Good afternoon operational improvement afficionados!
This week our managing director Eric Hiller published another piece about operational improvement and how to bring principles from Lean, Six Sigma, and VAVE into the discussion, specifically when engaging executives in an operational transformation.
Please see more here!
Hello operational improvement fans!
Apparently Eric hiller is cheating on us these days with his own personal website (www.eric-hiller.com). But, we are still happy to pass on his work to you. He just wrote a new piece for medium.com called:
Eric Hiller Provides Operational and Process Improvement Tips
This article is targeted toward executives and high level consultants that are trying to affect a process transformation in their organizations.
Certainly there are 1001 ways to fail in a process transformation in the organization, but in this article Eric’s only going to focus on the top ten (well, 11). On the other hand, if you get these 11 right, you probably will avoid 90% of the pitfalls!
Anyone who has ever heard the famous NPR show the Prairie Home Companion will smile warmly, remembering warm and disarming voice of legendary storyteller Garrison Keilor talking about the fictitious Minnesotan town, Lake Wobegon. Garrison’s sign-off to the show has entered pop culture: “And that’s the news from Lake Wobegon, where all the women are strong, all the men are good looking, and all the children are above average.”
We know of another place called Lake Costbegone. It’s a magical land of companies tightly clustered around a lake of profit. Lake Costbegone is the vacation spot of Product Cost Management. Lake Costbegone (and maybe many other corporate disciplines besides Product Cost Management) are similar to Lake Wobegon.
That’s right. At Lake Costbegone ALL the companies are, at least, average.
The post that we put up a couple days ago (Is the View Worth the Climb in PCM?), showed the effect on a company’s product cost, based on whether a company is best in class, industry average, or a laggard at Product Cost Management. The splitting of the companies into these three categories is almost universal in Aberdeen research reports, and other analyst firms use a similar framework, too. However, we don’t think we had ever met a client or potential client to that thinks that they are in the laggard category.
Sure, there are people that are more realistic and honest within each firm, who will tell you “off the record” that their organization is doing very badly at Product Cost Management, or whatever corporate initiative we are talking about at the time. However, no one wants to proclaim in the sight of others that their organization is a “laggard.” Apparently, admitting that your organization is not, at least, average is the corporate equivalent of a stock analyst giving a sell signal. It’s just not done. Stock analysts typically give only three signals: Strong buy, Buy, and Hold. No one really knows what “Hold” means, but we are all pretty sure it means, “You might wanna think about dumping that stock.”
Being “industry average” might mean exactly that, the organization is industry average in whatever technique on which the firm is evaluating themselves. However, they could also be a laggard in need of great improvement, but just don’t want to admit it.
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The funny thing about the post from a couple days ago is that the gap or potential between industry average and best-in-class companies is actually *bigger* than the gap between the laggards and the industry average (see figure to the left). Therefore, if you are in the industry average, you should be quite excited about getting to best-in-class, because there is a big carrot to do that.
Our opinion is that companies are better off when they mistakenly consider themselves laggards when they are really industry average than when they consider themselves industry average when they are really a laggard. The industry average designation is much more of an invitation to apathy in Product Cost Management. No one wants to be the laggard, and that’s a good thing! What’s the worst thing that can happen, after all? If you misclassify yourself as a laggard and you actually are the industry average, your effort to get out of laggard state will probably move into being best-in-class.
And that doesn’t seem like such a bad thing.
We spend a lot of time thinking about how organizations can improve Product Cost Management. After all, it’s our job at Hiller Associates, but we’re also very passionate about it. We’ve often wondered, why is it that there are so many people in Product Cost Management who are very intelligent and hardworking individuals, and yet the field, in most organizations, does not advance.
Why is this?
We have concluded that one of the biggest problems is that most Product Cost Management Experts are independent acoustic live performers.
What do we mean by that ? Well, if you go into the average product company and meet the Product Cost Management organization, it usually consists of a very small group of experts. They typically are sequestered in some back office. They appear to be a covert operation of some large organization, such as purchasing. When you meet them, they are almost always hardworking people , who looked frazzled, but still have their noses to the grindstone. They are busily trying to avoid product cost before launch and wringing cost out after the start of operations.
