Cost-Modeling Applications in the Decision-Making Process: A Service Outsourcing ExamplePosted: May 8, 2012
In this engaging session, a father-son presenter team set out to show attendees how to “sell” cost-modeling data — not only to suppliers when negotiating, but also to decision-makers in their own organizations when the data they uncover indicates a change is in order.
Victor Sower, Ph.D., C.Q.E., distinguished professor emeritus of operations management at Sam Houston University, and Christopher Sower, MBA, C.P.M. director of global logistics at Champion Technologies, began their session with a basic overview of two types of cost modeling: internal and external.
“Internal cost models are created with internal data you already have,” they explained. “But, that doesn’t mean it’s easy. That data is rarely in the right format, and you have to go digging for it.” These cost models can be instrumental in identifying the break-even point for production of a new product or when a make-or-buy decision needs to be made.
External cost modeling is even more difficult; it relies on data about a supplier, or potential supplier. “With external cost modeling, you’re trying to project what it should cost an upstream supplier to produce an item,” the Sowers said.
For this session, they chose an industry-specific example of external cost modeling to illustrate their points – specifically, a trucking supplier. In this example, a refinery was undergoing a large capital expansion that would triple its truckload needs from 32 per day to more than 130.
When calculating this cost model, the Sowers crunched a lot of data: indirect costs (insurance, maintenance); direct costs (driver wages, truck purchase price — including amortization and depreciation); diesel fuel (price, mileage); work time restrictions; shipping and receiving hours; and time/distance data (loading/unloading times, transit times). All costs were then broken down into dollars-per-minute values or dollars-per-mile values, and then applied to loading/unloading and trips both ways.
In the end, the Sowers found that the indirect costs quoted by the carrier were 23 percent higher than the industry average. Additionally, its quoted net profit was 55 percent higher than the average. Altogether, the trucking company quoted their total operating cost at more than $96 per hour. The Sowers’ data calculated it to about $86. They settled on a price around $87 an hour.
“And they were already the lowest-cost provider!” Christopher pointed out, illustrating the importance of not always accepting the initial bid, even it it’s the most competitive.
“We entered into a fact-based negotiation and were able to use the supplier’s own data against it to get the cost down,” they told attendees. “It’s way tougher to go in and demand, ‘I think my price is too high.’”
But, one task is even more difficult, according to Victor: enacting change based on that data – even if it’s in the company’s best interest to switch suppliers. Inertia and hidden politics are frequent, frustrating roadblocks.
To combat both, the Sowers recommend getting the most likely naysayers involved early in the cost modeling process. “To drive change, it takes one of two things: lowering the resistance to change, or increasing the forces for change,” they concluded.