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Statistical Data Analysis

Q&A: How data can help cut labor costs

Running a business is expensive. Last year Deloitte revealed that a typical Fortune 500 company is overspending an estimated $30 million on labor costs alone each year. And while the first instinct when you need to cut costs is to reduce your workforce, changes needn’t be that drastic. Businesses have a wealth of data available that can provide insight into where inefficiencies may be occurring, they just need to know where to look.

In the lightly edited Q&A below, Brian Proctor, managing director, LaborWiseTM, Deloitte Consulting LLP, discusses the challenge of using data to combat labor overspending, and suggests ways companies can reduce their labor costs without compromising productivity or employee morale.

 

What types of organizational data can businesses use to help reduce labor costs?

Regarding hourly employees, there’s a lot of data—overtime costs, missed meals and so on. On-call is a common item; organizations often pay 10, 20, 30 or more people to be on call for an extended period of time but find their callback rate is actually less than 10%. So, there’s significant overspend in that area.

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