Is HR the Most Analytics Driven Function?

Traditionally, HR is very people-oriented (after all, it’s in the name). People drawn to HR have a talent for finding people, hiring people, and helping people thrive in the work environment. It’s all very focused on the human element of work life and company productivity. But HR has also stealthily become one of the most data- and analytics-driven functions in business.

It’s not just that sophisticated analytics make sense for HR (complex data allow organizations to recruit smarter and serve their employees better), but also that HR is leading the way. Even finance, arguably the most data-centric field, relies on descriptive analytics (preliminary results/analysis) rather than predictive analytics (identifying probable future trends) or prescriptive analytics (plotting the best path forward based on the data), which take data to the next level and put it to work to make substantive and productive changes.

According to a recent study by Oracle, only 37% of finance respondents were comfortable performing predictive or prescriptive analytics, while 51% of HR respondents were able to use them. This suggests that having data (which the finance industry has in spades) is not the same as being able to wield it effectively. In the survey, 98% of HR respondents agreed that “my HR function is highly skilled at using data to determine future workforce plans currently.” Similarly, 94% of HR respondents agreed that “We have accurate, real-time insight into our employees’ career-development goals currently,” showing one of the biggest values of an analytics-driven strategy.

What Is Driving This Trend?

One of the biggest drivers of the analytics boom in HR is Artificial Intelligence (AI). It may seem counterintuitive that robots are the biggest change agents in Human Resources, but the unprecedented nimbleness of artificial intelligence programs and machine learning are creating an environment where organizations are able to identify who and where to recruit, which employees might be at risk (or who are primed for success within the company), and where they can best target their resources.

Why Are Analytics So Essential To HR?

The short answer is flexibility. In the past, so much of HR’s work was done in the hope that it would yield the right results. From recruitment venues to processing applicants to filling vacant roles, analytics give real-time insight and the ability to determine and adapt strategies accordingly. Organizational strategies that were once implemented on a yearly level become adaptable as real-time results come in and predictions about the near future are made, allowing organizations to reallocate time and resources away from areas that aren’t working.

What Are The Most Important KPIs?

Establishing and tracking key performance indicators (KPIs) is one of the most important ways an organization can improve its analytics game. KPIs (or strategic metrics) measure how HR is using its resources and help determine how successful HR is within the organization as a whole. Tracking and developing a broad database gives organizations incredible insight and predictive abilities for future planning.

Some of the most productive KPIs in HR include:

  • Average time-to-hire
  • Average cost-to-hire
  • Average employee salary
  • Average retirement age in the organization
  • Average number of training hours per employee
  • Percentage of cost of workforce (cost of workforce compared to all organizational costs)
  • Average number of vacation/unpaid leave/time off per employee

Having these numbers in your pocket and knowing how to turn them into strategic plans for the future help improve HR return-on-investment (ROI).

That so many in the HR field feel ready and capable of using advanced analytics is a great sign for the future. This commitment to taking the nearly unlimited data out there and wrangling it into useable metrics is putting HR at the very forefront of all fields.

However, there’s still plenty of room to grow. In the Oracle study, one of the HR respondents’ biggest goal areas for improvement was pushing analytics even further. So if your organization is still getting up to speed with the latest ways to maximize your analytics, you’re in good company.

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