Too Important to Measure

“So, please join the movement to ban productivity from medicine. We are not producing anything. We are caring for patients who need our full attention.” This is the concluding appeal from “It’s Time to Ban ‘Productivity’ in Medicine,” by Robert Centor, M.D.

This type of rhetoric is designed to imply that anyone who disagrees hates people – or, in this case, patients. Often it is children or mothers or women in general. But the basic formula is a false dichotomy, where if you do things my way, you care for people; if you do anything else, all you care about is getting rich while harming others.

Profit is not the enemy; at least not any and all profit. “Profit” at its simplest is just a way of saying thanks that is tangible: the doctor gets paid for the health care.

Businesses today can be so multi-layered and convoluted that it’s easy to imagine the “profit” only means that some man in a suit somewhere far away from the real work gets to buy a new yacht. While this can be one of the outcomes, and we can agree for the sake of the discussion that it’s unfair, it’s not the simplest or most basic meaning of profit. In the simplest form, it means that the guy in the suit can pay the doctor for his work and not lose money. This is good, because if the guy in the suit loses money and expects to keep losing money he quits paying the doctor.

Then the doctor would need to get his or her money directly from you. And the doctor would need to be really sure that he or she is getting enough money to pay off the medical school debt, and also make all those grueling years of school worthwhile. It’s hard to be sure of that unless you get that guy in the suit involved again. Paying for the doctor’s schooling just makes this harder to talk about but doesn’t really change the facts: whoever teaches the doctor needs money, so if the patient who pays taxes to pay for the schooling to be provided for free to the doctor and pays more taxes to pay the doctor so that the actual doctoring is free – it’s just more complicated, but at the end, if the whole thing is not making a profit, it is losing money and will have to shut down.

There are big, hard to manage problems in health care in the USA today. And it’s a lot harder to measure whether doctors are doing a good job than it is to measure whether widget-builders are building widgets.

Those two truths do not justify this self-entitled appeal to “ban” productivity measurement in health care.

The complaints that Dr. Robert Centor has are basically the same complaints that everybody everywhere in every job has when their job gets measured. Measurement always introduces the possibility of perverse incentives. When you measure how many widgets the widget-builders make, they have a tendency to make more; when you emphasize the measurement of how fast they can make widgets, they make more at the expense of product quality, safety, and improvement to the product itself and the production process. Improper measurements of “productivity” were one of the major problems in American manufacturing that were called out by Toyota (and other Japanese manufacturers) when they overtook American car manufacturers in product quality and reliability.

Thus, the Toyota Production System never recommends measuring how many units are produced as a good measure by itself. At the most basic level, the Toyota Production System admonishes you to understand how many are actually wanted and not to build too many. Along with that, if the widgets you make do not work they do not count as “units produced” – quality matters. Furthermore, if you haven’t done your research to make sure the widgets do something valuable to your customers, anything you make is waste no matter how expertly you make it.

Transferred over to health care, the first thing we can observe is that measuring how many patients doctors see is probably the same as measuring how many junky unsafe cars factory workers can produce. It’s measuring the wrong thing. How much only matters if you are making the right stuff. So if we are going to learn any lessons from manufacturing productivity – any of the lessons on productivity and quality from the last five decades or more – we need to figure out how to measure whether doctors are doing the right stuff before we try to measure how much of it they do.

Measuring quality of care is a lot harder than measuring quantity of care, no doubt.

But even measuring quality of manufactured goods is harder than it sounds at first. Most of the cars sold in the world today don’t need to be able to drive any faster; a car that can go 125 mph is not worth any more than a car that can go 95 mph to most people. But a car seat that is comfortable for hours at a time is probably worth paying for. That’s harder to figure out, but it matters more for the real meaning of product quality (what customers are willing to pay for).

I’ve said it before but I probably can’t say it too many times. Measuring quality of care is hard. But think for a minute about the opposite. What if we don’t measure care quality at all, ever?

Well, if we don’t ever measure the quality of care, that gets us right back into pre-scientific medicine: “Sounds to me like you need to swallow some cat dung. Hope it works for you!”

Instead, although measuring care quality is hard, and we can’t do it perfectly, we need to measure care quality and keep finding new and more accurate ways to measure it.

But what about costs? Leaving aside the vast and unhelpful complications of the current health insurance system, if I go to Dr. Jones for corrective lenses and he prescribes glasses that adjust my eyesight to 20/20 and charges me $200, but (for science!) I then go to Dr. Smith and he prescribes glasses that also bring my sight to 20/20 and charges me $500, which is a better deal?

Okay, so the same work for less money is better productivity.

Tell me again why we shouldn’t measure productivity?

What we need to do is have continuing conversations about how to measure real productivity. Yes, there is definitely a possibility that measurements could lead to perverse incentives; managers need to recognize that and account for it. Managers who emphasize simple measures of “productivity” in factories will see quality go down, and DID see quality go down, and lost their business to competitors who paid more attention to quality. If you are a health care provider working for an administration that measures “productivity” only in quantity, the problem is not the measurement: it’s your management. And they will lose their business. (Provided they are allowed to lose it; which means they have to lose money if they don’t satisfy patients; which requires patients are allowed to choose providers whom they think give better care; but that problem is for another discussion.)

I was recently asked how I would apply Lean Six Sigma concepts to reduce patient visit time, if given the chance. Part of my answer was: who says patients want their visit time reduced? Most people I know want to spend more time with the caregiver and less time in the waiting room, so “reducing time” is a poorly-stated goal.

The root cause of the problem Dr. Centor is observing is not the use of measurements; it’s that the same interest group gets to determine limits on what the patient needs and how much the doctor will get paid for it. Insurance companies can limit what they will “accept” in billing, which effectively means what the doctor is allowed to do (to be paid). If patients paid directly, they would pay more to spend more time with the caregiver. Since the payers are managing by numbers, not by experience, they need countable things like tests prescribed; add that with a very natural desire to make sure you’re getting bang for the buck (which is, in this case, measureable health care per dollar of reimbursement), and presto! You now have an incentive to prescribe as many expensive treatments in a short period of time as possible.

Misuse of measurements will always be a risk, especially when money is involved. The right approach is not to stop measuring altogether, as Dr. Centor suggests, but to think carefully about what you measure and think twice as hard about what it means. Problems with measuring performance do not apply in a fundamentally unique way to health care providers; there are problems with measuring engineers, HR communications, and office workers in general; right on down through to factory workers. Managing by the numbers makes no more sense than driving your car by staring at the speedometer. You need the speedometer to keep your senses in check, but you need to stay aware of the context to know whether 45 MPH is too slow on the highway or too fast in a school zone.

In the case of Dr. Centor, his rallying cry was addressed pretty well by commentator David Pogge, who wrote in part: “However, the implied alternative appears to be a system based on the notion that every provider knows what is ‘optimal’ and their work will drift towards providing that optimal service if external pressures are removed. This idea is either self-aggrandizing or naive. Healthcare providers are human, and therefore they are as flawed, selfish, shortsighted, lazy, and prone to misjudgment as all other human beings. To think otherwise suggests that one has never actually worked with real people in a real healthcare setting.” People, whether patients or doctors or factory workers, cannot be managed well by numbers alone. But people, even doctors, need numbers to provide objective feedback. Sometimes the numbers will be misleading, and sometimes the numbers will be irrelevant; but medicine without measurement is just superstition. A doctor should know better.

Rushing to Fail (Part IV)

(This is the fourth post in a series; see earlier posts I, II and III)

Here we come to the most significant chapter of the saga.

The MRP system in place at the company at that time tracked three dates for a given order (more precisely, for a line on the order):

  1. Requested date, when the customer asked for it;
  2. Promise date, when the factory currently expects to be able to provide it;
  3. Due date, the date by which the work should be done inside the factory, used to sequence all of the factory work.

Due date is not necessarily the same as the promise date. First, if the factory was running behind overall, due dates could be missed. You wouldn’t want to move only one due date for one order into the future, because it would lose its place in line versus all of the other past-due orders. Also, depending on how the entire system is set up, the production control system that coordinates by due date might not include activities after assembly (transfer to shipping, pack for shipping, consolidate with other items on order, etc.), and in fact in this case the system did not track specific activities for shipping. So a one or two day gap between due date and promise date would allow time for shipping activities, or might be used to provide a small buffer in case of minor delays.

Promise date is not always the same as requested date, because customers can request things faster than they can be built – because of how much they want, or because of a long lead time to get a special component, or because the factory overall is already busy.

Given these three different dates, and the fact that all of them can be changed, what does it mean to be “on-time”?

Customer Request Date would make the most sense. But customers can ask for unreasonable things – they can ask for giant orders of specialized product to be delivered the next day. Orders came in by many means – by fax, by phone, or through an early use of the Internet called Electronic Data Interchange (EDI). Not all of those methods reliably required the customer to specify a request date; if no value was provided, the system defaulted to next-day.

So a significant portion of the request dates were quite out of reach.

Using Promise Date is no good because the promise date can be changed by the factory, so being “on-time” to promise date is a simple matter of updating the field before shipping. Promise date needs to be changeable by the factory so that an indication of what is expected to happen can be provided, but measuring that will only measure how reliably people can change the promise before delivering on it.

Therefore a modification to the system was ordered which stored the first promise date given, the Original Promise Date.

But it turns out that the factory more or less controls the generation of the first promise, as well, so before too long the Original Promise Dates were soaring out into the future, and the factory’s performance to Original Promise Date was improving.

What to do? Well, no problem in people management can be solved by measurement alone. But it’s pretty obvious that the right thing to do in this case would have been to accurately capture what the customer actually wants – the customer being the person willing to pay for what you can provide.

This factory with the on-time delivery problem was not a pizza factory. If someone called asking for pizza, that person would not be a customer. It was not a space ship factory, and if someone called asking for a space ship they would not be a customer. It was also not in the business of providing most products to most customers on a next-day basis, and so most people requesting that would not be asking for what the factory could provide; they would not be customers.

The basic steps toward measuring on-time delivery include knowing what “on-time” means, which means understanding what the customers you can reasonably serve are willing to pay for. That implies two basic points, and a third point follows along:

  1. Customer request date must be provided. It could be provided once and applied to an entire order, or provided for each line on the order, or the order could be held as “pending” until a customer service agent could follow up and obtain the information. There would be some expense to make the changes to the system. There would need to be some conversations with customers in the habit of getting next-day shipment at no extra charge, when available, merely by lazily doing nothing, that they now have to ask for what they want.
  2. For most customers in most cases, request dates that would be moderately challenging should require an added expedite fee. If the customer is not willing to pay for the service of quick shipment, they are not a quick shipment customer.
  3. If you charge extra for what your competitors provide for free, you will lose business. For important deals where an expedite fee would lose the business but it might be possible to provide the order in time, it may be appropriate to waive the fee. This would require diligent investigation on the part of the sales representative regarding what the customer actually wants, and equally diligent investigation as to exactly what the factory is currently able to provide. While this extra effort might seem unwelcome, it should be better for all parties than conversations about why delivery is late – and the intolerable frequency of those conversations was the basis for the whole improvement effort in the first place.

The best situation of all is, of course, to provide what the customer wants instantaneously, at no extra charge. But it is better to only promise what you can actually deliver than to take money for a service (fast shipment) that you cannot provide.

