2018 HR Prediction Series Part II: A Move to Measuring the Employee Lifecycle

As we discussed in our last blog, we decided to make predictions about the future of HR analytics because it’s so vital to monitor trends and we want to be sure you have the latest information for you to make informed business decisions. Our second prediction is that organizations will start to focus on measuring the entire employee lifecycle – from pre-hire to exit.

The truth is that many organizations already do this in pieces. The opportunity exists to build a cohesive measurement strategy to assess the different phases of the lifecycle. This requires an integration of assessment/survey content and a strategy for how to use and harvest the intelligence from this data. We have been measuring the lifecycle for years at SMD. We recognized the value long ago and over time, have built a solid measurement framework with aligned content across the lifecycle. We have also built an integrated dashboard that helps organizations synthesize the data—and focus on actual business drivers—to harvest real intelligence. So, we think this trend is spot on.

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If you know SMD, then you know that we of course built our measurement framework around driving a real business outcome. With the employee lifecycle, we focus on voluntary turnover. There is a real ROI with voluntary turnover and each phase of the lifecycle can provide unique insights and value to the organization regarding voluntary turnover. For example, we know that a key driver of voluntary turnover in the first six months of employment is the misalignment of new hire expectations and the reality of the job. This alone can make the business case for entrance and onboarding surveys.

We are already seeing many of our competitors start down this same path. In fact, two big survey firms have announced lifecycle products in the past few weeks. We are glad they decided to finally join the party.

This prediction can be considered a trend (at SMD we are always skeptical of trends), but it is a positive one, if done correctly. Done poorly, it will just be more data with limited value. Be on the lookout for prediction #3, and to hear all of our predictions tune into our webinar this Thursday, January 25th at 2:00pm EST, click here to register.