There has been a lot written over the years extolling the virtues of “should-cost” in the world of product cost management. There are approximately 10 specialty software products that will help you calculate should-cost; major consulting firms talk about should-cost and, of course, will help you with it.  It is a major focus for the U.S. government, as well.   In fact, if an executive or manager is asked , “How important is it to know what the parts you buy or will manufacture should cost before committing to a supplier or a make/buy decision?” nearly 100% of the managers will answer that it is very important, or critical, to the profit of the firm.

Very few firms, though, have a standing, well-functioning process for should-cost.  For most purchasing organizations, it is not a part of the culture to ask what something should cost BEFORE going out for quote.  The best situation is that there are a couple of cost experts, sitting in the back corner of the purchasing department, who are masters of one or two of the specialty product cost management (PCM) software tools.  However, these people never have enough capacity to fully serve the buyers in the purchasing department, let alone to support engineering with design-to-cost activities.  I have worked in the PCM field for 20 years now, first as a researcher in feature-based costing, then founding and leading one of the PCM software companies, and now as a PCM consultant.  I have experienced the situation above in 99+% of the companies that I have encountered.

Why, deep down, no one really cares about should-cost

If we accept that (1) should-cost is very important to creating and improving profit, (2) adequate tools exist to help with the difficult task of should-cost, but (3) almost no firms regularly use should-cost in their product development and sourcing processes, we have to ask “why?”  Why is it that no one really seems to care that much about should-cost as a strategic tool for increasing profit?

One answer is that people see should-cost as a “nice to have” and as a theoretical exercise that is often “wrong.”  To most people, “wrong” means that the should-cost prediction for a given part was $105 when the part actually cost the firm $86 or $142. The should-cost estimate is not within what the user thinks is a “reasonable” range of estimation error.  Therefore, should-cost gets pushed aside in many people’s minds as an imprecise and useless academic tool that provides little value to the firm. 

Should-cost as a leverage tool, not a diagnostic tool

In the short example above, the root cause of why people judged the should-cost estimate to be wrong was that they used should-cost merely as a predictive tool.  They wanted what I call “absolute accuracy” in the cost estimate.  The should-cost tool calculated a part cost of $105, but the part cost $142, making the tool is 35% “inaccurate.”  There are a number of reasons why there is a discrepancy between the two numbers that include estimator error, a poor PCM tool, bad data, or most importantly, commercial “noise.”  All of these specific reasons are beyond our time in this discussion. 

Although this example shows a 35% discrepancy, a much bigger error exists.   The error is not a tactical error in estimation technique or calculation; it is the strategic error of using the tool of should-cost itself with the wrong purpose in mind.    The error is the reliance on should-cost only as a DIAGNOSTIC tool, as opposed to a LEVERAGE tool to push the price or cost of a part down. 

Look at the triangle below.  Triangles are famously rigid structures in civil engineering that are hard to deform, and that’s why you will see them all over bridge designs.  On the top of our triangle is the quote your firm receives for a part or product, and on the bottom right is the should-cost prediction.  You would like to push the negotiated price in the bottom left to be the same as the should-cost estimate, but to do that the quote will have to change.  Most people have the expectation that the predictive power of should-cost alone will have the strength to shrink the triangle to the point that all three numbers are the same (i.e. the little orange triangle).  That is a great goal, but it is not typically realistic.  Often, the value of the should-cost estimate will not be used as a diagnostic, but as a lever to shrink the triangle to a lesser extent, as shown by the dashed line.

 

Why no one cared that Peter Lynch missed his estimates

Some people object to the idea that should-cost ought to be viewed as a tool for leverage, versus exclusively as a tool for prediction.  However, these people don’t expect the same level of fidelity in the tools and/or service providers that govern their personal finances as they do when should-cost is used in product development.  One of the most celebrated investors in modern history is Peter Lynch.  While running the Magellan Fund for Fidelity from 1977 until 1990, Lynch earned an annualized 29.2% per annum, beating the S&P 500 by an average of 13.4% each year!  Lynch used his own version of should-cost models – the investment folks call these “valuation ratios.”