Traditional PCM experts are like solo classical musicians. They improvise solo (excel spreadsheets) or play an expensive instrument (an expert tool). They play for command performances before the nobles. In this case, the noble is whatever manager is in the most desperate trouble at the time. The PCM guys are always overworked, but their solution to this is to work harder. Just like a classical live musician, they can only be at one place at one time. Their performances are beautiful to listen to, but there is no recording, nor is there a broadcast, so that others in the world can hear the wonderful music they make. They really are a solo act.
We show this on the diagram below by showing the simple sine wave representing the music they sing. Pound for pound, person for person, no one can save more cost than these soloists, singing their song live and alone. However, as with any organizations that relies on people to scale, it can all only scale so large, and it can only scale so fast . That is why professional services companies are typically very small. The growth of the company is limited by the expert resources they can find. Think of this versus a product company, where once the product is designed, it can be replicated very quickly through the magic of manufacturing.
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It’s time for product cost management groups to stop being solo live classical musicians and crossover, as they say in the music biz, to be rock stars. On the diagram to the right, look at the traditional path vs. a maximum performance path. It’s time for PCM experts to spend less time playing alone and move to being Rock Stars (and maybe the director of the band). In this arrangement, the musician continues to do a lot of what he does today. He composes and produces the music. The music itself is the technical expertise needed for product cost management, but the expert should be sharing it with the entire organization, not just a few people in solo performances. This requires that he have a *vision* for Product Cost Management. This is not a vision for how to cost model the next part or assembly, but where the organization is today and where he wants it to get to in the future.
The key to success is to amplify the music made by the Product Cost Management expert. To do this, you need to find the right management champion. Management is an amplifier, because their job is to receive the good ideas that their people bring them and then boost the signal on the idea to the rest of the organization. Management also parses the signal to the right speakers in the organization that can most beautifully and powerfully and produce that signal. Think about a modern 5.1 or 7.1 home theater system, where the amp or receiver parses the signal and sends the right frequencies to the right speakers.
And, if you’re going to be a Product Cost Management rock star, you want the biggest and highest quality amp you can get. You would be pitching your vision at the VP or C-level. Remember the movie Spinal Tap? You want the amp that goes to 11!
Every rock star is going to both tour and record. The management amplifier lets you to play to stadiums full of people. But you also need to record it, so that your fans can hear it over and over. To generate maximum profit for the organization, the fans (engineering, purchasing, manufacturing, etc.) needs to be able to execute on your PCM vision. Many times that music will need to play when you can’t be there. You record by (1) changing the culture and (2) designing a PCM process that the organization can follow.
The rewards to the organization when the PCM team moves from live classical performers to rock stars are very enticing. Although the results of the individual product cost manager experts will certainly be smaller, the rest of the organization now is producing results as well. Together, they will produce many more cost savings and far more the cost avoidance than the Product Cost Management expert could do alone.
We realize that moving to the rock star model will initially be uncomfortable for some people who are experts. It’s hard for experts to let go of control, especially on a complex set of activities like Product Cost Management. There will be mistakes by the organization. There will need to be teaching. The system may be chaotic at first. That’s OK. This is the only way to get to a better state. It also means that the individual product cost expert will have to spend LESS time actually producing results on his own. His time needs to be used developing vision, casting vision, teaching, strategizing, and leading the organization. He doesn’t have to compose that vision and record it alone. His executive sponsor can help get him some great song writers and producers, both internal to the organization and through external consulting partners. And the executive champion will also fund these resources.
Therefore, it is critical to find the right management sponsor who understands the benefits of moving from a solo live performance model to the recorded rock star model. The management sponsor needs to have the authority to reduce the individual PCM demands on the expert. The expert must produce less individually so the organization can produce more as a whole.
Sadly, looking back at my time as a CEO and then the Chief Product Officer at a company that made Product Cost Management software , and in my current roll as a strategic consultant, I have never seen this rock star transition be driven by the musician (the Product Cost Management expert). Every time I’ve seen organization move the needle on Product Cost Management, the impetus for that change was an executive sponsor who had a vision for a better world. The executive sponsor (typically in engineering, purchasing, or a product owner) was poking his nose into the world of product cost, sometimes knowing very little about it. Paradoxically and sadly, often the existing Product Cost Management organization, instead of being grateful for the help and wanting to get made into a rock star, was resistant or even resentful of the help. That’s too bad, because rock stars make a lot more money than classical musicians, and often have far better job security. (People are going to pay to see Aerosmith until they die.)
