Why we love data driven performance management? (And you should too!)

Why we love data driven performance management? (And you should too!)

We have consistently written about how annual performance reviews (done traditional way) rarely provide any value in today’s dynamic work environment.

A typical performance management process consists of self-assessment by employee followed by response from direct manager & then a face 2 face discussion. The process is designed to bring to fore important achievements & potential improvement areas for the employee.

This whole exercise does not account for lack of objectivity from both the parties – employee as well as the manager. That is, even though this process is known to be vulnerable from common psychological biases it is still popular in numerous organizations.

What is data driven performance management?

Data driven performance management is a process that relies heavily on factual data to make informed judgements & decisions about managing employee performance.

Its underlying intent is to bring to the fore, employee strengths & weaknesses in the most objective way. Bypassing all the biased opinions that employee’s manager, peers or direct reports may have. It rests on the fact that an individual can be good or bad at certain aspects of his job & the performance should be managed taking that into consideration. Not based on a blanket judgement.

Challenges in managing performance driven by data:

Today, data analytics plays huge role in many decision making processes in an organisation. However, such analytics haven’t been consistently used to monitor individual performance, with a few exceptions of course.

The primary reason being the amount of work being done by employees may not generate sufficient data to analyze. Secondly it is difficult to obtain such data as employees typically collaborate with multiple entities/departments within the organization. And lastly everyone is simply too busy firefighting to actually invest a significant amount of time in data analysis.

 

By using data driven analytics for performance management, large volumes of data can be translated into meaningful information about how employees have performed over a period.

 

There could be multiple data points that could be pivotal to an organisation’s employee performance management strategy. But almost in all the cases, these data points will differ across organisations, departments, roles etc.

That doesn’t mean this data shouldn’t be gathered at all. It simply conveys that organisations will need to invest some resources till they formulate & streamline a data driven employee performance management strategy.

Once there, recent advances in machine learning & predictive analytics will start bringing in exponential return on that investment.
Below, we have gathered a few data points that could be instrumental in helping you build your employee performance strategy. Some of these data points could be generic whereas other could be specific to a role or a function.

Data points for performance management

Feedback from multiple sources & over a period of time

Rather than doing annual or even semi annual reviews, make them more frequent. Gather these feedback items from multiple sources, not just managers. This will allow you to get rid of (to an extent) the recency & confirmation biases.

Additionally train people to provide feedback along with as much context as possible. That lets you see the big picture down the line, when the feedback is being analysed.

Measurable goals that are tracked more frequently

Annual goal setting is known to be a wastage of resources, due to its ‘set & forget’ nature. The set & forget philosophy of goal setting is proven to be ineffective. If you are seriously looking to gather factual data around employee’s corporate goals, use OKRs or SMART methodology.

Not just set the goals measurable & time bound, ensure they are updated more frequently. These frequent updates along with final grades will provide you with a holistic view of the employee’s efforts.

Adherence to timelines

We would recommend giving employees freedom to perform the tasks they own. That doesn’t mean tasks should not be time bound, it just means ‘stay away from micro-management‘. And whenever there is an instance that deserves praise or improvement, document it for future reference.

Quality of deliverables

While measuring quality for some functions could be very straight forward, for others it could be a peculiar challenge. e.g. Sales teams are known to be measured by the dollars they earn. But do we know the most common metrics used by other functions for example technical writers?

Before measuring the quality, its important to document the metrics & agree on them with respective employees. Make sure there is no room left for interpretation.

Innovation

Innovation is one of those aspects, that are immensely challenging when it comes to their measurement. Having said that, the academics have definitely advanced the research so as to allow us objective measurement of innovation.

For example, one of the recent measurements for innovation is RoPDE (Return on Product/Service Development Expense). Interestingly, RoPDE is derived from standard accounting data.

As mentioned earlier, there could be number of data points related to efficiency, effectiveness, relationships at work, work-life balance and so on. It all is going to revolve around your company values.