The Cost of not Deploying Operational Analytics

Posted On : Jan 26, 2014

Implementing a labor management system or other operational analytics platform is generally viewed as a large, complex project on par with rolling out an ERP system or other enterprise level technology. Since these systems do not run mission critical processes for the company, they are often delayed due to other priorities. However, for most companies, labor is the largest expense, so companies really need to consider what is the cost of not having this type of technology in their business.

 

Easy Metrics has consistently seen productivity gains of 25-40% in its customers. What is the cost of not having those gains?

We have worked with and studied hundreds of different production operations covering a range of industries from warehousing, assembly, insurance claims management, call centers, data entry, government licensing, seafood processing, packing houses and many others. In operations where employees have a direct impact on productivity levels and are not consistently measured, the variance between the most productive employees and least productive is 200-300%. In other words, if the average employee produces 100 units/hr, the top 20% will be around 150 units/hr and the bottom 20% will be around 50 units/hr.

Using this example, a simple way of getting a 10% increase in productivity is to train/replace the bottom 20% with employees that can produce at the average. What is the cost of not doing this? Let’s assume 100 employees with an hourly cost of $15/hr. Increasing productivity by 10% basically means you need 10 fewer employees. So instead of spending $1500/hr on labor (100*15) you are spending $1350/hr on labor. For an 8 hour day, the savings is $1200 per day, $6000 per week, $25,800 per month, and $312,000 per year.

The above cost savings is only looking at a basic deficiency correction model. On the employee side implementing a comprehensive operational analytics model with employee feedback, activity cost accounting and incentives can achieve cost reductions of 15-20% operationally. Additionally, understanding your cost to serve enables you to right price or eliminate unprofitable customers, further adding to your bottom line.