So, my advice to you is that if you want to become critical to your management, be noticed in the organization, see your organization produce far better results, and get rewarded for doing it, it’s time to stop playing acoustic solos live.
It’s time for you to become a rock star.
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%.
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.
In last week’s post we talked about where Product Cost Management sits in the organization . We concluded that Product Cost Management lives in a weird no man’s land between purchasing, engineering, finance, and manufacturing. Because the area is a wilderness, we used the analogy the people seriously pursuing Product Cost Management in companies are similar JRR Tolkien’s legendary Rangers in the Lord of the Rings trilogy . The Rangers go about doing good and benefiting the general public, even when the public does not recognize the good they are doing. Sometimes, the general public even considers these solitary trackers and warriors as meddling, or even, sinister. We even compared the best product cost management folks to the most famous of all Rangers, Aragorn, son of Arathorn .
Several people wrote us about this article, very pleased with the analogy comparing product cost management people to Tolkien’s Rangers. They also validated our assertion that Product Cost Management in the organization, lives between other major functions. We must say that EVERYONE was on board with the post and feeling very good about it.
This week we’re going to burn through all that good will and make everybody angry!
We’ll do this by explaining why people from every one of the major functions in a manufacturing company are ill-equipped for Product Cost Management. Are we doing this for the schadenfreude* of internet lulz? No, we’re doing it because we believe these paradoxes are true. These are the unspoken but often thought, truths that need to come to the light of day.
*For a PG-13 musical definition of schadenfreude from Avenue Q, click here.
It’s unfortunate we have to say this, but we’re not embarrassed of it either. First, one disclaimer:
The statements below are obviously generalizations of the functions within the organization, as well as of the people of that make up those functions. Throughout our firm’s long experience in industry with Product Cost Management, we have met many individuals within each of these functions that do not fit the stereotypes below. However, the paradox below truths hold in general. Any resemblances to any person, living or dead, is purely coincidental.
The short answer is, that engineering really doesn’t care about product cost that much. Product cost is a distant second or third , or maybe a fourth priority, compared to other product attributes such as time-to-market, quality , or performance. We say this despite the fact that we have data of our own, as well as data from other analyst firms, that show that when asked about product cost, product development executives will prioritize it near the top (usually 1st or 2nd). However, our experience in practice is that when the rubber meets the road, product cost is not the first or second priority. On a personal level, the paradoxical thing is that engineering is actually better equipped than almost any other function to do a good job at Product Cost Management.
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The reason for this is that a major challenge of Product Cost Management is linking the physical characteristics of a part (e.g geometry, features, mass , time to produce the part, etc.) to the financial (dollars and cents). Engineering lives and breathes the physical world. Engineers are trained to understand the physical world and to control it from the very first day they stepped foot into engineering school . They’re not afraid of the physical world . The problem is that product cost, despite the statements of most engineering executives, really is one of the last priorities to address when you’re in the middle of a product development program.
Finance relationship to PCM is the exact opposite of engineering . Finance DOES have the incentive to control product costs. In fact it, it’s their whole world. The problem is, most finance people are not from an engineering background, and are, quite frankly, terrified of the physical world of 3D CAD , features , and even if the manufacturing floor. To them, it is very uncomfortable to leave the safety of dollar numbers on an excel spreadsheet. They are also often hampered by the accounting classes they took in college. Specifically, Financial Accounting thinking has come to dominate the way they perceive Managerial Accounting in a way that is wholly inappropriate. Accounting , in reality, has a backwards looking allocation-of-cost viewpoint, rather than the forward looking predictive cost paradigm, which is needed for product cost management . The problems with the current accounting paradigm are certainly worth a future blog post, if not magazine articles or whole books !
