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Staffing Waste, New Hire Scrap Rate and Cost to Proficiency

by Joseph Murphy

PwC Saratoga released its Human Capital Effectiveness State of the Workforce Report.

Prior to the recession, first year new hire turnover was around 30%. I have labeled early new hire turnover Staffing Waste. It creates rework - the need to do it all again. Source, Select, Offer and On-board. An amazing failure rate. Stop and look at your organization. Where else does your CEO tolerate a a scrap rate of 30%

During the down turn, job security was uncertain, layoffs high, and new hire retention increased. PwC reported that last year Staffing Waste level is on an upward trend. Presently at 22.6%, up from its low point of 21.5%. This is a poor testimony to recruiting effectiveness and talent management. Who owns the budget for staffing waste?

Cost to Proficiency is the investment it takes to get a new hire to target productivity levels. This metric has two components with significant impact on the bottom line: time to proficiency and dollars to proficiency. In a job with a six month learning curve, an early turnover creates a one year time to proficiency and it creates two recruiting cycles to produce one performer. There is a pretty comprehensive article on the subject here. Staffing Waste

One of the most problematic issues talent professionals face is the assertion: "I am a good judge of talent." the PwC data would suggest 20% to 30% of the time the hiring decision is wrong. The assertion by those making hiring decisions is not supported with evidence.

The report goes on to suggest this upward tick in the staffing waste is an indication of 'breakdowns in the hiring and on-boarding process." I agree, and offer a caveat. We are moving back to normal. The low was a results of reduced career options, contracting workforces and a desire for stability in unpredictable times.

Averages Are Made of Highs and Lows So the average is moving up. But averages are made of highs and lows, what is yours doing? And no doubt, the causes of turnover are complex. But the use of internal big data can be revealing. If you have the data, and the skills to conduct the Talent Analytics.

One of our clients won the ERE Most Strategic Use of Technology Award. They documented the relationship between multi-method assessment results and a range of job outcomes, including 90 day retention. We prefer to examine 90 day retention versus one year retention due to the more direct relationship among the hiring decision and early success data. New hires either quit or get fired because of gross miss-fit. One year post implementation, the client realized about a 50% reduction in 90 day staffing waste. The downward trend line continues and now, 4 years later, they have a reasonably stable state level of 5% 90 day new hire turnover, or stated another way, a 95% yield in their staffing process for new hires achieving proficiency.

A Good Judge of Talent The client's ability to achieve higher levels of retention comes from evidence-based hiring. Big data, suggests the capture and analysis of large data sets. Big data practices can be applied to internal data sets. This surfaces as the active discipline and rigor of testing assumptions, and refining criteria used to to screen and evaluate candidates. In our practice, we continuously listen to clients asserting which experiences contribute to success. However, when asked about the analysis that supports that conclusion, it is absent.

Give me a call (888.845.7633) to discuss evidence-based hiring. You can learn more about the practical rigor involved in learning from your own big data. You may be able to buck the trend, and increase your new hire retention.