The growing power of Amazon compels a bit further discussion. Amazon got where it is today partly by providing lower prices than its competitors, including delivery. Amazon delivers faster than others, and often for free, and their prices are lower. Many of Amazon’s competitors figured they were not able to do this without losing money. As far as I know, Amazon’s never solidly disproven this suspicion; for years they’ve been so busy spending money growing it’s never entirely certain they’re making profit on their core distribution business. They’ve also muddied the water with the Prime membership program and it’s interestingly flexible definition of two-day shipping, and the possibility of quietly boosting prices for complacent, regular shoppers (hard to prove without having account access to a large sample of customers).

But how Amazon did it is largely irrelevant. If you are certain they subsidized money-losing shipping with investor cash and growth-hype marketing, go do the same. If you think they hide their shipping costs in a membership program, go do the same. Advertising “free shipping” when the shipping cost is baked into the prices is a well-known marketing ploy, and at this point convincing investors to pour money into a unprofitable but growing business is also well-known. In the end, whether the money is coming from end-user customers or investor customers, someone is paying; and whether you are providing actual shipment of widgets or dreams of getting rich off of a unicorn stock, something is being provided.

So, to insist: customers pay for what you provide. If they don’t pay or you don’t provide it’s not a lasting business.

The possibility of considering investors as customers leads us to another interesting wrinkle. It turns out that investors are the customers of every publicly-traded company. (What follows is just a quick review of the classic agency problem; skip five paragraphs to “From the lofty heights” if you don’t need it.)

The investors are represented by the Board of Directors. Directors can be replaced by a sufficiently large contingent of shareholders (investors). To keep their jobs, directors try to keep investors happy.

Directors must approve the compensation plan for the top management. They do whatever they can think of to ensure that the top management will take actions that make the shareholding investors happy.

Shareholders of any size can easily sell stock on any given day. Sell Company A, buy Company B. In general, then, shareholders have no reason to want Company A to do well over the long term. As long as the share price for Company A has increased enough to pay off any costs associated with buying and selling the stock, big share holders always can (and, in a sense, “should”) dump the stock for a better offer at any time.

So investors always want to know that, compared to other stocks with a comparable risk of losing value, the stock of Company A is doing really well right now.

That’s why publicly traded companies tend to want to have really swell results every month, and especially every quarter and at the end of every year. Most businesses have natural ups and downs; ice cream sells better in the summer than in the winter. Peppermint candy sells better for Christmas than for Independence Day. But publicly traded companies do whatever they can to overcome the natural ups and downs of their business, because if they aren’t doing great right now they might get dumped for some other company that’s doing a little better.

From the lofty heights of the stock market this looks like a jolly little beauty pageant. From the ground floor of a factory, it looks like deciding to ship the newer order for plain vanilla ice cream before the older order for vanilla ice cream with organic Oolong tea leaves sourced exclusively from certified fair-trade villagers in Nepal, because the donkey is lame in Nepal and the tea leaves are late and we can ship the plain vanilla order this month, making the profits in this month a little bit better. We could ship the older order for the organic Oolong vanilla two days from now when the tea leaves get in, and if we ship the plain vanilla now we will be out of vanilla for three weeks, making the Oolong order even later. Too bad; that “customer” will just have to wait, because the real customers are the investors and they want to see good profits this month.

In short, resources get borrowed from an older order that can’t ship in order to fill a newer order that can ship. There are many possible reasons why an order might be hard to ship – it requires special components, the customer wants the entire order to ship complete and other items on the order are late, the customer hasn’t passed the credit check, and more.

Clearly this violates the principle of first in, first out (FIFO), or in Toyota Production System terms, continuous flow. It also probably irritates you on general principle; nobody instinctively likes how it sounds. But, as they say, nobody wants to know how the sausage is made; but that doesn’t stop them from eating it. Very likely you will find some practices that make you irritated or uncomfortable behind every nice thing, particularly the nice things that seem remarkably cheap, remarkably convenient, or otherwise mysteriously available to you without any particular effort that you know about.

Let’s ignore the irritation factor. The problem with this scenario goes deeper than just making the organic Oolong vanilla customer wait longer than necessary. This kind of out-of-sequence activity causes rippling chaos that spreads far beyond the visible consequences when the decision was first made. Every part of the production process is designed to work in a basically first-in, first-out way; even if it hasn’t been adopted as part of imitating the Toyota Production System, than at least because it is awfully hard to build the order for five years from now since you don’t know what they are. At some level, you add things to your production plan as you become aware that they are wanted.

In our entirely made-up example of the organic Oolong tea vanilla, perhaps the tea leaves need to ferment, and they were planned to ferment next week when the tea leaves came in; but they can’t be fermented too long before being used, so if we aren’t making the Oolong vanilla until three weeks further out we’ll need to delay fermenting the tea leaves. But that will cause a conflict with fermenting the mint leaves for the mint that was supposed to run that week, so now we have to move that. And then we’ll have to reschedule the chocolate for the mint chocolate, and that will affect the schedule for the chocolate in the chocolate peanut butter; and so on.

It is of course possible to deal with these kinds of disruptions, because they happen whether you deliberately cause them or not. But it should be readily apparent that there is a difference between dealing with problems you tried to prevent versus deliberately causing yourself those problems. Dealing with one specific chain of events is not too daunting, but when the problems occur on multiple components for multiple products on multiple orders over many weeks, and the problems can affect each other, the consequences multiply. It’s not eight plus eight, it’s eight times eight.

The Toyota Production System principle of flow is meant, in part, to reduce those self-inflicted complications. Going from eight root-cause problems (eight times eight, 64) to seven root cause problems (seven times seven, 49) reduces your total problems by 15. Reality is more complex than that simple math, in good was as well as in bad ways, but the principle holds: problems multiply, and keeping things as steady and predictable as you can will make it much, much easier for to work on your real problems without being distracted by all the consequences of problems you caused for yourself.

