The term accurate or question, “How accurate is your cost model?” is a poor application of the word. To better understand this position, we first need to get the definition of ACCURATE. This is how the web defines it:
“The degree to which the result of a measurement, calculation, or specification conforms to the correct value or a standard.”
Hopefully, just reading this definition you see the problem with the question, “How accurate is your cost model?” The issue is that it is comparing your model to the CORRECT VALUE. So, what exactly is the CORRECT VALUE? The correct value is not now and never should be the supplier’s price. A Cost Model is built on facts and assumptions where a PRICE may have nothing to do with either. A price may be nothing more than what the market will pay and have no real ties to cost. The price is a constantly moving target and therefore should never be considered the CORRECT VALUE to be measure against.
How do you respond to the skeptics when challenged about your accuracy? You respond with facts. You explain that you built your model based on facts and data collected from reputable sources. Therefore, having good source of data is very important. You show you used industry standard accounting principles. You demonstrate the logic used to create the model. You explain to them that it is just math.
Unfortunately, convincing skeptics that the model is correct or “realistic” vs a “Theoretical”, “Optimal” or unrealistic can be a challenge. This difficulty is directly proportional to the gaps between the SHOULD COST and the current price. The larger the gap the greater the potential the skeptics will disagree and the bigger battle you will have. This is where solid data is even more important. There a numerous source of data. You can go to one place and get it all, you can go to various governmental agencies, it can even be part of the software solutions you select. You can subscribe to industry indexes as well.
Another way to disprove to the naysayers is to run sensitivity analysis. This analysis would be where you demonstrate the impact of varying the areas that have the biggest questions. What is the impact if you increase the material by 5%? What happens if you increase the cycle time by 10%? What happens if you depreciate the equipment over 7 years instead of 10 years? The idea here is to build confidence in your calculations. Show the minimal impact of each change INDEPENDANTLY.
The best way to quite the disbelievers, and this will take time, is to compare the data against the suppliers cost breakdown. Ideally this is done outside supplier discussions (these will be additional blog topics). You step through the cost breakdown line by line, assumption by assumption, data point by data point. You show you calculated the material cost by weighing the parts and multiplying the weight by the cost per pound from the published material index. You calculated the cycletime based on cooling time for plastics, cut time for metals, stroke rate for stampings etc. You demonstrate what it takes to match the supplier’s numbers. To get to their material pricing they would have to be either using “x” more material or paying ”y” more per pound. To get to their manufacturing costs they would need to have a cycletime of “A” or have a machine worth “B”.
The intent it to stop defending your model and to start challenge the supplier to support their pricing with facts.
Gerald (Jerry) Collins
Owner and Founder of Society of Cost Engineers