People Analytics and Your Seasonal Workforce

summer jobThe following guest post is courtesy of our board member, David Creelman.

With Spring upon us and Summer right around the corner, many businesses are actively hiring seasonal workers to ensure they have coverage for their busy seasons.

For example, just last month, Home Depot, the nation’s largest home improvement chain, announced that it was hiring more than 80,000 workers nationwide to ensure that its nearly 2,000 stores are staffed and ready to welcome spring 2016, its busiest season.

The home improvement industry isn’t alone, of course: golf courses, recreational facilities, summer camps and programs, seasonal restaurants and retailers, along with many others are all in hiring mode right now to match this seasonal business cycle.

Beyond just getting bodies onboard, leveraging this seasonal workforce can be a big competitive advantage. Whenever we are dealing with a potentially big strategic advantage; particularly one involving large numbers of workers; we want to call on the power of people analytics.

So how can people analytics help? The truth is, they can help in so many ways that I could never name them all in a short blog post, but I can say that there are a few questions that every seasonal employer should be asking themselves right now:

• Are we scheduling in a way that minimizes labor costs?
• Are we scheduling in a way that minimizes turnover?
• Are we running an analysis to discover the right trade off between the two?
• Would increasing training for seasonal workers pay off?
• What are the most costly mistakes seasonal workers make, that regular workers don’t make?
• What is the most effective way to screen seasonal workers?

You can approach these questions with sophisticated statistical methods, but you don’t need to. If you don’t have the data, tools, or skills for advanced analytics, you’ll find you can go surprisingly far with the back of an envelope or Excel. Yes, you want to do as good a job as you can; especially when it’s a strategic issue, but my mantra is that some numbers are almost always better than no numbers. Don’t let lack of heavy duty analytics horsepower be an excuse for not thinking about these issues.

My challenge for businesses is this: is it a normal part of your culture to bring analytics savvy to challenges like optimizing the effectiveness of your seasonal workforce? We are all enamored with Big Data and the latest analytics tools; but in my experience the lack of an analytics culture is usually the bigger problem. My advice? Especially if you are starting from scratch, focus less on what the analytics tools are, and more on creating an analytics-focused culture that puts value on numbers-based analysis.

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