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Emerging Trend of Workforce Analytics

Regis Mulot, EVP Global HR, Staples, Inc.

Regis Mulot, EVP Global HR, Staples, Inc.

Workforce analytics is one of the hottest trends in Human Resources. In fact, many companies feel behind if they aren’t doing some sort of predictive analytics to improve their HR processes. With so many external pressures for organizations to evolve, HR functions are trying to implement these analytics without getting the proper structure in place first, and are seeing little to no true progress as a result. In order to ensure success it is beneficial to consider some of the necessary components to evolve a successful HR analytics team.

So what does success look like?

This is a common question many HR professionals must ask themselves. Most HR initiatives are tough to measure using metrics, and as a result it can be difficult to clearly define success. HR analytics is no different. In most cases, the best way to identify success is to provide the business with actionable data. There are many degrees of success. For example, you may provide value by simply helping the business identify the demographics of their workforce or by collecting multiple sources of data and discovering what is driving a turnover trend. In the end, if you are providing the business with insight that is impactful, you can consider your effort a success.

"The best way to identify success is to provide the business with actionable data"

The 3 main building blocks as keys to success:

1. Building credibility – This starts with getting clean data, this is a challenge for every company but must be established in order to build credibility. As you start to standardize and send findings out to the end user, you must educate your audience about what the metrics mean and why you are using them. This provides clarity and will prevent having to continually explain to the business what the data represents (i.e. using rolling 12 turnover instead of annualized turnover).

2. Building relationships – For a large company with multiple business units, it can be challenging to interact and communicate with hundreds of business leaders. As an alternative, filtering everything through Human Resources Business Partners (HRBPs) can be beneficial. This process is particularly effective when HRBPs take the time to explain how their business works and offer guidelines for the type of business problems that need to be solved. Building these relationships generates more conversations around how to best utilize a HR analytics team to provide value.

3. Get some traction and run with it – Similar to most big companies, Staples is not limited to just one line of business, there are several large and very different functions including retail stores, eCommerce, B2B sales and supply chain. With varying needs and speeds at which each function performs, it is impractical to think that all parts of the business move along at the same pace. Some areas will inevitably slow down any progress so you have to drive forward with the areas willing to move ahead. The HR analytics maturity curve spans several years with four main stages:

The speed at which particular functions advance along the curve at different companies can vary. Staples has some functions that only utilize the HR analytics team up until the “advanced reporting” stage. Other groups that have matured faster are driving strategic initiatives based on key insights the HR analytics team has provided. For these groups, workforce planning then becomes a two-way street. When there is a successful project with one business function it gets shared with other areas to educate them on the analytics capabilities they could utilize.

Using a system or an advanced analytics tool may help with building data credibility, doing predictive analytics, and getting results faster. You will notice that none of the first three keys to success involve utilizing advanced systems or predictive analytics because success should not be defined by whether or not you get to that point, as there is a lot of value to be delivered at all stages of the curve.