Purchasing often suffers from the same malady as finance. They don’t understand the physical world very well. Many buyers also have a bit of a multiple-personality problem when dealing with product cost. On one hand, buyers are suspicious that the supplier is not telling them the truth and charging them too much. On the other hand, if a Product Cost Management person or another should-cost source provides the buyer with a product cost for a part that doesn’t match with the supplier gives them, the buyer often immediately concludes that the should-cost (not the quote) must necessarily be wrong . Riddle me that? They also have a a commodity worldview. It’s more beneficial for them to focus on large groups of parts within a commodity, as opposed to single parts within a product that is being developed. Finally, the incentive of RELATIVE cost reductions (i.e. “year over year” cost reductions) sets up a very bad dynamic with Product Cost Management. PCM is first focused on making sure the product comes to launch AT the right cost, rather than reducing cost year over year later. All these topics are worthy of extensive articles, in and of themselves, but that must wait.
In some ways, manufacturing is probably currently better equipped to deal with Product Cost Management than anyone else in the organization . Manufacturing people are usually comfortable with the physical attributes of the product, just as engineering people are (although they do not have the depth of knowledge in this respect that engineering typically does). Manufacturing does care about cost, just as finance does. They also have a practical nature like purchasing and are quite likely to be comfortable dealing with suppliers. However, there are PCM challenges and paradoxes for manufacturing, as well. First of all, due to rampant outsourcing in most organizations, the only manufacturing left in many companies is final assembly. Therefore, the manufacturing guys are often absent from the PCM ballgame. Their concern about how they’re going to assemble the parts together for the final product, not how to make the parts. Secondly, manufacturing is a very busy place, concerned with the here and now and fighting fires, rather than more strategic pursuits such as Product Cost Management.
So, we’re all in a bit of a pickle functionally with Product Cost Management. The table to the right gives a summary of the paradoxes we face functionally. It also adds one global problem that we talked about last week, which is that PCM doesn’t really fit nicely within any of these functions.
Given these structural problems in the organization’s functional cultures, is it any surprise that most companies struggle with Product Cost Management?
What’s the solution? It’s probably too complex of a problem for one Silver bullet. However, hopefully in the next post we can propose at least one possible way to move beyond the organizational problems and paradoxes discussed today.
If you are a Product Cost Management person with an inner nerd like us, then you probably love and the Lord of the Rings trilogy by JRR Tolkien. One of the iconic characters in the book is the king in exile, wondering the wilds as a Robin Hoodesque type of character, a man named Aragorn. One of the things that makes this character so compelling is the fact that he, and his brothers-in-arms, the Dunedain Rangers, secretly wander the wilds protecting those who are blissfully unaware of the evil all around them.
Why do we love Aragorn, who goes by the nom de guerre “Strider” so much? It’s because Aragorn is unpretentious, self-sufficient, self-sacrificing, and yet dangerous and mysterious at the same time. Aragorn gets things done, even when those around him don’t realize it. And when those around him do get to know him, they are astounded at just how powerful, efficient, and clever he is.
Yes, Strider is a misunderstood man, as Mr. Butterbur, the bartender at the Prancing Pony, the inn at Bree says,
He’s one of them rangers. Dangerous folk they are — wandering the wilds. What his right name is I’ve never heard, but around here, he’s known as Strider.
Strider and the rest of the Rangers don’t really have a home, and so it is also with Product Cost Management in most organizations. It’s very rare to find Product Cost Management a department that is not a part of a larger organization. And, it is always seems to be the red-headed stepchild of that organization. No one really knows exactly who these guys are or what they do, except that “I think they know a lot about cost and manufacturing stuff.” Product Cost Management never seems to fit in with the organization in which it has been placed, and everyone is always wondering if it really belongs in another organization.
So where does product cost management belong in the organization? That’s a difficult question because Product Cost Management relies so heavily on information from four different organizations. In order to do their work of profit maximization, expert in PCM deep domain knowledge of the following:
These are very broad pieces of information that are flung across the organization. If we look at the figure above, we see that these pieces of information are hidden in the four main functions of a manufacturing company: engineering, finance, purchasing, and manufacturing. Product cost management, like the Rangers in JRR Tolkien’s trilogy, seems to live in the no man’s land or wilderness between these organizations, where few people from any of the four organizations are comfortable operating.
Why are most people so uncomfortable operating in this nexus? Well, that’s a subject for our next post.
