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Predictive analytics has become the standard decision-making framework for finance, marketing, healthcare, retail, logistics, and countless other business operations. Predictive analytics also powers our non-working lives, from Amazon product recommendations to travel itineraries and social media news feeds.

Predictive Talent Analytics – Where Do We Start?

When it comes to adopting predictive analytics for talent decisions, however, HR still faces many barriers. In a recent webinar, HR Tech expert Greg Moran talked about the top use cases for predictive analytics in HR, and barriers including a lack of analytical expertise, as well as silos in and outside of HR.

To help HR leaders overcome these barriers and begin using predictive talent analytics, Greg answered the industry’s top questions on skills, silos, and technology in HR.

HR is traditionally a soft-skills industry. How do we improve our analytical capabilities?

The best place to start? An online class. An intro-level understanding of data analytics would be helpful to everyone in HR today. You don’t need a Ph.D. in data science, nor do you need to gain a mastery of statistical analysis. You can hire data scientists and data analytics teams for that. Your goal should be to adopt an analytical mindset where you can start to think in terms of ‘How do we apply data to our biggest business challenges, what kind of questions can we answer that we weren’t able to answer before, and how do we get access to the data and technology we need to improve the operations of our business?’

Talent Acquisition and Talent Management departments are often disconnected. How do we connect these teams together so we have more access to data?

This is really common area where silos form within HR. The first step is to build a business case for sharing data, which involves articulating the types of questions you want to answer and the results you’re aiming for.

You can say, ‘As a talent acquisition organization, we don’t want to just understand our cost per hire or our time to hire. We want to understand how we’re impacting quality of hire and the overall performance of the business. The only way we can understand that is by getting access to post-hire data.’

A big challenge in HR is being able to articulate bottom-line results. So, take your case a step further by saying, ‘We believe that by connecting performance data to pre-hire data, we can improve our hiring decisions for a 10% increase in sales’—which, depending on your business, can have millions of dollars of impact. And that’s a compelling reason to make a change.

There are a lot of IT products on the market. Which is best for HR analytics?

The answer to this depends on what you’re trying to accomplish. Before you look to technology, you first need to understand the business questions you’re trying to answer. Are you trying to solve for turnover? Are you trying to solve for performance, or diversity, or some other challenge? The technology you choose should be geared toward driving business intelligence in those areas.

If you’re trying to solve for employee performance and turnover, you’ll benefit from using a predictive analytics tool in your selection process. A predictive talent assessment, for example, will analyze performance potential and turnover risk to identify your top candidates. Another good option is an employee engagement tool, where you can start to identify correlations between engagement, performance, and turnover. All of this you could potentially do on a spreadsheet, but the technology is there to provide efficiency and transparency into your processes.

To learn more about improving HR’s analytical capabilities and getting started with predictive talent analytics, watch our webinar: How to Gain an Edge with Predictive Talent Analytics

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