resources consulting firm.
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