The crowning irony for this particular company’s efforts to improve on-time delivery was the decision that had been made some time prior to designate certain customers as so important to the business that their orders would ship ahead of all others. Because these were by nature customers representing a significant portion of the total business, their orders tended to affect most of the products. If a particular product was running past-due and a production schedule drawn up to get the oldest orders down from two weeks old to two days old, and then just as the products went to shipping a priority customer order came in, that priority order might use up all of the product. The order could come in and ship out in less than a day, leaving everyone confounded who thought that the old orders would be caught up (the customers themselves, the customers service agents talking to the customers, the factory production planners, etc.).

The priority customers were also fairly likely to be major distributors who carried significant inventory of their own and might not need the product nearly as urgently as the smaller customers with older orders.

As already mentioned, production control software is designed to plan to build things basically in the order they were requested. Typical production software is designed to plan to produce in the future, not to explain why production ran a certain way in the past, so it was not particularly easy to tell why the product meant to ship on old orders somehow disappeared without clearing up the old orders.

And if the product was one model in a family with shared components, and a second production run was made after the first disappeared to really clear up the old orders, that might use up shared components meant for other orders. Again, the problem spreads in a ripple.

All of the issues discussed in this article are some form of rushing: accepting a next-day shipping “request” without checking to see if it is paying business; shipping out of sequence to boost end-of-period revenue; or shipping out of sequence to flatter a key customer (rather than investing in improving basic ability to ship to all customers faster). Although not possible to get an accurate measure on how big the ultimate impact of these rushing efforts were on overall on-time delivery (because production computer system plan future production action, not explain past production action), the principle of problems multiplying and the demonstrated success of the Toyota Production System (and similar philosophies, when rigorously followed) give a pretty good indication that the self-inflicted injuries were severe enough to justify stopping those practices.

Ultimately, to achieve on-time delivery, it is important to stop rushing.



For Want of a Nail (Part III)

(This is the third part in a series; see Part I , Part II and Part IV)

In the previous installment we saw how neither the human operators nor the computerized information system had a clear, timely understanding of what inventory was meant to be in a specific location or reserved for a specific purpose. The material handling processes in place did not conform to the principle of visual control (“mieruka”). Although the system was intended as a form of kanban, it did not conform to the principles of kanban because the role of the spare parts pickers had not been considered, and there was no visual feedback for them. This could also be considered a lack of mistake-proofing (“poka-yoke”), and potentially a lack of “5s”, specifically Sort and Set In Order, again from the perspective of the spare parts picker who had no means to distinguish parts available for shipment and parts reserved for production. It also should be considered a dangerously incomplete IT systems implementation of a process, but a reliance on IT systems to “make things work” is itself not understanding the principle or benefit of visual control.

Today’s episode has to do mainly with leveling (“heijunka”). Leveling is always a sore point in implementing a Toyota Production System based process because it is in direct tension with the principle of responding to customer demand. There isn’t any case where customer demand is level and unwavering; even for oxygen, although we are always breathing, as we need more oxygen when active or excited than when resting.

But leveling is fundamental to quality, or more specifically to being able to observe whether results are in line with expectations. If you expect your production line to produce 100 units every day, all of the workers should be working at the same pace every day, and you should minimized if not eliminate mistakes caused by rushing. Further, without having a standard pace for the entire process, it is all but certain that some parts of the process will be able to operate faster than others, and the faster steps will accumulate work in process behind the slower processes. The extra inventory allows the faster process to “hide” errors by recovering while the slower process catches up, a short-term success that obscures the potential for small problems to grow into big ones.

In this particular factory, leveling production was made difficult by the large number of different end products, some of which had constant demand (although varying in total volume) and others with only occasional demand. If the occasional-demand items would politely take turns the production could be leveled and still tied directly to demand, but of course this serendipity was not reliably present.

So the basic system for moving components from storage to the production line relied upon a crew of material handlers to monitor several assembly lines and restock all of them as needed. Most materials we provided via a “two-bin” system: in concept, you start with two full bins. When the first is empty, it is taken away and refilled before the second is used up. (Sometimes more than just two bins are used.) Because the bin quantities were not all aligned to have enough parts for the same number of finished products, and because some parts were used in common across several end products (but other components were not), the rate at which parts would need to be replenished was not reliable. A change-over from assembling one product to another would mean refilling many bins simultaneously; if several lines needed to change over at around the same time, work might back up considerably.

Further, since production lines might build a number of different products and not all were built equally quickly, and not all lines were always producing, there was drastic variation in the level of support needed from material handlers. At the end of the month, and especially at the end of the quarter, pressure to build as much as possible went up sharply.

To compensate for the changing work load on the material handlers, the more senior members of the assembly team were also authorized to retrieve components from storage. When the urgency to maximize production was greatest, production planners (typically responsible for balancing available component parts with current final product demand, a desk-based job) would assist in moving components to the line so that none of the potential builders would lose time moving parts.

The production people were trained, expected, and performance measured in terms of production of complete products. Precision in counting and handling component parts was not part of how their success was evaluated in any direct way.

When parts arrived at the last minute, material handlers (full time or temporary fill-ins) would retrieve the parts directly from the receiving dock, before they had been counted, quality checked, or received into the system at all. Combined with the other uncertainties afforded by the process, the question of how much of an item was available and where it was stored was always unclear.

Several component parts were springs, or spring-like items, which could easily become entangled with one another. These parts, and all small, lightweight parts, were shipped in bags or boxes. Taking parts out of storage, or out of a bin during the assembly process, is very likely to involve pulling out more parts than desired; disentangling was not a straightforward process, and it could be expected that one or more parts could drop off, roll, or bounce into places unknown. These were always small, cheap parts; when pressure was on to build, build, build, it hardly seemed worthwhile to spend time chasing runaway parts. There’s always tons more in the bin.

