Jun 032013

Numbers. They have such a comforting certainty to them, don’t they?

Words can be interpreted. But, numbers, they have that beautiful mathematical ring of truth. I was thinking about this the other day, when I got a number from a friend. I was helping him review a model he had made, and I asked him what the median result was from the model. He told me 16.42%. I ask him, “Do you believe it’s 16.42%?” He responded, “Yes, 16.42%.” This was a very smart guy, with multiple advanced degrees in engineering from a great school. However, the data set from which he was calculating this percentage came from a group of people who are giving him estimates of the money they had spent on certain activities, as well as data from an accounting system. And yet, he was quite positive that the result was 16.42%.  I.e., he thought that the result he calculated from the inputs had enough precision to generate FOUR significant figures.

Now, I’m sure that he would have realized, if he had sat down and thought about it for a second, that expecting this kind of precision when the inputs had virtually no precision of all, at least not the precision of four significant figures, was ludicrous. However, that’s the great thing about computers, especially when using spreadsheets like Microsoft Excel.  They will give you as much precision as you want. In fact, to what does Excel default… two significant digits behind the decimal point.

What I find really funny about this is that most engineers have learned the hard way, over time, that there is this thing called “tolerance stack-up.” In other words, no matter what you specify on a CAD model or drawing, a machine only has so much physical capability to hold that dimension. Therefore, engineers become very proficient at specifying tolerances. In recent years, they have even become much better at understanding the stack up of these tolerances on the final dimensions of a part. In fact, there are very sophisticated software packages dedicated to helping engineers do this.

In more general usage, Monte Carlo modeling became all the rage 10 to 20 years ago. Monte Carlo was an attempt to recognize the inherent noise in numbers that we measure, and how that uncertainty affects the models that we make, especially financial models.  However, the funny thing is that when it comes to calculating product costs, people ignore the precision question, and just assume they have the precision they wish they had.

Take a look at the figure below . Let’s go through a simple product costing in concept. For the part we are looking at, we first need to know the physical quantities that are used in making it. For example, we need to know the mass of the part, but that’s a tricky thing, because we have scrap and varying amounts of mass could be used up in certain processes. So, we might be +/-1-3% in our estimate of how much was used. Similarly, we need to know how much time is actually spent on each machine. However, this varies batch to batch, and measurements aren’t always so accurate. There may be many processes that make up the part, including extra inspections and re-work. Let’s say our measurement of the time it takes has a range of 5 to 15%.

Product Cost Management Ignorance is Bliss

Until this point in the analysis, at least we’ve been dealing with physical quantities, not financial quantities. But, if we move to financial qualities, the problem gets much worse. Even material rates are not such a certain thing. They move around over time with various surcharges for this and that from the different material providers. And, the number depends on what material is sent t0 what lines, etc. Labor rates and overhead rates are far more black magic. Accountants with green eye shades spend endless hours calculating these rates from monstrous ERP systems, using Byzantine Activity Based Costing allocation schemes. We hope that the allocated rates are accurate to the real truth on the floor, but I don’t think we can really expect them to be more than +/- 10-20% from what’s really going on.

Never fear though! At the end of the calculation, we have calculated that this particular part cost is $93.45. Why $93.45? Well, that’s what our spreadsheet model or our product cost management software told us. And, of course, a cost NEEDS to be within 10% of what we think the real cost is.

If the product cost management user actually calculated the tolerance stack-up of the uncertainties of the inputs that went into that cost, they would probably find that the costs are more than +/-10% from the true cost. If they seriously considered the possible precision, would they say the part cost $93.40-93.50? I doubt it. Would they say it costs $92.00-93.00? Nope . They probably would say that the part could cost between $88-$97. But, a range like that is not very comforting . It’s much more fun to hit that little “$” format button on Excel or cut & paste the number from the product cost management software .

It’s $93.45. That’s what it is. Because ignorance is truly bliss in the world of Product Cost Management.




  22 Responses to “Product Cost Management Precision… Ignorance is Bliss”

  1. Moderator re-posting a comment from a Linked-in group:


    George Spiller SAYS:

    Even if we can do a perfect job of projecting what a new product will cost, we still do not know whether the marketplace will pay enough for us to make a profit. As we adopt the
    lean approaches embodied in “The Lean Start-up”, we decrease the amount spent developing new offerings that the market does not want, by obtaining real feedback sooner.

    • George,

      Perhaps, my writing has atrophied in quality and clarity. I don’t see much in my article that has to do with pricing of a product to the end customer or decreasing time to market or the lean start-up. Maybe you can trace out the connections that you see between the article which is actually about: considering the inherent precision that is possible in a cost calculation, and the topics you seem to want to discuss?


  2. Moderator re-posting a comment from a Linked-in group:


    David Russell Schilling SAYS:

    I’m reading an interesting book “Numbers: The Language of Science” by Tobias Dantzig which Albert Einstein read and recommended highly. It talks about the origin of numbers, finger counting, finger symbols, multiplying with your fingers (really cool, search on Google to learn), base 10 coming from the number of fingers, and how if we evolved with only two fingers we may not have as much intellectual capacity and potential as a species to think and change things. It’s an amazing read so far.

