HR’s tryst with data

People analytics is HR’s chance to be strategic
The Human Resources (HR) function’s tryst with data is very old. Ever since the organised way of doing business started, managers have been concerned with this clichéd question ¬`how to find the right person for the right job at the right time and cost?’ And the answer to this is still evading them.
So what is HR or people analytics or workforce science? HR or people management has traditionally been seen as an `art’, relying on use of gut or intuition while making people or HR-related decisions in organisations.However, recent developments have highlighted the benefits of using data while making people decisions, thereby giving them a semblance of data-based objectivity. This scientific approach to HRM in organisations has given birth to a new field called HR analytics, which lies at the intersection of data algorithms and intuition in making people decisions across the employee lifecycle. It is generally defined as systematic collection, analysis and interpretation of data to improve talent management decisions. It is equally important to know what is not HR analytics. Generally, it doesn’t include simple headcount or employee engagement score or attrition data. It is much more than these.
For a long period, HR has been striving to get a seat `on the table’ along with finance, operations and marketing functions to become a strategic function in any organisation.In its quest to become `strategic’, at the basis level, it has been demonstrating its value-add to business by showcasing metrics focusing on `efficiency metrics’ like lowering HR cost per employee or reducing cost of per hire, etc. Some other organisations have gone a step ahead and showcased ‘effectiveness metrics’ like employee engagement or satisfaction increase or employee retention increase to highlight HR’s value-add to business. However, Clevel executives have been sceptical of these metrics and these have been generally labelled as metrics for justifying the existence of HR without any tangible link to either topline or bottom-line performance. So this gap of showing how HR metrics link to business metrics has always remained. HR needs to move up the ‘measurement or metrics value chain’ from efficiency – effectiveness metrics to ‘business impact’ metrics to demonstrate the link between HR and business metrics. These impact level metrics require the use of advanced statistical modelling techniques and complex algorithms to perform two key types of analysis – predictive and prescriptive analytics.
Predictive analytics will inform C-level ‘what will happen’ – for example – who will quit next and prescriptive analytics will inform C–level ‘what can be done to prevent that attrition’.
So this kind of HR analytics purely based on data catches the attention of C–level executives and hence, provides an opportunity for HR to become truly strategic.

Source: Economic Times
Date: 19th August 2014


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