Ultimately it was not clear how often dropped parts caused shortages versus parts not ever being shipped. Most small, light parts were shipped loose packed in bags or boxes and the count of pieces in each bag or box could vary. The suppliers would write on the box the count, but there was no routine verification by weight. Checking by weight as parts were removed was complicated by the light weight of the parts; they weighed little enough that plastic or cardboard would count as significant number of parts.

It would be relatively straightforward to establish the weight of the parts, establish a minimum stock by weight, and write off the continual shrinkage due to dropped parts or undetectable short shipment. But the parts were bought and tracked by each, and the each-count was always off, and so production was halted for small, cheap parts as often as it was for large expensive parts.

Better than allowing dropped parts and potentially short shipments would be designing purpose-built containers using rods or grooves to keep parts in a consistent orientation, clearly marked with a weight corresponding to an exact count. While it would require a modest investment to design and produce the specialized containers, and possibly working with the supplier to help establish a reliable process to transition the parts from their production equipment to the containers, the payback in reduced uncertainty would have paid back such costs.

For want of a nail, the shoe was lost;
For want of the shoe, the horse was lost;
For want of the horse, the rider was lost;
For want of the rider, the battle was lost;
For want of the battle, the kingdom was lost;
And all from the want of a horseshoe nail.


Reservations Regarding Inventory (Part II)

(This is the second part in a multi-part series. See Part I, Part III, and Part IV.)

One of the most frustrating, recurrent problems that would cause late delivery at this company was a part shortage on an assembly line because the parts had been shipped out as replacement spare parts.

This was not a true root-cause problem because if the total count of parts on hand were accurate, the most harm that could be caused would be a slight delay as parts were moved from one place to another. But, through a combination of several different system configuration decisions and limitations, it was quite common for the same item to be stored in more than one location, and quite common for the location-specific inventory count to be wrong even if the the total count were right, and quite common for the system to indicate that inventory should be taken from a place where it actually no longer was.

How did it get so bad?

The simplest way to provide component parts, widgets let’s say, for assembly into a finished product (gizmos) is to keep large quantities of widgets on the shelf and pull some out of inventory when you need to build a gizmo.

The Toyota Production System teaches that it is not good to have widgets sitting in boxes on the shelf. There are many reasons to consider this wasteful – the extra time it takes to put things up on the shelf in storage and then get them back down when needed, the overhead costs of paying for the floor and roof and shelving for the inventory, the risk that at some point the design of the gizmo will change and the widgets will no longer be useful, and so on. American business managers will usually mention the cash tied up in the inventory that can’t be used for other purposes; I consider this is the least important reason from a Toyota Production System perspective.

Under the Toyota Production System, the worst thing about having many widgets on the shelf is that they will allow you to continue on as if nothing is wrong even if any number of things go wrong: your customers order more than you expected, you break more than you expected while trying to use them, your supplier is later than expected, and so on. A problem you don’t notice is a problem you don’t fix. Since inventory will cover for almost any problem, it encourages people not to fix any problem–it makes it difficult to tell that there is any problem at all.

It would be best if the widgets appeared exactly when needed, and no sooner. Reality being what it is, nobody has managed to apply this theory throughout their entire supply chain. But, if you want to be like Toyota, one of the first things you will do is direct your factory to use a “pull” system rather than a “push” system.

A “push” system is like wood in wood chipper, gravel on a screen, water in a tub, or paper in a paper shredder. The work gets loaded on in a big batch and you try to get through it as quickly as possible. Your job is to get rid of the work and the faster you do it and the more you do the better job you have done.

A “pull” system is a bit like a vending machine or a grocery shelf with a spring loaded pusher. Right up in front, clearly available and ready to take, is one item; as soon as you take it another one appears. Of course in a vending machine the whole load is put in all at once, but in concept a “pull” system has exactly one of everything ready to immediately replace one of whatever is taken.

It is impossible to have a perfect end-to-end pull system in a world where there is weather and friction and, ultimately, time. But as an ideal concept it is a great reminder that making more than is wanted is waste. Make exactly what is wanted, when it is wanted, and no more.

The conventional, “common sense” way to run a factory is to order 1,000 widgets (the widget factory makes them in batches of 1,000 and you get a better price per each if you order in that quantity) and put them on your shelf. When you want to make 50 gizmos you create a production order and 50 widgets are taken off the shelf and brought over to the gizmo assembly line, and then the gizmo assembly line tries to build 50 gizmos as fast as possible. It is a “push” system because the assembly line reacts to having inventory dumped on it by building as fast as possible.

In an idealized “pull” system, there is one finished gizmo sitting at the end of the line. The last worker on the assembly line has an almost-finished gizmo, and each of the other workers has a gizmo in a successively less-finished state. When a customer orders a gizmo, the finished one is picked up off the end of the line and handed to them (or shipped to them). As soon as the finished gizmo is picked up off the end of the line, another gizmo is immediately finished and delivered, and every in-process gizmo moves forward one step, including the step where the widget is used.

To approximate this ideal process, you can store the widgets right there on the assembly line so that the widgets are removed from “storage” one at a time, by the worker on the line, as they are needed.

Production control software was traditionally not designed around that kind of thinking. Production software is used to consuming all of the component widgets when the order to build gizmos is first released. Clever people came up with a work-around whereby the computer system would be told when a complete gizmo was finished, and since a gizmo was finished the system could then correctly infer that one of everything that goes into a gizmo must have been used (including one widget). Rather than consuming the inventory in advance, the system effectively backtracks to correct its own records of how many widgets are still on the shelf. (“Backflushing” is a common term for this backwards flow of information.)