  3. Moderator re-posting a comment from a Linked-in group:


    Ron Giuntini SAYS:

    Great post Eric. I guess one of the challenges for professionals in our field of product/service costing is that we too often think we are so “smart” that we don’t even consider that the eloquence of being so precise in the outputs of our models results in us often being so inaccurate. The term that is used for such “arrogance” is “physics envy”; a desire of smart people to develop models whose precision will result in the same outputs of that which is found in the sciences.
    Keep up the good works in opening up forums on the destructive focus of our community on being precise, rather than accurate….guess it comes from our financial accounting roots

    • Hhhmmmm, maybe that is why I am immune. Having product development roots, I never encountered accounting formally until I was at Harvard Business School. I must tip the hat to HBS for really drilling us with the 9 fundamental principles of accounting, one of which was the difference between “Relevance” and “Reliability.” They were very insistent about thinking when you needed each and to balance them. It’s not an exact analogue, but relevance is more similar to accuracy and reliability is more similar to precision.

  4. Moderator re-posting a comment from a Linked-in group:


    Paul McMahon SAYS

    Product cost is important and where the numbers came from is important. At a conceptual stage, the allowable tolerance is +/-50%. However, actual values then need to be put in as the requirements are firmed up. A capability/assurance module also needs to be added (depending on risk and value) to allow for any surprises that can occur.

  5. Moderator re-posting comment from linked-in group.


    Steve Walter SAYS

    Many bloggers and companies seek to increase their search engine rank by trying to get their web pages linked from as many sites as possible. It was once possible to comment on an article posted on a popular site such as the Wall Street Journal or CNN and include a link to their, i.e., the commenter, site. The search engine would then treat the comment as a bona fide link from the popular page’s author, rather than a commenter link. This in turn would cause the search engine to increase the ranking of the commenter site as a desirable resource. I am told this is no longer a success-oriented strategy because search engine algorithms are getting smarter with time. Thus, you still see comments with links to unrelated topics and sites.

  6. Moderator re-posting comment from linked-in group.


    Franck Ramaroson SAYS

    This is all about culture. In our daily life we accept to state uncertainty around the price of an item we would want to purchase. For example, if I would want to buy a computer with a certain number of requirements, I would make some market investigations. In any case I will come up with the statement that the price will be between xxx and yyy. I will set up my budget based on this range!

    So why isn’t it the case in business? I think that there are two reasons. The first is the engineer’s tendency to be precise in his calculations. When we learn about physics and mathematics, our evaluation is based on our reasoning of course but at the end the level of precision we come across is important. The second reason is the decision-maker ability to deal with uncertainty. Would he like a statement such as
    – “this project will cost xxx with vv% confidence, given that…the minimum would be mmm and maximum MMM”
    – or “this project will cost xxx according to our estimation”?

    • @Frank

      True. The difference in physics is that physicists actual spend significant time quantifying the uncertainty in their calculations. They know the numbers are uncertain beyond certain percentages.

      If I were the decision maker, I would rather have the former “this project will cost xxx with vv% confidence, given that…the minimum would be mmm and maximum MMM”

      The only time I want the later is when someone is contractually signing up to the price. And, to be honest, I would still want to know the uncertainty in their calculation. I don’t want them getting half way done and then extorting more money from me to complete the project… or cutting corners on quality and schedule to meet the price!

  7. Moderator re-posting comment from linked-in group.


    Gerry Gerber, CR • This discussion really hits home with me.

    Having been in the home improvement industry for 40 years as of May 23rd, a lot of numbers have crossed over my desk.

    What amazes me is the time that is spent on bids, based on books, based on general scenarios that have little or no accuracy built into the assumptions, yet, all of the folks in the remodeling industry WANT pricing estimate software programs to speed up the process of their inaccurate estimate?

    We all need to remember that life is really too short to not step back and look at numbers for what they are,,, an opinion of cost, at least in the “bidding” arena.

  8. Moderator re-posting comment from linked-in group.


    Marcel Hoks SAYS:

    What’s funny about the article is the assumption of the percentages taken into account. Isn’t that the bases for the discussion: assumption? 🙂
    Who was it that stated: “Assumption is the mother of all f%$#@-ups!” (Google result: Mr. Eugene Lewis Fordsworthe).
    Anyway, It’s indeed interesting how numbers can influence our thinking and above all our common sense! Maybe it is in the human blood to get blinded by the thirst for result or solutions…

  9. Moderator re-posting comment from linked-in group.

    Craig Tallar SAYS

    Costing Software performs a good “check,” however, other understanding are missing when viewing from a manufacturing side of part tolerances, relationships, vertical to horizontal machine spindle, reach, stock, and other concerns the ‘software’ cannot ‘calculate.’ Number are more factual. Yet can be cheated to direct what is ‘envisioned’ to achieve the results sought. One will find the answer, after on is build and the final costs are in!

    • @ Craig – I would say that is not deficiency in the software per se, but in the model. If the costing model was written to include the example variables that you reference, it would be fine. It’s always a balance: How automatice / easy / user friendly do you make a model vs. how much ‘accuracy’ to you want.

      But, as we discuss in the article, the bigger question is, how much precision do you really need to make a good decision?

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