The criticisms of psychometric testing fall back on a fear of HR becoming too dependent on what is, in the end, just numbers and analytics. As big data moves further into the HR space, similar fears may begin to appear.
“Businesses are generating so much data today and they are not really tapping into it to understand the workplace as well as they could,” he told HC.
O’Hanlon cited the huge roll-out of big data initiatives in the marketing world as an indicator of the success it may have if used internally to examine employee engagement, company culture, and other aspects of the workplace.
He mentioned OneTest’s own move to using big data and psychology together to gauge how employees like to communicate. By collecting data on the methods of communication used, and then analysing how employees who use them are reacting and how efficient the use is from a psychological standpoint, employers are able to gain greater insights into what works and what doesn’t.
The data required for what O’Hanlon has proposed is already being generated – and in many cases being collected – by organisations, but HR professionals are simply not making use of it yet.
“There’s a lot of information that is already out there but the challenge is how do you effectively tap into that and make sense of it?” O’Hanlon said. “That is really what big data is about … tapping into really high volume high variety type data to generate insight.”
The backlash that psychometric data has experienced recently is something O’Hanlon understands, but feels can be overcome. He acknowledged that whenever an aspect of the workplace is measured, a ‘false dichotomy’ manifests that pits human understanding against information and data, when really the goal should be to link the two.
“Depending on how you use it, you really should be harnessing big data to support your decision making rather than outsourcing your decision making to a black box … we’re not trying to replace the role of an HR professional, it is really making the decision-making more effective by providing them with more knowledge.”
O’Hanlon added that if big data is treated as a purely technical numerical approach, it is likely to fail – whereas analytics work well when focused on business problems and working with people.
“One of the big pitfalls is people treat it as technical only, and if you try that you are going to fail,” he said.