Now, all that was just to set the stage for one of the more interesting problems that came up. Some years before I had become involved, the company had decided that widgets needed as replacement parts should be shipped from the factory making gizmos, rather than from a separate spare-parts warehouse. Why keep the same stuff in two different places? Why ship twice, first to the warehouse and then to the customer?

But in this factory’s version of the “pull” system, widgets were moved in small batches from storage to the assembly line, to approximate as much as possible a one-piece pull system. Since it wasn’t literally a one-piece flow system, sometimes there were more parts in the bin than would actually be needed. On the other hand, for larger quantity builds, the bins would be refilled several times from stock. The computer system was only told after the fact, when all of the gizmos were built, to remove the corresponding number of widgets from inventory.

So when a customer wanted a spare part (or two, or ten, or two hundred), and when they didn’t find the parts in the warehouse, the parts picker would go to the assembly line and take the parts. Then the assembly line would run out of parts and not be able to finish making gizmos.

Fundamentally this was an inventory accuracy problem. The production control system was still checking to make sure there was enough widgets in total to meet all of the needs. But, because it was neither a true one-piece flow system nor a conventional “push” system where all the inventory on the line was truly committed for a production build, it was never visually clear to a parts picker which parts were “really” needed for a build versus just moved to the line to follow the rules of the “two-bin” system.

That it was not visually obvious to the spares parts picker is an immediate red flag from a Toyota Production System perspective. But the “Lean Manufacturing” improvements had been implemented for manufacturing, without consideration for the spare parts process. Basic problems with inventory control were amplified, both in terms of the actual physical effect but even more importantly in the frustration and ill-will the misalignment of processes caused between assembly workers and spare parts pickers. With neither clear visual process control nor up to date and accurate transaction records, it became impossible to tell where the problem started.

The whole mess was a combination of problems, beginning with the batch-based rather than one-piece backflushing, compounded by the keeping inventory in more than one place, and complicated by shipping spares out the same facility and inventory as production. But it all could have worked if the inventory handling had been flawless. Instead, for many parts, it was difficult to tell how many parts actually were in a package from the moment they first arrived in the building, and it didn’t get any easier after that. This is an example where one of the most fundamental Toyota Production Systems principles, “set in order,” was lacking. I will revisit the topic of parts handling and presentation in a later post.


Ordinary Challenges for On Time Delivery (Part I)

This is the first part in a multi-part series about on-time delivery. If you are familiar with manufacturing (light machining and assembly), all the topics in this post will seem quite mundane. But they deserve to be mentioned because ordinary problems with ordinary solutions can still be part of the chaos even when there are some special causes. Part II describes the inventory chaos resulting from using visual control systems inconsistently across overlapping processes. Part III describes how lack of work leveling leads to inconsistent responsibilities and lack of accountability. Part IV describes how an emphasis on metrics rather than fundamental customer relationships, and on immediate results rather than process capability, skewed efforts to improve.

I spent a significant amount of time trying to help one company improve its on-time delivery.  My primary responsibility was to identify causes for late deliveries. Some of the causes were pretty straightforward:

  • Inventory inaccuracy resulting in component shortage
  • Quality non-conformance requires rework or scrapping part
  • Traffic jams in production processes
  • Supplier late delivering to factory

Since the nature of these problems was pretty ordinary, possible improvements are also not hard to imagine. Inventory accuracy could be greatly improved by locking up inventory and restricting access to authorized personnel who are trained and held accountable to always update the system on how much inventory was released and for what purpose. Although there was a fairly limited number of people who were “usually” responsible for transferring inventory from storage to point of use, there was quite a large set of people who might do it to help out – on second or third shift, when many assembly lines all needed replenishment at the same time, or for any number of other real or imagined reasons. Consequences of restricting access might include delaying some assembly lines if the demand for parts at a given point in time were too great for the authorized staff to handle, or paying authorized staff to stand around and do nothing during periods when demand for materials were lower than peak.

There were also a surprising number of cases where inventory accuracy was hampered by material packaging and presentation deficiencies: pieces dumped in bulk into plastic bags with no clear indication of count, or a count indicated but no corresponding weight with which to check the count. Some parts were packed in bulk even though they were highly prone to hooking and catching on one another, making it quite easy to take more than needed and drop some during handling. More often than not, it was difficult or impossible to tell how many parts were supposed to be in a container at any point in time. Imposing packaging requirements would likely result in an increased component cost.

Quality issues for parts produced in house were, like most quality issues, the result of process variation. Contributing causes might include the condition of the tools or fixtures, contamination of fluids, or unfinished components not to specification. Standard practices for quality control were known and discussed, but the recurrence of issues is a telling indication that corrective actions did not reach to actual root causes. Symptoms of not addressing the root cause include if the corrective action involves rebuking an individual, increasing manual inspections with the addition or alteration of inspection methods or tools, or other changes which would cause the process to take longer and must be done by the worker (not automated equipment) without any change to the way the worker’s performance is measured or evaluated by their immediate supervisor. In other words, instructing the worker to get the same amount of production but follow steps that take longer to do.

Traffic jams occur when the cascading effect of a problem affects later jobs which themselves have no problem, but are started late and finish late due to the problems on other jobs.

Supplier issues, whether late delivery or poor quality, generally have the same types of causes and possible solutions. Much as with internal employees, the main thing that matters in the long run is how suppliers are held accountable. Informing suppliers that you are displeased will have little result if there are not increasing consequences, starting with charges for nonconforming material and ending with discontinuation of the business. Dropping a supplier for quality or on time delivery issues can result in higher costs for buying from higher performing suppliers.

