Say Good-bye to Should-be Costs and Hello to Predictive Pricing 

I have been around cost estimates and should-be costs since 1984 when I joined Ford Motor Company with my newly minted MBA and partial head of hair (yes, it is all gone now). 

While should-be costing provided real insights into costs and pricing, I always found it to have some drawbacks: 

• Many suppliers find the term and the process offensive by implying the manufacturers’ experience makes them the experts on costs. 
• It places the buyers on the defensive by having to explain why their should-be model is correct and the suppliers’ costs are wrong. 
• Some buyers abdicate their negotiation responsibility by relying on their should-be cost estimators to work with suppliers to bridge the gap between estimates and the suppliers’ costs. 
• Some of the costing software has become so complex that even the cost estimators can no longer explain the intricacies of their estimates. 
• Market forces, not should-be costs, are more important in driving pricing for some commodities. 

By using Predictive Pricing, we can realize the cost estimate benefits while eliminating the drawbacks.  The key aspects of APD’s methodology for Predictive Pricing are as follows: 

• Provides a variety of methods for estimation including linear, multivariable, and knowledge-based cost methods as well as open book costing on the supplier shop floor 
• Determines an estimation method that is correct for the commodity and the level of commodity spend 
• Looks at the statistical variance of supplier quotes and prices compared to the model estimation 
• While admitting the model is an estimate, it provides a consistent measuring stick to supplier pricing and quotes when negotiating with suppliers.  Using this method, a buyer can tell a supplier: “Your quotes are consistently 7-9% over the model.  Your competitors are winning business at 3-4% over the model.”  Buyers no longer need to defend the model because it is used as a comparator and not a should-be cost. 
• Uses the statistical variance analysis between estimates and supplier pricing to develop Predictive Pricing for new programs 

APD has two white papers on building cost estimation models: