ATD Blog
Thu Mar 02 2017
Today’s business executives are increasingly applying pressure to their human resources departments to “use predictive analytics.” This pressure isn’t unique to human resources, as these same business leaders are similarly pressuring sales, customer service, IT, finance, and every other department head to use predictive or analytical tools.
Every department needs to uncover predictive analytics projects that affect their bottom line (increase sales, increase customer service, decrease mistakes, increase calls per day, and the like).
When human resources analysts begin a predictive analytics initiative, it appears to mirror what other lines of business do. However, instead of having a great outcome, it can be potentially devastating for HR.
Unless the unique challenge HR faces is understood, it can cause an HR department to falter, lose analytics project resources and funding, and leave them mystified, with no idea how they missed the goal of the predictive initiative so badly.
Like all other lines of business, Talent Analytics’ experience has been that when HR focuses on predictive analytics projects, they look around for interesting HR problems to solve; that is, problems inside of HR departments. They’d like to know if employee engagement predicts anything, if they can use predictive work with their diversity challenges, predict a flight risk score that is tied to the amount of training or promotions an employee has received, or see if employee onboarding relates to how long an individual lasts in a role. Though these projects have tentative ties to other lines of business, they are driven from an HR need or curiosity.
Our firm is often asked if we can “explore the data in the HR systems” to see if we can find anything useful. We recommend avoiding this approach. It is exactly the same as beginning to read Wikipedia from the beginning (like a book) hoping to find something useful.
When exploring HR data (or any data) without posing a question, what you’ll find are factoids that will be “interesting but not actionable.” People may comment, “really, I never knew that,” but nothing will result. You’ll pay an external consultant a lot of money to do this, or have a needed internal resource do this—only to gain little value without any strategic impact. Avoid using the Wikipedia approach—at least at first. Start with a question to solve. Don’t start with a data set.
Like all other lines of business, HR wants to show results of their HR-focused predictive projects. However, there is an important disconnect: HR shows results that are meaningful to HR only.
Perhaps there is a prediction that ties the number of training classes to attrition, or correlates performance review ratings with how long someone would last in their role. This is interesting information to HR but not to the business.
The HR department can learn from the marketing department, which came before them on the predictive analytics journey. Today’s marketing departments, which are using predictive analytics successfully, are arguably one of the strongest and most strategic departments of the entire company.
Today’s marketing leaders predict customers who will generate the most revenue (have high customer lifetime value). Marketing departments did not gain any traction with predictive analytics when they were predicting how many prospects would “click.” They needed to predict how many customers would buy.
Early predictive efforts in the marketing department used predictive analytics to determine how many webinars they would need to conduct to get a thousand new prospects in their prospect database. Or, how much they’d need to spend on marketing campaigns to get prospects to click on a coupon (Adding new prospect names to a prospect database is a marketing goal not a business goal. Clicking on a coupon is a marketing goal not a business goal.) Or, they could predict that customer engagement would go up if they gave a discount on a Friday (Again, this is a marketing goal not a business goal.) The business doesn’t care about any of these “middle measures,” unless they can be proved and tracked to the end business outcome.
Business wants to reliably predict how many people would buy (not click) using this coupon versus that one. When marketing predicted real business outcomes, resources, visibility, and funding quickly became available.
When marketing was able to show a predictive project that could identify what offer to make so that a customer bought and sales went up, business executives noticed. They highlighted what marketing was able to do, giving marketing more resources, funding, and visibility. Important careers were made in marketing for people who were part of strategic predictive analytics projects that delivered real revenue or real cost savings to the business's bottom line.
Marketing stopped being “aligned” with the business; marketing was the business. HR needs to do the same thing.
Many people get tangled up in definitions. Is it people analytics, workforce analytics, talent analytics, or something else? It doesn’t matter what you call it—the point is that predictive workforce projects need to address and predict business outcomes not HR outcomes.
As marketing learned over time, when HR begins predictive analytics projects, they need to approach the business units they support and ask them what kinds of challenges might be affected by the workforce.
When HR departments use predictive analytics to solve real, line of business challenges that are driven by the workforce, HR becomes an instant hero. These HR departments are given more resources, their projects are funded, they receive more staff for their analytics projects— and like marketing, they will turn into one of the company’s most strategic departments.
If you’re feeling pressure from your executives to start using predictive analytics strategically and have a high-volume role, such as sales or customer service, you’d like to optimize, get in touch.
Editor’s Note: This post is reprinted from the Talent Analytics Blog.
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