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The Beginners Guide to Predictive Workforce Analytics


Under increasing pressure and facing unique challenges, Human Resources departments are turning to analytics to improve their business practices. Learn what HR needs to be focused on, and what pitfalls they need to avoid.



Predictive Workforce Analytics

Human Resources Feels Pressure to Begin Using Predictive Analytics

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 line of business (LOB) leader, to do something predictive or analytical.

Every line of business (LOB) is clear on their focus. They need to uncover predictive analytics projects that somehow affect their bottom line. (Increase sales, increase customer service, decrease mistakes, increase calls per day and the like).

Human Resources Departments have a Different, and Somewhat Unique, Challenge not Faced By Most Other Lines of Business

When Human Resources analysts begin a predictive analytics initiative, what we see mirrors what every other line of business does. Somehow for HR, instead of having a great outcome it can be potentially devastating.

Unless the unique challenge HR faces is understood, it can trip up an HR organization for a long time, cause them to lose analytics project resources and funding, and continue to perplex HR as they have no idea how they missed the goal of the predictive initiative so badly.

Human Resources' Traditional Approach to Predictive Projects

Talent Analytics' experience has been that (like all other lines of business) when Human Resources focuses on predictive analytics projects, they look around for interesting HR problems to solve; that is, problems inside of the Human Resources departments. They'd like to know if employee engagement predicts anything, or if they can use predictive work somehow with their diversity challenges, or predict a flight risk score that is tied to how much training or promotions someone has, or see if the kind of onboarding someone has relates to how long they last in a role. Though these projects have tentative ties to other lines of business, these projects are driven from an HR need or curiosity.

HR (and everyone else) Needs to Avoid the "Wikipedia Approach" to Predictive Analytics

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 as 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 a question, what you'll find are factoids that will be "interesting but not actionable". They will make people say "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 precious 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 dataset.

Human Resources Predictive Project Results are Often Met with Little Enthusiasm

Like all other Lines of Business, HR is excited to show results of their HR focused predictive projects.

The important disconnect. HR shows results that are meaningful to HR only.

Perhaps there is a prediction that ties # 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.

Here's what's going on.

Business Outcomes Matter to the Business. HR Outcomes Don't.

Human Resources departments can learn from the Marketing Department who came before them on the predictive analytics journey. Today's Marketing Departments, that 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 predict how many webinars they'll need to conduct to get 1,000 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.

Marketing Cracked the Code

Business wants to reliably predict how many people would buy (not click) using this coupon vs. 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 took notice. They took such close notice that they highlighted what Marketing was able to do, they gave Marketing more resources and funding and visibility. Important careers were made out of marketing folks who were / are part of strategic predictive analytics projects that delivered real revenue and / or real cost savings to the business's bottom line.

Marketing stopped being "aligned" with the business, Marketing was the business.

Human Resources needs to do the same thing.

Best Approach for Successful and Noteworthy Predictive Workforce Projects

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.

Like Marketing learned over time, when Human Resources begins predictive analytics projects, they need to approach the business units they support and ask them what kinds of challenges they are having that might be affected by the workforce.

There are 2 critical categories for strategic predictive workforce projects:
  • Measurably reducing employee turnover / attrition in a certain department or role
  • Measurably increasing specific employee performance (real performance not performance review scores) in one role or department or another (i.e. more sales, less mistakes, higher customer service scores, less accidents).

I say "measurably" because to be credible, the predictive workforce initiative needs to measure and show business results both before and after the predictive model.


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