Steve Goldberg's Analyst Perspectives

Predictive HCM: The Benefits Are Real, as Are the Cautions

Posted by Steve Goldberg on Jan 2, 2018 12:43:17 AM

Two of the most impactful contributions of any HR department are driving employee engagement and employee productivity, outcomes that are highly correlated of course. These contributions are meaningful because, for an organization of any appreciable size, even fairly small upticks in employee productivity translate into significant financial benefit. The math is simple: Increase revenue per employee (for example, via technologies that enhance productivity) from $150,000 to $157,500 (just 5 percent) in a workforce of 5,000 employees and you capture $37.5 million in incremental revenue. The magnitude of this business impact is several times larger than shaving even 50 percent off the HR operating budget in an equivalent-sized organization.

But that’s a hypothetical. In the real world of your organization, where is that employee productivity improvement coming from? Maybe you’re thinking the answer involves having better-quality data that can drive better workforce-related actions and decisions. As a reference point, our Human Capital Analytics benchmark research found that almost half (46%) of organizations spend more time preparing data and reviewing for quality and consistency than they actually spend analyzing the data. Clearly, timely, accurate and consistent data is a factor in improving productivity, but the business value of accurately knowing employee engagement or productivity levels for the preceding quarter pales in comparison to the value of knowing what will likely happen in the next quarter. And it is even more valuable to know why employee engagement levels will probably change in the next quarter. This is where analytics come in to help HR organizations craft and lead more effective HCM actions and programs. Our Next Generation Human Resources Management Systems benchmark vr_HRMS_08_new_technology_deployments_planned-2.pngresearch found that business analytics is the top technology planned for deployment in 51 percent of organizations followed by big data (42%) which is intended to provide a centralized and managed environment for analytics.

For HR leaders, being able to predict what changes will likely occur in the workforce and why would be significant progress toward supporting better top-line business performance. But things really start to get exciting when, with new tools and predictive frameworks, HR teams can also help organizations avoid adverse circumstances like a downturn in engagement or an increase in employee turnover or HR-related compliance problems.

This is the essence of predictive HCM, an emerging approach that enables HR to know what will likely happen in the workforce and why, and managers to avoid disruptive, resource-draining HCM problems.

As HCM systems keep evolving and HR functions become more comfortable operating in the data science arena, opportunities to use predictive HCM across the employee life cycle will abound. As a result, the overall employee experience will improve. Early capabilities include predicting flight risk, job fit/job match and performance; down the road we will see innovations in predicting gender-biased decision-making, various types of compliance and safety risks, and even when “passive” (talented but not looking) job candidates will be more receptive to other opportunities.

What else is coming down the pike? When will HCM systems deliver the ability to predict the best learning approaches for each employee or who has clear leadership potential – or conversely, who might exhibit poor judgment or low personal integrity, or which highly valued candidates will opt out of the recruitment process and when?

As with all powerful technologies, however, predictive HCM carries potential risks of misuse. With all predictive tools, organizations should avoid acting before establishing algorithmic validity and the non-bias of those constructing or interpreting the frameworks. Our Next Generation Predictive Analytics benchmark research found that 42 percent of HR organizations are planning to use predictive analytics and almost as many are evaluating them for use in their organization. For those that have adopted predictive analytics for HCM, over a third (34%) have found increased workforce productivity as a top benefit. Are you prepared to use them and gain value from them?

The trajectory of predictive HCM, what might lie ahead, and how to evaluate the readiness of your organization and the technology required will be covered in my live 30-minute webinar on Jan. 16th at 2pm ET/11am PT. You can register now.


Steve Goldberg

VP & Research Director

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Topics: Predictive Analytics, HCM, Human Capital Management, Analytics

Steve Goldberg

Written by Steve Goldberg

Steve is responsible for the Human Capital Management (HCM) research and advisory services practice. He guides HR and business leaders in leveraging their workforce for competitive advantage. He guides HCM technology vendors on the market of buyers and where their applications and technology can have maximum impact. Steve's uniquely diverse HCM experience spans over 30 years, including HR process and HCM systems practitioner leadership roles, heading up product strategy for one of the most respected HCM application vendors, and operating his own global advisory practice. His expertise areas of coverage include HRMS, Talent Management and Workforce Management, with specialized focus on recruiting, learning, performance, compensation and payroll. Prior to joining Ventana Research, Steve worked as a corporate VP in HR at UBS/Swiss Bank Corporation and Huizenga Holdings, product strategy leader at PeopleSoft and Unicru, and was also VP and Research Director at Bersin & Associates. Over 35,000 HR professionals and business executives have been informed by one of Steve's presentations on HCM, or have read his published work. Steve holds an MBA in Human Resource Management from University of Buffalo School of Management and a BBA in Industrial Psychology from The City University of New York.