People Analytics: From Baby Steps to Cost Savings from Big Data Analytics

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Heads-up HR leaders, the big data revolution is making a difference in almost every other facet of your enterprise, and it's time for you to join the fun. Although cost savings from big data analytics could simplify and drive decision processes in HR, it has yet to impact most HR departments in significant ways.

However, the future promises significant changes to how HR does business with people analytics:

HR Readiness

The steps HR needs to get ready for cost savings from big data analytics are clear:

  1. Useful, trustworthy big data sources, properly tagged with metadata that allows HR to search effectively.
  2. Integration of predictive analytics with HR software (e.g., R, SAS, Google Prediction, Amazon QuickSight).
  3. HR analytics training.
  4. Experience working with decision support systems that are fully integrated with personnel management practices.

Big Data Adoption

The federal government, which understands the vital role big data will play moving forward, is leading the charge. For example, the Office of Personnel Management founded a Big Data Community of Practice because it understands the importance of data for assessing and improving its own effectiveness. Through agencies and laboratories such as the Navy Personnel Research, Studies and Technology Center, the military has actively embraced the concept of collecting personnel data on a large scale for decades. The Centers for Medicare and Medicaid Services are using big data to support health care programs such as actuarial studies, fee-for-service compliance and other projects to measure and manage labor-intensive health care, where increasingly many HR professionals are employed.

Save Time and Money

Cost savings for enterprises that implement big data predictive analytics in HR will likely be driven by data collected in three areas:

1. Reduced recruitment cost through improved targeting

Much of today's recruitment advertising and promotion reaches a broad population of candidates, while the positions are increasingly specialized. According to TechCrunch, platforms like LinkedIn are using their own big data sources to improve job listings, so company-owned and managed big data sources can reach even better targets. HR could own big data-driven descriptions of positions that will break out of traditional occupational category descriptions. This can reduce the cost of position advertising and attrition costs by improving the candidate-position matching through analytics.

2. Reduced turnover cost by predictive analytics

More than most managers, HR leaders tend to understand the costs of employee turnover. Predicting indicators and trends for turnover allows for mid-course correction. Big data streams from on-the-job performance incorporate, but also go beyond, the obvious factors like absences and performance reviews, to more specific measurements. Examples of these big data sources include real-time call metrics for call center agents, manufacturing product and service quality for line works and sentiment analysis from social media for marketing. Per Entrepeneur, Xerox reportedly reduced its call center turnover by 20 percent using big data techniques.

3. Opportunities within the Internet of Things

The Internet of Things (IoT) is bringing new ways to measure the performance of people, products, services and the environments where they interact. Real time data from work environments can improve worker safety by providing alerts to employees, their managers and to enterprise risk models. IoT can help enforce workplace rules like hand washing and identify specific employees for remediation before sickened customers file class action lawsuits.

For example, an article in EHSToday reported on a collaboration between Honeywell and Intel that is designed to improve worker safety by developing an "industrial wearable solution for a connected worker to help protect workers from unexpected and previously undetected risks in industrial environments."

The Payoff

Improved retention and employee longevity will be supported by integration with intelligent decision support systems for HR. Although the implementation to augment your HR resources with big data analytics will initially require hard work, the cost saving opportunities will make the time and energy needed for extra data science training well worth the effort.