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Author's profile photo Susan Galer

Workforce Analytics Turns Human Resources into Evidence-Based Business Partner

iPad - Headlins 3.jpgWhat’s the real reason why top-performers are leaving the company voluntarily? How much more revenue could sales teams generate if they had the precise combination of training and compensation they needed to do a better job? How can companies make sure the right people are in the right place short and long-term as business demands fluctuate?

According to Peter Howes, Vice President of Workforce Planning and Analytics at SAP, workforce analytics has the power to solve business problems like these and more. I recently talked with Howes about how human resources (HR) can and should use predictive analytics for the advantage of the business. Here are three major takeaways from our conversation.

Don’t take metrics at face value

There’s a lot of talk about workforce analytics but most companies today are only doing reporting through metrics and dashboards. Consider employee engagement surveys. They may capture tons of feedback on what people like and don’t like about the company. Yet without correlations between variables like tenure, salary, training, and opportunities for advancement, HR and the business at-large may still be in the dark. If they don’t know the complete picture of what’s happening and why, they can’t take corrective action.  This is why Howes said HR must move from monitoring to investigation.

“We don’t get insights from the monthly headcount, termination and training reports. Metrics don’t segment or correlate the data,” said Howe. “Siloed business systems are also holding predictive analytics back. Too much data is reported at too aggregated a level, and all the richness of internal variations is lost. HR needs to integrate the data and connect it to the business.”

It’s not that the technology for workforce analytics isn’t out there. It’s just not available at every company. “Most companies don’t have the adequate technology onsite or the capabilities and motivation to go down this path,” said Howes. “We’re already doing that in SuccessFactors Workforce Analytics, pushing out key data to customers so they don’t have to troll through it.”

Tell the business what it doesn’t already know

We hear a lot about the need for storytelling in marketing and communications. Similarly, Howes says predictive analytics requires HR to become storytellers too. The objective is to put information in the context of what the business cares about.

“I worry that people just publish unusable data. We aren’t making better decisions because people aren’t converting the data into insights relevant, useful and applicable to the business,” said Howes. “The real exciting work focuses on capturing insights about the organization which are important but currently unknown.”

Technology alone isn’t enough – data scientists needed

Although there’s a tremendous upside to using advanced statistical analysis for workforce planning, Howes said most companies lack the analytics acumen to deliver what the business needs. Recent research bears this out. The McKinsey Global Institute predicts that by 2018 the United States alone could face a shortage of between 140,000 to 190,000 people with deep analytical skills, as well as a shortage of 1.5 million managers and analysts who know how to use the analysis of big data to make effective decisions.

“There’s an immaturity in HR as to what workforce analytics means,” said Howe. “The fundamentals for workforce analytics involve the use of statistical analysis that reveals correlations between variables like performance ratings, salary increases and organizational tenure.”

To be clear, there are no easy answers to questions like why top-performers leave or how sales teams can be more effective. But workforce analytics holds the promise of unlocking data for insights to head off problems, turning HR into a partner the business can count on for company-wide success.

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  How Companies are Using Workforce Analytics

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      Author's profile photo Christopher Solomon
      Christopher Solomon

      “Most companies don’t have the adequate technology onsite or the capabilities and motivation to go down this path,”

      That is what I see in about 95% of my clients. And for the ones that are large enough to do this, they tend to have so many disparate systems and not enough skilled resources to put in the time/effort/money to actually get all the interfaces/integration working together to "feed" any one system to make better decisions based off of true analytics. Therefore, they tend to run a hodge-podge of reports, try to make the own correlations "in their head" and put forth their best "guess". The promise of it sounds so great, but very few make that leap.

      Author's profile photo Former Member
      Former Member


      My experiences are mostly similar to yours but partially different. First I agree that most companies don't have adequate technologies for true Workforce Analytics. Obviously I believe SuccessFactors is changing this. The education required around technology is not to confuse BI/Data Warehouse technology with Content. Technology alone is not enough as most companies can't build the content, nor is it cost effective for them to build content.

      I strongly agree with you that 95+% of companies don't have the internal capabilities to build a strong Workforce Analytics capability. The critical skill missing is the ability to interpret the results from Workforce Analytics. Mostly we just Report workforce data at an aggregated level, which is not insightful. We don't interrogate workforce data to find key insights that we didn't previously know. We don't do this as most HR Analysts don't know what to look for and don't understand what the implications might be.

      While many companies have multiple systems as you say, I have worked with 100+ companies who have brought the data from multiple systems together. Companies are reducing the number of systems but most will never get to one system. That is why we at SuccessFactors, and my former company Infohrm before that, put a lot of effort and R&D into integrating data from multiple systems.

      AT the end of the day lack of capability in interpret thedata is a greater constraint than technology, even though the right technology and "content" is a fundamental prerequisite.