Marketing Should Own Inventory

I’ve seen Marketing expected to manage these business success metrics:

  • Market share
  • Profit margin
  • Sales forecasting

To support these goals, Marketing is generally supported out of the following costs:

  • Payroll for employees
  • Media & collateral
  • Public Relations
  • Trade Shows
  • Training
  • Advertising

In two of the companies I have worked with, Marketing felt hampered in its efforts to reach its goals due to product lead times. In both cases “Lead Time” was not formally considered a Marketing Metric, and in both cases “Inventory” was not considered a Marketing cost.

This seems to me to be a fundamental organizational defect. Delivery lead time is a competitive consideration in many markets (I might dare say most markets), and it’s widely recognized that inventory can be substituted for lead time, and lead time for inventory. This equivalence is a fundamental theory of the Toyota Production System.

It’s true that the need for inventory below the shippable SKU level is partly determined by the manufacturing process capability. Manufacturing clearly owns the responsibility to continually improve the reliability and speed of the manufacturing process. But it still seems quite achievable for the responsible Marketing representative to say, “We have X inventory position in order to support Y delivery expectation.” If challenged as to why so much of X inventory is in WIP (not yet shippable), it should be fairly straightforward to show the inventory required to buffer against the supply chain performance.

As all production and supply chain managers know, a great deal of the need for inventory comes from variance between the demand forecast and the actual demand. It’s also sometimes been my experience that Marketing (or Sales) wishes to divert inventory that was built for Customer B in order to satisfy Customer A – but will still sometimes unabashedly complain about the lateness of fulfilling Customer B’s order. Sometimes these sacrifices have to be made; but Marketing should be paying out of their own pocket.

Simply put, Production and Supply Chain should have fiscal responsibility for inventory covering supply chain and manufacturing process variance, and Marketing should have fiscal responsibility for inventory covering demand variance. Somewhere out in the wide world I’m sure it is so; but I wonder why it is not the rule everywhere.

Waste, Want, and the failure of the Toyota Production System

The fundamental genius of the Toyota Production System is bringing the focus on the customer into consideration for any and every process. The Toyota Production System does not always have the most convenient tool to directly address a particular problem, but many other methodologies lack the fundamental centering on the customer. Six Sigma is a set of tools to reduce variation, for example, but it does not intrinsically ask you whether the product you reliably produce is what your customer wants. Six Sigma will cheerfully coexist with the waste of over-processing.

When the Toyota Production System was first being hailed as the panacea for American manufacturing, the common stereotype was that American manufacturing was designed to produce as much as possible, regardless of whether anyone wanted it. American manufacturing managers care about machine utilization – the more, the better! And this attitude has not entirely gone away; or rather, it has largely not gone away at all, and only gone underground. This Monday a friend told me that his father, and old-timer at a local factory, preferred working on the third shift, away from all the nonsense about Toyota production, where he could produce three times as much as the first shift.

People of all occupations speak in short-hand, so for a man to boast of his production quantity does not necessarily prove he is overproducing, or producing with any more defects than his first-shift neighbor. And those on the first shift, where “Toyota production” is blamed for slowing things down, may be trying to drape Toyota-inspired charts and graphs over the same attitudes and goals and incentives as they’ve always had—which can only result in more inefficiency, not less. “Overproduction” shifts from being solely a problem of the commercial product and becomes the production of charts that nobody wants, needs, uses or cares about, charts which are always updated when a manager from Corporate is scheduled to visit but never updated when there’s a push on to hit the end of month production target. But someone involved in this story has definitely lost track of what Toyota Production System is fundamentally about.

I was once involved with a major event, featuring a Genuine Actual Real Toyota Engineer, meant to apply Toyota Production principles to one of the production lines in a century-old factory that had second and third generation employees. One of these old salts, Tom, was responsible for scheduling production on the line—not his first job at the company, and not his first year in that job.

Tom didn’t take very kindly to being told how to do his job, but he didn’t rely on the strength of his own opinions. He got data – the orders for the product that ran on that line – and he charted it. He printed the chart on the plotter so that it was three feet tall, so that he could show on the chart the enormous spike in demand he’d recently dealt with. It was quite out of the bounds of the typical run rate, and made a terrific illustration.

The Genuine Actual Real Toyota Engineer from Japan thought that it must be a stock order, and through his interpreter he asked about that. “No,” Tom said, “it’s not an order for stock; it is an order from a customer, a shippable order. If we ship it we can invoice for it and get paid.” The Engineer was amazed, shaking his head and muttering “Very difficult, very difficult.”

As it happens, they were both right. As Tom said, it was a shippable, invoiceable order, and Tom’s boss, and his boss, and all the bosses all the way up the multinational diversified corporate ladder wanted him to build, ship, and recognize revenue, as soon as possible but at least in time to be in the next quarterly investor update. But it was stock, too; stock to be held by a distributor, stock that would not tie up our capital but would sit in the “customer’s” warehouse for months being gradually sold off; stock purchased at a pretty discount because it allowed a sales person to save the quarter.

American business managers caught on quickly to Toyota’s anti-inventory message, because inventory ties up capital and that makes investors fidget. Inventory is bad! Down with inventory!

But the Toyota Production System also emphasizes takt time, which is to say the amount of time it takes to complete a step in the manufacturing process – or better put, the amount of time it takes to complete every step in the manufacturing process, so that the whole entire process moves ahead in synch, like a clock, to the tempo of the takt time. To conventional thinking, this is arbitrary and silly; some days you have to work harder and faster than others, that’s just the way it is. Slowing everything down so it will look pretty and synchronized makes as much sense as telling soldiers who are being shot at to walk slowly and not muss their uniforms.

