Human Resources delivers predictive analytics for the best strategic business outcomes
People are every organization’s biggest asset and expense. The workforce can represent up to 75 percent of the total cost of doing business, a percentage that’s often higher for companies in retail or other service industries.
However, according to Peter Howes, Vice President of Workforce Planning and Analytics at SAP, most organizations don’t apply the same analytical rigor to decisions about their workforce as they do to other business areas like strategy, finance, research and development, marketing or sales.
In this Q&A, Howes discusses what Human Resource (HR) practitioners need to know about workforce analytics in order to use them effectively for strategic business outcomes.
Q: Where do workforce analytics fit into corporate priorities?
A: Analytics are core to HR in helping to manage the business because companies need to know if they’re getting the best return from their workforce, and making the best people-related decisions to get the best return.
Q: What are HR’s top three challenges in using workforce analytics?
A: Most human resources departments don’t have the right technology. They’re still trying to do workforce reporting off manual tools like spreadsheets, and trying to pull and integrate data from disconnected systems. The second challenge is that HR doesn’t have the right skills to interpret the data. The third challenge is that many HR practitioners and vendors talk about workforce analytics and predictive analytics, but what they are doing is really just reporting. Reporting aggregates numbers like headcount, number of separations and total compensation. Workforce analytics applies statistical techniques such as correlations, test of significance, factor analysis or multivariate analysis. Predictive analytics allows HR to model the impact of current and future HR practices on business results.
Q: What’s possible with workforce analytics right now?
A: What’s possible is far beyond what most companies are actually doing, which is reporting through siloed metrics and historical dashboards. With the right technology and data analysis and interpretation skills, organizations can integrate their business data – revenues, expenses, production units – together with the people data to find out the key ways people impact on business performance. The cutting edge is developing more predetermined data mining that analyzes workforce information to find the variations. Segmentation yields actionable business insights.
For example, most companies report on voluntary employee turnover. You can now easily break the data down by performance rating, tenure, employee engagement score or job grade. We’re already doing that in SuccessFactors Workforce Analytics, pushing out key data to customers so they can connect the dots quickly. We need to build the capabilities of the HR community, as well as the business at-large, to think about what’s possible.
Q: Can you provide examples of how companies use workforce analytics to get significant business results?
A: The objective is to gain insights everyone can use to make decisions that have better business outcomes. For example, most companies agree that high-performers are much more valuable to the organization, with a much greater positive impact on business performance than the average worker. Yet it’s amazing how many companies don’t know the voluntary termination rate of their high-performers, and how the turnover rate of high performers varies by position tenure.
One large company discovered that high-performers with correspondingly high emotional engagement, meaning they liked the company, and their job, team and manager, were leaving at more than double the average rate of turnover. Armed with that data, the company conducted post-exit surveys and focus groups with current high-performers, revealing that the high emotional engagement of these employees did not make up for the lack of career opportunities. By developing better career paths for high-performers, the company significantly reduced those turnover rates.
Some companies are using analytics to improve sales team performance. Data correlations can reveal how revenue per sales representative varies by voluntary termination rates, performance rating, received training and tenure. These kinds of workforce analytics are helping managers make better decisions. They can increase sales force productivity by addressing performance issues and ultimately retaining stronger people.
Q: What’s the most important thing HR practitioners should do today?
A: HR needs to understand and link the people factors to the performance of the business. The only way they can do this is by building a center of excellence around workforce analytics. This should consist of a team exclusively focused on analyzing data to find insights currently unknown to the organization. Of course, they need the technology and capabilities – data scientists – to interpret the data and convert it into a compelling and actionable business story.
Q: What can customers expect from SAP in the areas of workforce analytics and predictive analytics this year?
A: We have a very large team of workforce analytics experts dedicated to developing our software capabilities and assisting organizations in using them to greatest business advantage. I’m particularly excited about our focus this year on operational workforce planning, which addresses a company’s ability to manage accelerated and unexpected change. Companies can model in detail the optimal workforce they’ll need short- and long-term.
Equally important, customers are learning how other organizations are using workforce analytics through our Value Improvement Program that includes on-site summits and webinars, as well as the ongoing exchange of information through forums on our collaborative platform, SAP Jam.
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Top image: Shutterstock; all other images via SAP