How Big Data enhances your performance management processes
There are maybe three reasons why Big Data has been slow to take off for performance management.
First, individual employees haven’t tended to produce enough data to be classified as ‘Big’.
Then there’s the fact the data trail for an employee’s day-in-day-out activity is often scattered across several systems (or is just not traceable).
Finally there’s the fact that most HR departments simply don’t have the either the analytical skills or time to dig into the data and draw meaningful conclusions.
However, as more and more data transactions are recorded, as HRMS technology becomes ever more sophisticated, and as HR teams focus on the possibilities of information, Big Data principles are being applied to individual and team performance. The times may be a-changin’…
Ongoing data gathering
The traditional cliché of performance management is the annual assessment or review. The principle of regular feedback has long been accepted but in order to make it a reality, data collection must be constant. When that collection was by way of the manager’s notebook, it’s inevitable that other priorities would be an obstacle.
However, with monitoring and collection of targets, goals, and all forms of employee communications and activity, that data is becoming more and more automatic, creating a wealth of material for performance feedback. It’s still common for that material to then be accessed and used by managers but looking ahead, AI-driven performance management is not far away.
As humans, we know we’re fallible and subject to… well, subjectivity. Which can be a problem when performance management rests on a principle of objective and fair feedback. Unfortunately, HR policies cannot entirely eradicate unconscious bias from the process, whether based on difference (for example, in terms of race, gender or sexual orientation), or unfair comparison to colleagues and peers. Machines do not discriminate… unless they’ve been programmed to, of course!
These days, the majority of interactions are electronic – email, messaging, online – and therefore recordable and recorded. With the right focus, such data can be mined to examine particular types of transaction, for instance those between colleagues and team members. Individual performance in the team context can be studied and feedback offered to maximize positive teamworking and collaboration.
As a final thought, it’s worth remembering that while the science of Big Data and AI might be used to enhance recordkeeping and feedback, there is still an art to people management. Software may act as an impartial observer and chronicler but a human being is still required for the ongoing manager-employee conversation that lies at the heart of performance management.
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