Predictive Analytics Set To Define HR Tech in 2022

2021 was an exceptional year in many ways for predictive analytics in the HR domain. Talent acquisition professionals had to entirely revamp their hiring processes and the remote-first workplace remained status quo. On top of that, the Great Resignation saw more than 4 million workers a month voluntarily leave their jobs some months, creating one of the toughest talent markets in modern times. Many HR leaders have turned to technology to adapt to and navigate through these dramatic changes. 

From talent acquisition to retention to diversity, equity, inclusion, and belonging (DEIB) initiatives, technology will continue to play a bigger role in helping HR teams move quickly and efficiently in the coming year. Here are four HR technology predictions that I expect to shape and reshape the industry in 2022. 

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Optimization Goes Multichannel

Talent acquisition teams have heard a lot about optimizing their targeting across various channels—how it increases performance, increases the likelihood of candidates finding your posting, increases an employer’s brand recognition and deliver a more favorable return on investment. It can raise the department’s profile, as well, by surfacing candidates who are closely aligned with a job posting’s requirements.

How talent acquisition teams apply optimization has become more sophisticated over the last several years, in part because it pays real dividends. Research by industry analyst Josh Bersin and consulting firm Deloitte found that employers with “high-maturity” talent acquisition realized 18% higher revenue and 30% greater profitability compared to companies whose efforts were “low maturity.”

The de-facto platforms for recruiting were once the company’s website, job boards, LinkedIn, Facebook and Twitter. These days—particularly with the growing need to reach passive candidates—businesses are approaching 2022 searching for new ways to take optimization to the next level. Next year will be the year the optimization of recruiters’ work will hit its stride. We’ll see more getting creative and expanding their efforts into channels such as TikTok, chatbots, Reddit and influencer marketing. The concept will become increasingly multichannel, putting candidates squarely at the heart of talent acquisition efforts, across campaigns.

Predictive Analytics Plays a Bigger Role in Retention

In this day and age, predictive analytics is an expected component of Human Resources, helping practitioners anticipate and respond to challenges like employee turnover, and planning for appropriately targeted retention efforts. 

Especially during periods like today’s Great Resignation and in remote or hybrid environments, it’s critical for business leaders to understand which employees are at risk of leaving, why they’re considering leaving, and what the organization can do to either prevent or better plan for the outcome it desires. That kind of ability, HR leaders say, calls for focused discussions around ways to better engage employees, to consistently measure employees’ experiences and to understand what forces outside of work might be affecting them.  

Dashboards that present predictive analytics can share information to inform decisions on hiring, retention and flight risk. In turn, data experts say, organizations will be able to improve their performance in specific business areas, such as sales growth, customer satisfaction, turnover, retention and manufacturing output. This can be particularly helpful for companies competing in tight labor markets or looking for people with scarce skill sets. 

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Personalization Expands in Talent Acquisition

Today’s job market is so dynamic, so active, employers have to make every connection count. When multiple roles are in play, it’s counterproductive to cast a wide net—if you don’t proceed in an intelligent, focused way, you’ll not only attract more candidates than you can handle, but more candidates who aren’t qualified to solve your problems. In other words, sometimes narrow is better.

This is especially true when it comes to passive candidates, which are becoming more prevalent and making the recruiting process exponentially more challenging and time-consuming. Oftentimes, they’re more likely to have their head down to work than to be scanning the market for their next opportunity. Nor are they likely to notice your newest social media campaign—its message is too broad. Getting their attention requires true personalization, which can entice targeted candidates to consider your opportunities first, streamline the hiring process, and lay the groundwork for a rewarding relationship, regardless of whether a candidate gets this particular job.

Although it may sound counterintuitive, automation will be increasingly used to achieve personalization early in the recruitment process by automatically sending them tailored communication using the channels they prefer and timed exactly right. A/B testing elements such as subject lines and message length and call to action can help dial this in. Then, when they move further on in the process, talent professionals can step in to help seal the deal with a hands-on approach. 

Continued Focus on AI and Machine Learning 

The rise in data has been supported by a growing dependence on artificial intelligence and machine learning. Once a sign of cutting-edge technology, today they’re considered table stakes by both HR and technology leaders.

For good reason: When powered by advanced technologies, data and analytics help companies improve hiring productivity and develop efficiencies in their talent acquisition processes. These are particularly important as talent acquisition teams struggle to meet increasing recruitment goals, survey a talent pool that has expanded exponentially and meet the DEIB goals their companies set during 2020 and 2021. AI and machine learning will have expanded roles in helping companies cut through bias by identifying candidates based on attributes and true matching attributes instead of keywords. 

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AutomationHR technology trendshuman resourcesmodern talent acquisitionpersonalizationPredictive Analytics
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