Good Morning PCM world,
Another reader sent in questions with respect to the article 2012 revenues of the Product Cost Management market. However, this question was a little more broad:
Is there any difference between Project cost management and Product cost management from your your point of view?
That’s a very simple but good question. We had not considered addressing it before the question came in. The short answer is “YES!,” there is a big difference. The big difference is as simple as the two words:
PRODUCT vs. PROJECT
We have defined Product Cost Management before here as:
Product Cost Management – An agreed, coherent, and publicized system of culture/goals, processes, people, and tools following the product lifecycle, that ensures the product meets its profit (or cost) target on the day that it launches to the customer.
The definition of “Project Cost Management” is more murky. The wiki entry on Project Cost Management is less than satisfying. Here is the main definition portion of the entry:
“Project cost management (PCM) is a method which uses technology to measure cost and productivity through the full life cycle of enterprise level projects.[citation needed] PCM encompasses several specific functions of project management that include estimating, job controls, field data collection, scheduling, accounting and design.”
Other resources for a definition are Ecosys EPC, the Project Smart blog, Hard Dollar Software, and TutorialsPoint. Based on the knowledge from these sources, we would define Project Cost Managemenet as:
Project Cost Management – Project cost management is a group of techniques, including budgeting, forecasting/estimating, change control, field data collection, scheduling, accounting and design, and reporting that are used together to ensure that a project is completed at its target cost and on schedule. It is most often associated with the construction industry. In construction projects, it would include tracking of both project costs and the costs of the materials for structure being built. In the world of manufacturing, it would only include the costs of the project such as R&D and SG&A.
Note that in the definition we make a distinction between two very different industries: Manufacturing vs. Construction. In construction, we are most often making one thing — some sort of structure WHILE we are in in the midst of the project itself. In manufacturing, we are undertaking the project in order that we make many copies of a product in the future (when production begins). In manufacturing, we call the project, “Product Development,” including sourcing, testing, design, manufacturing planning, etc. In manufacturing, which is our primary focus on this blog, there is a fundamental difference in Product vs. Project cost management that goes all the way to the income statement itself.
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See the figure to above to understand the focus of Product vs. Project Cost Management on an example income statement for a manufacturing company. The question then probably arises in everyone’s minds: Do we need both and which one is more important? That’s beyond this article, but maybe we can talk about it further in the future, if there is interest. We’ve left you some clues to answer those questions yourself in the figure above.
In the meantime, somebody call the Project Cost Management guys and tell them they are infringing our acronym! Everyone knows that the *real* PCM stands for PRODUCT Cost Management!
There are universalities that seem to cross people and cultures, such as, it’s polite to say “please” and “thank you.” These universalities also occur numerically. For example, designs that follow the Golden Ratiopop up all over the world. Many other aspects of one group versus another may vary, but there are these universal touchstones that pervade the world. The same is true with companies. Granted, one might argue that one company simply is imitating another company and that is why they share a simple practice or the important of a certain number. We believe that this is, indeed, true in most cases. Still, there are a couple of numbers in companies that seem to arise independently in all companies. We are going to talk about some of those universal and independent numbers today with respect to Product Cost Management.
The great universal number in PCM is “10%.” I have met hundreds of companies over the years, both in consulting and when I was the Founder, CEO, and then Chief Product Officer of one of the product cost management software companies. Invariably, a meeting with a company will occur, in which one of the customers will utter the “a” word: accuracy. The dialogue proceeds similar to the following:
CUSTOMER: So, how accurate is your software? PCM TOOL COMPANY: What do you mean by “accurate?” CUSTOMER: Uhh, um, well, ya know. How ‘good’ is the number from your software? PCM TOOL COMPANY: Do you mean do we have miscalculations? CUSTOMER: No, no, I mean how accurate is your software to the ‘real’ cost? PCM TOOL COMPANY: What do you consider the real cost? CUSTOMER: Uhh, um, well, I guess the quotes that I get from my purchasing department from our suppliers. PCM TOOL COMPANY: Oh, I don’t know, because it depends on how close the quote is to the true cost of manufacturing the part plus reasonable margin. Are you confident your quotes are correct proxies for the true cost of manufacturing. CUSTOMER: Hhmmmmmmm… yeah, I think think so PCM TOOL COMPANY: OK, how close do you expect the costs from our PCM software to be to your quote [or internal factory cost or whatever source the customer believes is truth]? CUSTOMER: Oh, you know, I think as long as you are +/-10% of the quote, that would be alright.
