The first challenge of workforce management has always been to find and retain top talent. With the advent of technology and the ability to gather worker data, many of us expected this challenge would become easier to overcome. Not so. We are now flooded with information. More tools, assessments and processes to capture information on employee productivity, engagement and potential have given us just that – more. The only way to make sense of it is to add data management and comparative analysis to our long list of responsibilities.
It’s time we turn this around and start to master information overload. But how?
How do we synthesize and compare assessments that use different rating models, processes and time frames? How can we align the subjective metrics of one team to that of another? How can we isolate the specific elements of workers history that impact their overall performance?
Here’s one answer: Let’s streamline our worker information into the most relevant data points.
What if we found a way to assess workers’ performance by looking at a consistent and digestible set of data? That would mean managers could quickly and accurately match a worker to a new project or assignment and provide clear feedback to workers on how they can join the ranks of top performing staff.
My colleagues and I used this idea to create an algorithm that rates workers on a five-point scale and will unveil it later this month.
I love this “rating system” approach because it allows us to harness technology to analyze data that already exists. We do not need to create additional work for managers. Virtually everyone collects data that is needed to develop workforce performance ratings — things like engagement, reliability, compliance and timeliness.
Of course, there needs to be room for additional information outside a strict format, but a sophisticated platform can incorporate exceptions into ratings.
This approach also upends accepted wisdom. The industry has long believed that the more time we spend on the front-end finding the right person for the right job, the less time – and expense – we spend on turnover, remedial training, loss of production and general frustration.
But, we don’t need to spend more time to find the right talent; we need to leverage new technologies to optimize the time that we do spend to find the right talent.
What do you think? How can we be smarter with our time to match the right worker to the right assignment?