How is performance management evolving?

We talk to Nathan Reynolds, Director of sales, ANZ, at Ceridian, about how HR can leverage people analytics to make data-driven decisions.

How is performance management evolving with the help of HCM technology?

In today’s world of work, an optimal employee experience is grounded in frequent and meaningful communication. This underlying truth impacts performance management discussions too.

Annual reviews asking managers to condense a year’s worth of accomplishments into a few answers discourages meaningful conversations. For one, bias and the rater effect collude to reveal more about the reviewer than the person being reviewed - that a lenient manager will give better reviews, regardless of the performance of their people, and a strict manager will give worse reviews, independent of how their direct reports actually perform. In addition annual reviews tend to bell curve while actual performance does not follow this pattern.

As a result, many organisations – including our own – opt for a more frequent and developmentally focused approach to performance development, leveraging the functionality of cloud based HCM technology to help facilitate.

What HCM technology allows for is the ability for employees to participate in their development every day, using the same system they access their pay, view their schedules and perform other common processes.

Moreover, through HCM technology organisations can equip their people leaders with tools that prescribe how to provide feedback based on the unique strengths of their team members. This personalised coaching elevates the ability to tailor conversations, ensuring the message is understood and acted upon.

With employees regularly talking to their leaders on a range of performance topics, they continue to feel appreciated and gain a better understanding of the opportunities unique to them.

How can HR leverage people analytics to make data-driven decisions and enhance the employee experience?

More HCM technology companies are adding predictive analytic solutions to their software mix allowing for insight into the likelihood of an employee leaving, their performance potential and their overall level of engagement – information that can help business leaders make better decisions.

Having said this, predictive analytics is very much based on real figures – using a combination of data mining, modelling, machine learning and artificial intelligence to analyse current information and make predictions about the future. Each model requires an objective – be it flight risk, or promotion potential – and the HCM data of an organisation’s choosing (such as compensation levels) to complete their algorithm and predictive probable outcome.

What does this all mean for organisations looking to improve their employee experience? With insights based on real data, business leaders become better equipped to take on a proactive employee engagement approach. Knowing which employees are likely to leave and potential (correlated) reasons for this likelihood, people leaders can start making changes to an employee’s scenario (compensation, training, etc) and influence a more positive outcome for that employee and the organisation as a whole.