Ding! Ding! Ding! – no more calls, we have a winner! The customer has uttered the universal expectation for all costs produced by a product cost management tool, with respect to the “source of true cost”: +/-10%
The universal expectation of customers of Product Cost Management software is that the PCM tool is accurate to within +/-10% of whatever forecast the customer considers the “true cost.”
This expectation is so common that you would think that every customer in the world had gone to the same university and had been taught the same expectation. Of course, that is not the case, but it is a ubiquitous expectation. How did this universal convergence of expectations come to be? We will probably never know; it’s one of the great mysteries of universe, such as, why do drivers is Boston slow down to 4 mph at the lightest sign of snow or rain?
The more important question is: Is the expectation that the cost from a PCM tool should be +/-10% of a quote realistic? To answer this question, we first have to ask: How truthful is “the truth?” The truth in this case is supposedly the quote from the purchasing department. The reader may already be objecting (or should be), because there is not just one quote, but multiple quotes. How many quotes does a company get? Well, that depends, but we all know how many quotes a typical company gets: THREE!
Three shall be the number of the quoting and the number of the quoting shall be three. Four that shalt not quote; neither shalt they quote two, excepting thou proceedest to three.The universal number of quotes that purchasing gets is 3, and they believe the “true cost” is within +/-10% of whichever of these 3 quotes they select as truth.
Do all the quotes have the same price for the quoted part or assembly? No, of course not. If they were the same, purchasing would only get one quote. So what is the range among these quotes? That is a fascinating question, one that I am currently investigating. So far, my research indicated that the typical range among a set of three quotes is 20-40%. That seems about right from my personal experience.
But, is the “true” price (cost + reasonable margin) contained within the range of the 3 quotes? Not necessarily. If we assume that quotes are normally distributed (another assumption that I am researching), the range would be much bigger in reality. For example, if we had three quotes evenly distributed with the middle being $100 and these quotes had a 30% range, the high quote would be $115 (+15%) and the low, $85 (-15%). This gives us a standard deviation that, conveniently, is $15. At two standard deviations (~95% confidence or “engineering” confidence), we predict that the “true cost” of the part is between a predicted high quote of $130 and a low of $70. This is a range of 60% (+/-30%). You can see this on Figure 1.
OK, but what about if we just source a single supplier. Well, there will be variance in this supplier, as well. This variance breaks down into two types: physical noise and commercial noise.
Figure 1 – Variance in the Cost Forecast from Quotes (click to enlarge)
Physical noise can easily account for a range of 20% (+/-10%) in the quote that a supplier might provide to an OEM. However, physical noise can be quantified and discovered. A supplier can share what routing or machine they are using. The problem is that Commercial noise is very difficult to quantify. How do you quantify when the supplier believes you hurt him in the last negotiation and now he is going to repay you for it, or that he needs your company as a new strategic customer and will underbid to get initial business? Worse yet, Commercial Noise is often LARGER than Physical Noise in the quote! How big is Commercial noise? That is difficult to say, because we can’t measure it very well, but from our discussions with purchasing groups, at minimum, Commercial Noise adds at least another +/-10% .
| Physical Noise | Commercial Noise |
| Comes from selection of different machines, routings. | Comes from market conditions, emotions, and transient conditions |
| Quantifiable in general by understanding the selections. | Very difficult quantifiable |
| +/-10% of the “factory average” | +/-20%+ on top of Physical Noise |
Supplier quotes are just one forecast of true cost. There are other forecasts the organization has.
What about those people in the organization with the most manufacturing and product cost knowledge? What is the noise in their estimates compared to a source of alleged truth, such as a quote. We are not sure, but we have asked another question about variance to these experts. When asked the question, “How close are you as a cost estimator to the estimates of other cost estimators in your company, people most often reply, “Probably +/-10-20% depending on the complexity of the part cost estimate or assembly.” So, we might say that the cost estimators have at least a 30% range of quotes themselves.
