People analytics, which involves using digital tools and data to measure, report, and understand employee performance, is going through a major shift.
After years of investing in cloud HR platforms and specialist teams, many chief human resources officers and business leaders, including CFOs, are not getting the results they want. In response, organizations are redesigning their technical analytics groups and solutions to better deliver real-time analytics at the point of need in the business process.
Still, as discussed in the 2017 Deloitte Global Human Capital Trends report, it is a slow shift:
While 71% of companies see people analytics as a high priority in their organizations (31% rate it very important), the percentage of companies correlating HR data to business outcomes, performing predictive analytics, and deploying enterprise scorecards barely changed from last year’s study.
Data-driven tools can now help predict patterns of fraud, conduct organizational network analysis, show real-time correlations between coaching and engagement, and analyze employee patterns for time management driven by email and calendar data
Moreover, readiness remains a serious concern: After years of discussing this issue, only 8% report they have usable data; only 9% believe they have a good understanding of which talent dimensions drive performance in their organizations; and only 15% have broadly deployed HR and talent scorecards for line managers.
What’s clear, however, is that many CFOs see the potential in people analytics investments. In the Q3 2016 CFO SignalsTM survey, 40% of surveyed finance chiefs expect to make workforce and talent analytics investments in the next three years.
In this article, we will explore the increasing need for people analytics, and why embedding such capabilities in the business can lead to greater understanding of the issues and actionable insights.
New tools, new mandates
Multiple stakeholders, including the board, are driving this change. Senior leaders are impatient with HR teams that can’t deliver actionable information and insights; therefore, analytics is shifting from a focus on HR to a focus on the business itself. For example:
- Leading ERP vendors are implementing a set of people analytics dashboards to help senior leaders understand attrition, hiring metrics, employee cost, and employee engagement by geography, business unit, and manager.
- The chief operating officer at a large chain of hospitals uses analytics to understand patterns of patient outcomes and how management and people issues contribute to results.
- The sales organization at a major consumer products company has partnered with HR to develop a complete model for sales productivity, which helps predict and diagnose problems, pinpoint training solutions, and improve quality of hiring.
- A retail head of operations now uses business and people analytics to look at customer and employee traffic patterns, identifying new locations where sales people should be positioned to help improve total customer purchase.
For companies that have been investing in this area for years, it is now easier to get such answers than ever before. Predictive analytics tools from many HR technology vendors have arrived, making it possible to analyze data regarding recruitment, performance, employee mobility, and other factors.
Moreover, executives now have access to a seemingly endless combination of metrics to help them understand, at a far deeper level, what drives results.
Moving beyond the analysis of employee engagement and retention, analytics and artificial intelligence (AI) have come together, giving companies a much more detailed view of management and operational issues to improve performance. For example:
- Data-driven tools can now help predict patterns of fraud, show trust networks, conduct organizational network analysis (ONA), show real-time correlations between coaching and engagement, and even analyze employee patterns for time management driven by email and calendar data.
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