Social media is potent as it generateshundreds of resumes on a daily basis,though it cannot consistently evaluateand process the same
Assessing ‘big data’ can be used to predict performance of a potential recruit
Cloud and social media technologies have the capabilities of catalysing a variety of functions in an HR ecosystem, making them more efficient and effective. It is the next evolution to talent acquisition and management. Time and again, technology was deployed without keeping in mind the basic ethos of the building blocks of the HR functions.
But while solutions on the cloud are cheaper and hence abundant, one must understand that they haven’t gone through the rigour required. For example, moving assessments to the cloud does not mean that competency models and competency-based interviews are no longer important. Social media is potent as it generates hundreds of resumes on a daily basis, though it cannot consistently evaluate and process the same and there is no one to analyse the quantum of data being generated.
This ‘Big Data’ when analysed right can lead to fundamental findings, empirical endorsements of long-lasting beliefs. For example, analyzing the ‘Big Data’ of applicant demographics, evaluations, selections and performance being generated by our near automated recruitment processes can be used to predict performance of individuals at the time of recruitment itself.
Similarly, the problem of plenty -- hundreds of resumes pouring in can be effectively streamlined with reliable and automated evaluation and a streamlined process. Progressive companies benchmark talent performance and build performance prediction models for recruitment.They also utilize statistical tools to do the analysis and process data to build performance prediction models based on our assessments.
In a recent study, involving the use of data on various parameters like demographics, assessment, and performance, we were able to effectively predict the performance of relationship managers in the banking sector.
With the help of multi-parameter optimization and regressions we were able to normalize performance across regions, to create regional and role-based models.The post rollout performance is expected to be higher by around 50 per cent. Such sophisticated analysis is only possible through intelligent use of talent optimisation tools, such as particle swarm optimisers.
Another example of a sophisticated use of technology involves automated spoken English assessment tools. Through such tools, extensive process engineering with inputs from various statistics delivered from selected and rejected candidates is plausible. A tight rope balance between false accepts and false rejects can actually become effective and efficient.
Numerous studies have led us to strongly believe that the effectiveness of automation can be achieved with a scientific approach to understanding and analysing data and drawing the right inferences.
Himanshu Aggarwal is Chief Executive Officer, Aspiring Minds