Predictive Analytics in Human Resources (HR) Explained

You might have come across the term “predictive analytics”. But what is it and how does it work? 

Essentially, predictive analytics is applied everywhere – from banking, marketing, sports, to even dating apps!

In recent years, this technology has been trending in HR. While some might think it’s just a buzzword, many reputable organizations have started implementing it and have since seen significant improvements in talent and business outcomes.

So in this article, we will explain all you need to know about HR predictive analytics and how it is revolutionizing HR.

 

What is Predictive Analytics?

Let’s start with a quick understanding about what predictive analytics is about.

Predictive analytics is a form of advanced data analytics that uses existing data to make predictions about future outcomes. It can help organizations generate future insights with a significant degree of accuracy.

This concept was made popular by the 2011 movie, Moneyball. Based on a true story, a baseball game manager and a Harvard graduate used predictive analytics to forecast the potential success of individual baseball players. In essence, it enabled them to explicitly scout for the high-performing players that were overlooked and undervalued in the market and manage risk. This led to the team winning 20 consecutive games between August and September 2002.

Source: Amadeus

So how does it work? Simply put, predictive analytics is done on historical data and outcomes. It then creates a formula, or an algorithm, that best models these historical outcomes. You can then run your current data through this algorithm to predict future outcomes.

 

How is it revolutionizing HR?

HR is a business function that has historically been the custodian of most organizational data. Most HR teams practise data-driven decision making to a certain extent. While it’s true that they have been able to use data to understand talent and workplace factors, the data was mainly descriptive of the current state of things.

Source: High-Impact Talent Analytics, Bersin by Deloitte, 2013

The graph above shows the levels of talent analytics maturity as defined by Josh Bersin, in a research collaboration with Deloitte back in 2013. However, a more recent survey in 2018 by Bersin found that 84% of companies were still in the first two levels of the model, which is operational-focused. Digital disruption, increased competition for talent, and changing workforce models have compelled HR leaders to advance to the more impactful, less administrative areas of people analytics.

Predictive analytics is a game-changer for HR because it enables the team to use data to not only learn about what happened but also make highly accurate predictions of various areas of the entire talent lifecycle – from identifying best-fit candidates, culture fit of an employee, their likelihood to stay engaged on the job, and their ability to perform under pressure, to name a few.

With those insights, HR can then hire more effectively, proactively engage and retain employees and reduce expensive turnover. This puts HR at a better position to become a strategic partner to help drive the overarching goals of the organization – using proven and data-driven predictive models, instead of relying on gut feeling.

 

Using predictive analytics to improve talent acquisition

Predictive analytics models can be used to identify candidates who are the best fit for the role and organization more quickly and accurately as compared to traditional screening methods. An AI screening tool that leverages predictive analytics can provide recruiters with information on how well the candidate’s skills, behaviors, interests and values match the role. In a competitive talent market, this allows employers to identify the top talent and make an offer to those candidates faster than the competition. This also results in improved time-to-fill and quality of hire. 

To implement a predictive analytics solution, employers first need to identify the key competencies and factors associated with success for a given role. This can be done by analyzing the data of previous hires, existing talent base or by referring to external data libraries. 

Once that’s done, the tool can use this information to identify candidates that best match the success profile. Using available data, the tool will also make predictions about the candidate, and the recruiter can use those predictions to determine which candidates to move to the next stages of the hiring process. With Pulsifi’s People Data Platform, we unify multiple data to provide a ‘fit score’ for each candidate that represents their overall fit to the role, which you can easily rank to focus on the candidates with the highest fit scores. 

Other than selecting the top candidates for the role, this form of sorting also eliminates subconscious biases in hiring that could cause a good candidate to be sidelined for reasons unrelated to their capabilities and potential. This encourages recruiters to consider candidates from a neutral perspective and focus on assessing the candidate based on their merits rather than social factors, ultimately improving the inclusivity and diversity of the organization — both of which are important for innovation and business success.

 

Using predictive analytics to improve talent management

Hiring right is just the first half of the equation. The challenge next is how to engage, develop, and retain these talent. Using a similar process to selecting the best candidates for a new role, predictive analytics can also be used to identify high potential (HiPo) employees and develop them for leadership roles. Whilst performance and high-potential are not mutually exclusive, HiPos are much more than just high performers. They are future leaders who demonstrate certain behaviors which make a meaningful impact on their team and the organization. 

By feeding employee data into the predictive tool, it can predict these behaviors that are intangible and often difficult to quantify to determine which employee exhibits the most potential or how closely aligned the employee is to the new leadership role. This analysis can also reveal the gaps that can be addressed to better equip them for their next role in the organization. On top of that, analytics can help pinpoint underlying factors that contribute to attrition and in turn, improve retention of talent.  

When it comes to retaining top employees, it is key to understand what motivates them and figure out how to help them thrive. Providing development programs that are relevant to the employee’s needs ensures the employee stays engaged and maximizes the value to the program. Predictive analytics can help suggest whether training is required for a particular employee and how to best design the program based on the parameters around the individual or team as well as the job requirements. Using Pulsifi’s platform to truly understand your talent, you can easily personalize your learning and development to create more meaningful and highly targeted learning experiences for your employees. 

 

Is your team ready to take advantage of predictive analytics? 

If so, talk to us here. Our product experts will be happy to give you a tour of our platform and how it can help your use case. At Pulsifi, we will work the ground with you to understand your requirements and tailor our solution to your needs. You can choose to kickstart with a pilot project in a critical business area to show results to further convince other stakeholders. Let us align on your requirements, take care of the rest, and help you bring your people strategy to the next level.

 

Jo Ee Hoo
Jo Ee Hoo

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