What about the historical costs in ERP? How “accurate” are they? There’s actually at least two problems with data in corporate databases. First, sometimes it is just plain wrong from the beginning of its life in the database. However, even if it is correct initially, it gets out of date very quickly. Material cost, labor rates, efficiency, etc. change. Go ask you purchasing buyer how close a re-quote of a current part that has been in the database for three or four years will be to the original quote. To give you an idea of the magnitude of this problem, consider these findings:
Variance in Different Forecasts for Product Cost (click to enlarge)
So, after all of the discussion of the variance within other cost forecasts, how “accurate” are the forecasts from a product cost management software? Well, if the internal variance among expert cost estimators independently estimating is 30%, the BEST the PCM tool could do would be +/-15%… IF it is controlled by experts. What happens when non-experts use this software? How much does the range increase? Who knows? Obviously, the more automatic and intelligent the PCM Tool, the less the added variance would theoretically be. But, is this added variance +/-5%, +/-10%, +/-20%? That is hard to say.
Regardless of the answer to the above question, the bigger questions are:
We know the answer to question 1: Be +/-10% of a my selected quote.
To answer the second question, let’s quickly review what we know:
| Source of the Cost Forecast | Common Variance Inherent in the Forecast |
| Range among 3 quotes | +/-15% |
| 95% confident interval (engineering confidence in quotes) | +/- (15%+15%) |
| Physical noise within one single supplier | +/-10% |
| Physical noise plus Commercial noise within one single supplier | +/- (10%+20%) |
| Internal range among cost experts | +/-30% |
| Best Case PCM Tool used by experts | +/-30% |
| Non-cost expert using PCM tool | +/- (30%+ 5%?) |
| Common [Universal] expectation of PCM Tool Cost Forecast | +/-10% |
Hhhmmmmmmm… Houston, I think we have a problem.
It just doesn’t seem that +/-10% is a reasonable expectation.
What can you do in your company to help reset these unrealistic expectations? There are three things.
Is this a painful realization? Perhaps, but you are already living with the situation today. It is not a new problem in the organization. If you don’t acknowledge the potential problem, you run the risk of misleading yourself. If you acknowledge the potential problem, you may be able to solve it, or at least make it better.
IndustryWeek.com has just published a new article authored by Hiller Associates title:
The process of product selection that people do in their personal lives (e.g. shopping on Amazon) is strikingly similar to the process of product development that people encounter in their professional lives. Interestingly, people are often better at making the complex decisions associated with product selection than they are at similar decisions in product development.
There are three things we can learn professionally from our product selection experience on Amazon:
To read the whole article, simply click on the link above to go to www.IndustryWeek.com, or simply continue reading the full text below.
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We just finished the biggest shopping season of the year from Thanksgiving to Christmas. A lot of people were making a lot of decisions about where to spend their hard earned money – mostly for the benefit of others with gifts. During that same period design engineers around the world were rushing to finish up pressing projects – and, probably as fast as possible, because they had a lot of vacation left to use, before the end of the year.
We make decisions every day in our personal and professional lives. But, do we make decisions the same way in both worlds? I don’t believe so. People might argue that decisions made at work involve much more complexity. After all, how much product development is really going on in most homes? However, a lot of product selection is going on in people’s personal lives. When considering complex product purchases, product selection starts to resemble product development in many ways. Let’s take a look at how people (including design engineers) make decisions when shopping (product selection) vs. how they make decisions in the corporate world (product development).
Consider the ubiquitous Amazon.com. Customers’ product selection experience on Amazon is overwhelmingly positive: Amazon scores 89 out of 100 in customer satisfaction, the top online retailer score in 2012. But product selection is *easy* right? Wrong. Look at Figure 1. Product Selectors on Amazon must consider multiple product attributes and, moreover, these attributes mirror the considerations of a product developer very closely. Product Selectors must consider performance, cost, delivery time, quality, capital investment, etc., without any salesman or other expert to guide them. But the really amazing thing is that the Product Selectors using Amazon are able to both prioritize these product attributes and consider them simultaneously.
