Why you need a data-driven recruitment process in a candidate-short market?

Your data is a veritable minefield. It can help you optimize costs, reduce manual effort, increase productivity, improve recruitment outcomes, and ultimately find and retain the best people for your business. And there’s a ton of it. According to recent global research, the average enterprise holds a whopping 2,025 terabytes of data.

But the key lies in how you leverage it.

Used well, your data can streamline the end-to-end recruitment process. In fact, data analytics can be employed across the lifecycle to source, screen, evaluate, and onboard best quality candidates.

However, the same report referenced above found that 43% of this data was simply not used at all. So how do you make the most of your recruitment data to make more informed hiring decisions? Harnessing predictive analytics is the answer.

Of course, a human simply cannot interpret data at this scale, and even the small amount we can process is open to our inherent biases. However, machine learning and modeling techniques can do what we can’t – hoovering up this data to make informed, bias-free decisions fast.

Essentially, predictive analytics refers to the process of using historical data to predict future outcomes. When it comes to recruitment, this is about using your existing hiring data to inform future recruitment decisions. For instance, predictive analytics can analyze candidate inputs, such as CVs, cover letters, assessments, and even their social media presence, to determine whether a specific candidate will be the right hire based on what has already worked for you.

In fact, it can be used to improve almost every step of the hiring process, eliminating bottlenecks and increasing speed. Some key areas include:

• Candidate sourcing – understand which sources are delivering the most qualified applicants to allocate budget and resources more effectively and ultimately reach the best candidates for your role.
• Candidate screening – understand which candidate screening and assessment techniques are the fastest and most accurate for specific role types to increase speed and improve outcomes.
• Candidate engagement – understand how to engage candidates better, reduce drop-off and increase speed and efficiency from application to onboarding.
• Candidate performance – predict how well a candidate will perform in the job based on their application and assessments and your current workforce data.

The most forward-thinking organizations are even taking it beyond current hiring processes, using the data to understand future hiring needs. Predictive analytics can help you determine:

• Which positions are likely to become vacant soon
• Which roles and skills are needed most urgently to meet business needs
• How long a new hire is likely to stay in the business

Harnessing these insights to build a data-driven recruitment process will ultimately increase your recruitment efficiency and success.

Making the most of your data to drive better recruitment has several first and second-order benefits that may be your competitive advantage in a challenging market. Properly used, your data should help you to:

• Understand and find the skill mix you need today and tomorrow to hire proactively
• Predict which roles are likely to become vacant and where you need new skills
• Identify at-risk employees who may be likely to leave soon
• Inform your sourcing decision to attract more top candidates
• Eliminate the influence of human bias in candidate screening and shortlisting
• Provide meaningful insights that help you make the best hiring decision
• Reduce costs through more informed resourcing
• Identify recruitment bottlenecks
• Optimize the candidate experience to reduce drop off
• Increase speed to hire by streamlining the end-to-end process
• Reduce manual efforts and inefficiencies

At the end of the day, recruitment is a critical investment for any business. Leveraging your organization’s historical data to predict its future needs and enable success is a must to reach the best candidates for every vacancy.