Can Predictive Analysis Improve Your Hiring Process?

The global economy is on the rebound, and pressure has increased to quickly land top talent. Otherwise, you risk losing A-level performers to your competition. Leading candidates have choices and are poised to move rapidly into whatever environment they see as best to advance their careers. They’re ready and willing to take that leap today to ensure their successful tomorrows.

The solution lies in predictive analysis, which when applied to the recruitment process, is known as talent analytics or workforce science. And that’s just what it is: a science. Predictive analysis uses historical data and current inputs to make accurate forecasts on future behavior. Organizations that adopt it enhance their hiring effectiveness by gaining a better understanding of which employees are successful – and why. They build robust, data-driven frameworks to rank recruiting sources and from there, precisely channel their future HR investments.

Tech Advances Drive Success

Though the fundamentals of predictive analysis have been around for decades, recent technological advances have taken it to new heights. These include:

• The growth of cloud-based applications: Platforms can be easily connected to create maximal interoperability.
• More cost-effective data storage: New apps are constantly being developed to make data easier to manage, process and analyze. Likewise, business intelligence engines are becoming more powerful and user-friendly.

Better Sourcing

Predictive analysis enables you to enhance recruiting as you accurately trace hires back to their sources and then link this information to quality of hire. You can then optimize your recruitment marketing and eliminate any poor sources. Sources that make your top tier can be lowered in priority or cut from your budget.

Enhanced Quality of Hire

Through the use of advanced analytic techniques, modeling frameworks and data from various sources, predictive services can link employee behavior and performance to desired business outcomes.

• First-year turnover is a good indicator of quality of hire. Generally, if an employee leaves your company during their first year of service, this is an indicator of either poor selection, poor onboarding or both. One recent study shows that first-year turnover grew from a historic low of 21.5 percent in 2011 to 22.6 percent in 2012 and 24.1 percent in 2013. This reversed trend may indicate breakdowns in hiring and onboarding. The survey of more than 150 U.S. companies also found the average annual cost of recruiting and staffing to be $357 per employee. That’s $357,000 for an organization with 1,000 workers or $3.57 million for a company that employs 10,000.
• Make sure your hiring models have measurable processes and reliable data. This may include pre-employment assessment and interview results, recruiting sources, engagement survey results and/or turnover statistics. By linking your hiring process to key indicators from the employee lifecycle, models can be developed and fine-tuned to predict the potential future performance of a candidate.

Improved Speed of Hire

As you build your quality-of-hire models, your understanding of which candidates are your best choices will grow. Then you can deploy tools that serve as leading job performance indicators. Your recruiting leaders must understand that:

• The amount of data involved in predictive analysis requires a technological investment, as well as business intelligence apps to apply it.
• Your company needs a team that understands data modeling and technical infrastructure and has the “right stuff” – namely, the experience and credentials to develop and review content.
• Models must be built on reliable data captured in a consistent fashion.

It’s a lot to digest – and the technical aspects of predictive analysis evolve at a breakneck pace. To help you stay current and ahead of your competition in today’s talent war, call upon the executive search consultants at BrainWorks. Read our related posts or contact us today.