CLICK ON PICTURE TO ENLARGE
So, how do the same people who are Amazon customers typically consider product attributes in the corporate world? Very differently is the short answer, as we see in Figure 2. First of all, people at work do not tend to trade-off product attributes simultaneously, but in series. Moreover, often each functional group in a product company (marketing, engineering, manufacturing, etc.), tends to be concerned with one dominating attribute, almost to the exclusion of other product attributes. How does the typical series-based consideration of product attributes that is common in the corporate world compare to the simultaneous trade-off approach that the customers of Amazon use? Exact numbers are difficult to find, but some sources say only 60% of products are successful. While not a precise comparison, the difference seems meaningful: Amazon scores 89 of 100 on the customer satisfaction index, whereas product companies have 60% successful products.
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Why is this? Don’t people get college degrees to be great product engineers, buyers, etc.? Don’t they get paid well to do these jobs? In contrast, most people have limited knowledge of the products they select on Amazon and spend hundreds or thousands of their own dollars to buy them.
There are at least three reasons why the product selection and product development processes differ, and the corporation can learn from all three.
Which product attribute is more important: time-to-market, product cost, or performance? There’s no right or wrong answer, in general, but there is a right answer for any given situation. The question is: does the product developer KNOW the priorities of different attributes. As an individual shopper, you may not explicitly write down the prioritization, but you know it. Your preferences and value system are welded into your DNA, so it is clear. However, companies are not individuals, but collectives of them. It is the responsibility of the product line executive to make these priorities clear to everyone.
This is similar to requirements engineering, but at a strategic level. Requirements are typically specific and only apply to a narrow aspect of the product. I am talking about the high level product attribute priority. Ask your product line executive: “In general, as we go through our development, what should typically ‘win’ in a trade-off decision.” If the executive cannot give you a concise and simple answer, he has some work to do to earn his big salary. For example, he should be able to say something, such as “We must meet all minimum requirements of the product, but we need to get to market as fast as possible, so we meet or beat our delivery date. Oh, and we need to keep an eye on product cost.”
The product executive needs to write the priorities down and share them with all. In this case, he might write:
This doesn’t mean the product executive will not change the priority later as the conditions change, but for now, the whole organization is clear on the priorities. This sounds very simple, but most people in product development are unsure of what the clear priorities are. Therefore, they make up their own.
The second thing that we learn from Amazon shopping is to consider all the constraints and targets for product attributes simultaneously. As we see looking at Figure 1 versus Figure 2, people naturally do this on Amazon, but organizations typically let a different priority dominate by functional silo. There are often arbitrage points (optimums in the design space) that will allow excellent results in one attribute, by only sacrificing minimally on another attribute. For example, the product executive may have said time-to-market is first priority, but he is likely to be happy to sacrifice one unit of time-to-market for an increase of 10 units of performance. This doesn’t mean that the organization is changing their priorities, but that the strategic priorities discussed above simply function as a guiding light that the product development team pivots around to find the point of maximum value for the customer.
Recent research is revealing the dangerous downsides of our always-on, always-new, always-more information society. To be sure, social media, like all technologies has the potential for adding a lot value. The question is: do you control the information or does it control you. The research featured in Newsweek shows three problems that have grown in importance over the last decades:
To answer this, let’s first ask how Amazon is able to overcome these challenge. To overcome the Recency vs. Relevancy challenge, Amazon ensures that recency is not the default option for the display of Amazon customer reviews. Instead, helpfulness of the review (relevance), as judged by other customers, is the default order. Amazon does not push immediacy. There are no annoying pop-ups offering a deal, if you buy in ten minutes. Certainly, Amazon does make buying easy and fast, but shopping at Amazon from the comfort of one’s home is a relaxing experience that promotes thoughtfulness. Finally, Amazon does not overload the customer with information. This is no small task, given that Amazon may offer literally hundreds of items to the customer among which he must decide. Amazon does this by presenting the information on a huge variety of products in a standard way, and by providing simple and powerful filters that discard large amounts of extraneous information.
In order to overcome these new information challenges in your own product development work, ask yourself these three questions:
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The world of online journals, social media, corporate social networks, and interconnected supply-chain applications is here to stay. It brings a world of new opportunity for better and more up to date information for product development. It also brings a deluge of extraneous information, and we need to accept this and learn to manage this. Amazon.com manages these challenges well. Your product development team can manage these challenges too using the principles outlined above.
