Predictive analysis has found its way into a rapidly-growing number of HR departments as word spreads about its ability to revolutionize the way companies recruit and hire.
Predictive analysis has been relied on for decades to support data-driven decision-making in industries like banking, insurance, marketing, and telecommunications.
Now, businesses across industries are harnessing the power of predictive analytics in recruitment to eliminate harmful hiring biases, identify top-performing candidates with high odds of success, and create fast hiring processes that save organizations time and money.
Sounds too good to be true?
Don’t worry. In this piece, we’ll break down the ins and outs of predictive analysis in recruitment and share a few tips any recruiter or HR professional can use to improve their hiring process and success with predictive analysis.
There are three primary types of analytics HR professionals can use to improve their hiring process: descriptive, predictive, and prescriptive.
Understanding the difference between these analytical fields will help organizations identify the best combination of analytics for their recruitment process.
Unlike predictive and prescriptive analytics, descriptive analytics focuses on providing insight into past events or actions.
Descriptive analytics is often carried out manually, and insights are shared using traditional business visualizations such as charts, graphs, and tables.
Descriptive analytics can be applied to the recruitment funnel and process by reviewing the success of particular recruitment actions and identifying problem areas in your hiring process.
For example, an organization that uses descriptive analytics to review its recruitment funnel might discover that, while they receive a large number of applications, most are underqualified and lack applicable experience.
This can signal to recruiters that they are casting too wide a net and allow them to correct course before wasting more time, effort, and money on recruiting.
Predictive analytics uses historical data and trends to forecast what is most likely to occur in the future.
Predictive analytics blends deep data mining, advanced machine learning, and complex statistical modeling to create highly accurate forecasts about anything — from the likelihood of a borrower paying back a loan to the future performance of a promising but inexperienced sales rep.
Predictive analytics is people analytics. It represents an exciting leap forward for the recruitment and hiring process. Insights gained after analysis allow recruiters to move away from subjective evaluations and 'gut feelings', and instead rely on data-driven candidate assessments.
The quantifiability of predictive analytics allows organizations to make strategic hiring decisions that are bias-free and highly likely to improve the performance and profitability of their human capital. And — it can save up to 23 hours of manual labor per week.
Prescriptive analytics reviews predictions provided by predictive analytics tools and identifies the best course of action moving forward. The main benefit of using prescriptive analytics is the power and versatility of prescriptive recruitment analytics tools.
Prescriptive analytics devices and tools analyze data to create multiple future outcomes, then rank the probability of each outcome using many variables.
An added benefit of this process is that prescriptive recruitment analytics tools can also provide an actionable roadmap to reach generated outcomes, providing strategic value to organizations that go beyond outcome prediction and advising.
When it comes to talent acquisition, predictive analytics in HR relies on massive amounts of raw historical data to drive machine learning, identify trends, generate valuable forecasts, and improve your hiring process.
Fortunately, the rise of workforce analytics has created vast performance, productivity, and engagement data sets that predictive analytics tools need to make quantitative and bias-free predictions that empower organizations to hire the right person, every time.
HR Departments can also use predictive analytics to automate time-intensive manual aspects of the hiring process, like early candidate screening.
Predictive analysis tools can evaluate interested candidates, and provide recruiters and hiring managers with a data-driven shortlist. This allows hiring professionals to focus the entirety of their efforts and attention on excellent candidates.
For talent management, predictive analytics can help recruiters improve every aspect of their hiring process. Let’s take a look at five ways predictive analytics can improve hiring success.
High levels of diversity, equity, and inclusivity have never been more important for businesses to develop to improve their hiring process.
Job seekers want to be a part of a creative, innovative, and diverse workforce and will pass up job offers from companies that can’t deliver that experience and equity.
Predictive analysis solutions eliminate the human biases that hold back DEI progress and allow companies to make fair, equitable hiring decisions.
Analytics recruitment tools can help uncover the factors and traits that separate your top-performing employees from the middle-of-the-pack performers.
This analysis of your top performers allows HR to identify the key characteristics of their ideal applicant and engage in precision hiring efforts to attract and recruit professionals that match that profile.
This allows organizations to grow their team strategically and deliver maximum performance with each new employee by only onboarding high-performing job applicants that will mesh with your current roster of MVPs.
Performance Fingerprints achieve this by analyzing candidate profiles and background data to identify key indicators that point towards extremely low odds of short-term churn.
With new hires costing organizations anywhere from 1.25 to 1.4x a position's first-year salary, reducing turnover and improving retention can save companies significant recruiting expenses while improving workforce morale and their reputation as an employer.
This benefit may seem redundant after the DEI section, but the truth is, bias is a problem in hiring that is worth discussing in-depth.
While many companies have begun to engage in anti-bias training to reduce the impact of explicit biases on their hiring process, implicit or unconscious biases still pose a significant challenge for many HR departments.
Lesser-known biases such as pedigree bias, attractiveness bias, and confirmation bias can all negatively impact your hiring ROI. Fortunately, the best predictive analytics tools eliminate bias at large, allowing organizations to hire with confidence.
Perception Predict was created by a world-class team of data scientists, I/O consultants, psychologists, and business leaders to bring the revenue-driving power of predictive analytics to businesses across the globe.
Our predictive analytics-powered Performance Fingerprints have been employed by multinational business leaders like Mercedes-Benz and preeminent cybersecurity firms like CrowdStrike to build exceptional, high-performance sales teams.
38% of companies use predictive analytics, and 62% expect to follow suit by the end of the year. If you’re ready to join the ranks of companies that have upgraded and modernized their recruitment and hiring process with predictive analytics platforms but aren’t sure where to start, book a demo with one of our experts today.
We are available instantly from 7AM-7PM EST Monday-Friday in our digital company headquarters. Stop by and speak directly with real, smiling, helpful humans. We are working hard to help you build and optimize the people part of your business. Stop by and say "hello", and say "goodbye" to hiring frustrations.