5 Trends Driving the Growth of People Science

5 Trends driving the growth of people science

People science or people analytics is 2017’s “must have” for businesses. Driven by the widespread adoption of Cloud HR systems, companies are investing heavily in programs to use data for all aspects of workforce planning, talent management and operational improvement. As more data becomes available, the work of people analytics teams will become central to management, leadership and human resources.


So what has caused this uptake in people science? The answer can be found in the growing competition companies face and the need to use data to improve efficiency, cut costs and enhance performance coupled with better data analysis tools available to them to monitor their workforce, identify areas for improvement and diagnose problems in real time.

Below are five key trends driving the growth of people analytics.

1) Digital business and HR’s changing role

Technology is driving continuous change. New business models are disrupting previous ways of doing things, and people with the right skills are needed to enable companies to take advantage of these shifts. The problem is that these skilled people are in limited supply as demand for their skills continues to grow.  Board members and CEOs are pushing their HR teams hard to deliver insights on the workforce that they can act on to recruit the best talent, improve performance, reduce risk, or cut cost across the business. They are simply not satisfied with updates from HR on engagement analysis and retention modeling any more, they want business analytics—to understand what they know about their people that can help to drive the business.

2) Analytics are “federated”

HR analytics was traditionally the domain of HR departments. Today companies are re-thinking HR as an “intelligent platform” embedding analytics into the entire workforce management processes and operations. HR analytics has expanded to people analytics, the changing terminology reflecting the expanding breadth and depth of scope. Teams and line managers across the company have access to pre-built dashboards with real time data measuring what really matters to the business, enabling a much more joint up response to operational issues.

3) Better tools available

Predictive and other analytics tools on the market are better and more readily available to companies, making it possible to analyze data regarding recruitment, performance, employee mobility, and other factors. Businesses now have access to a wealth of different metrics to help them understand, at a far deeper level, what drives results.

4) Organizational Network Analysis (ONA)

Recruitment remains the number one focus for people analytics followed by performance measurement, compensation, workforce planning and retention. However, there has been a massive increase in the use of organizational network analysis (ONA) and interaction analytics to study employees’ behaviour to better understand opportunities to improve the business as a whole. ONA is a structured way to visualize how communications, information, and decisions flow through an organization. Visualizing and analyzing formal and informal relationships can help shape business strategy that maximizes organic exchange of information, thereby helping the business become more sustainable and effective.

5) Augmented Intelligence (AI) + analytics

AI is becoming more common in businesses, so it is no longer necessary to just “model a problem”—many software tools now “prescribe or recommend” solutions. Thanks to AI, people analytics has moved beyond measuring engagement and retention, providing companies with a much more in-depth view of their management and operational functions empowering them to make improvements. Data-driven tools can now help predict patterns of fraud, show real-time correlations between coaching and engagement, and even analyze employee patterns for time management driven by email and calendar data. AI software can also analyze video interviews and assess whether a candidate is being truthful in their answers, exaggerating or is a good cultural fit. It can even measure overtime allowing companies to improve their work practices, cutting down on unnecessary overtime and saving millions of dollars.  Furthermore, off the shelf retention models are now available on the market making it easier to understand drivers of attrition.

It’s official, people analytics has arrived. People analytics is now commonplace in companies, providing valuable insights across organizations, yet many still struggle to find people who can analyze, interpret and react to data in an advantageous way. Moreover, data management remains a problem despite the heavy investment in cloud systems. There is still work to be done but it is clear that in 2017, the people analytics revolution has begun!

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