Who, though, is the enemy? Under the Toyota Production System, the enemy is waste in all of its forms, including producing more than is wanted or producing defective products that are not wanted. Defects are unexpected, of course, and unexpected things happen when there is a lot of change, a lot of variation, too much going on to keep track of it all. If we know exactly how long a step in the process should take, than we know that if it took more or less time something changed. The change could be a good thing, increased efficiency, in which case we should learn from it and apply that improvement wherever we can, but it could also be a bad thing: a missed step, a defect.

The pell-mell rush to ship everything possible in time to invoice it in this fiscal quarter is the right approach if this quarter is the only quarter that matters, if we never have to improve our quality or productivity or efficiency, if God is going to stop time and give us all eternal rewards based on our production numbers this month. But, if you take a slightly longer view, and consider it more important that you know how to get better, then takt time becomes important because it is yet another way in which variation—and the likelihood of defects, of time and effort spent on unwanted results—becomes visible. If those metaphoric bullets are coming from the CEO and the shareholders toward anyone who didn’t help make the profit target for the month, takt time will not save you. If the enemy is waste, then takt time is not a silly ineffectual dress rehearsal; it is the scrupulous elimination of any possibility that the enemy could be hidden from view.

The Genuine Actual Real Toyota Engineer wanted Tom to run the production line at the same speed (takt time), producing at the same steady level (Heijunka). Tom proved it was impossible to do that given the variability in the customer demand, so the Genuine Actual Real Toyota Engineer was stumped. He couldn’t tell Tom to disregard the customer demand as that would violate the fundamental principles of the Toyota Production System.

But what did that customer really want? As a distributor, they were not going to put the product immediately to use if it all showed up on one day. They would be reselling gradually over time. The customer wanted the discount they were able to wrangle out of their sales representative by placing such a larger order. With the discount in hand, they would have been perfectly happy to receive the products at a steady pace over a much longer period of time.

What did the sales rep want? He wanted the commission from booking the deal. It was a large enough deal that probably his manager had promised him some special extra compensation if he landed it. Nothing in the incentives or instructions offered to that sales rep made it his responsibility to learn when the customer actually needed to have the product in hand, so nothing in the incentives offered to the customer encouraged them to spread the deliveries out over time.

Nobody in the room that day with Tom – nobody in the building—had the authority to fix the problem. The root cause of that problematic order spike was that the sales rep did not know what his customer wanted, and in fact did not even know who his customer was.

“The Customer Is Always Right!” has become so hackneyed that it is hard to find it in use today without irony. But it is not wrong; it is right enough as far as it goes. It is simply insufficient, and fails to properly define who the customer is. The customer is the one who is willing to pay for the product you offer. If you run a hair salon and someone calls asking for pizza, that person is not your customer. If you run a car factory and someone calls asking for pizza, that person is not your customer. And if you run a car factory that can produce a car in four days and someone calls asking for a car in four seconds, that person is not your customer.

When someone with money asks for something you cannot deliver, that person is not your customer.

There are potential customers who will ask for something which may be difficult to deliver, and then the business managers must decide if it is worth the risk of failure and the extra cost to satisfy the challenging delivery; they must decide whether to accept the customer. A business that never adapts to meet new requests will not change as its customers change, and eventually all the customers it once had will no longer exist. But money on offer does not by itself define a customer. It must be matched to a capability to provide.

A capability for which nobody will pay is not good business (it is overproduction), but payment for something you are not capable of providing is also not good business (the result will be defective).

The order that the sales rep booked for an excessive quantity of product from Tom’s line could not be met by the date on the order. Since the capacity to provide was not available, the order should have been refused, or negotiated to something achievable.

But the order that was booked did not adequately represent what the customer wanted to pay for. The customer understood that the order would not likely all arrive by the date requested, but there was no penalty, surcharge or inconvenience for requesting it for immediate delivery. If it had been delivered all at once it would probably have caused a storage problem in the distributor’s warehouse (although very likely there was no penalty or negative feedback that would reach the person placing the order, any more than for the sales rep). The low price that the buyer wanted would have no adverse effect on the factory operations, while the short delivery time adversely affected a large number of other customers. The customer who booked the larger order would not have been willing to pay a surcharge for the harm to the rest of the factory’s business, but, being offered the convenience without any consequence, they were happy to take it.

“Customers” will take many things for free, but true customers pay for what they get. This crucial distinction is often hard to keep in view during new product development; Henry Ford is reported to have said that his customers would only have asked for a faster horse before he gave them the choice of a car. Those customers are using “horse” as a word to mean “fast, reliable, low-cost transportation,” and eventually “car” became a better term for that than “horse.”

When I was a product manager in a forklift company we had an inside joke that if you asked a forklift user what he wanted, he would tell you he wanted a radio and a place for his drink; and if you asked the forklift operator’s boss he would tell you that operators are not allowed drinks or radios while they work. The customer, as it turns out, is not the person who drives the forklift, but the person who pays for it. A certain amount of comfort for the operator reduces operator fatigue, improves productivity, and is good for everyone. But a forklift operator’s supervisor wants pallets to be moved in a safe, clean, efficient and attentive manner, and a forklift operator wants to watch football and forget he is at work.

It turns out, though, that forklift operator supervisors are not much more help. They will tell you they want the forklift to break less; but that is, like a faster horse, a trifle obvious, and if your warranty and service data is any good you already know what is breaking and don’t need to be told by the supervisor.

While the supervisor is telling you that he would like the forklifts to break down less often, however, you might notice that the operators are standing idly by their trucks, waiting for the third-party computer system to boot back up. It takes a while to boot up but must do so after every break, because while on break the operator unplugs the forklift from its only power source (a giant lead acid battery) in order to recharge it. If you could eliminate the need to unplug the battery (and power off the computer) in order to charge it, you would save the forklift supervisor down time on every single shift after every single break, far more time than he is losing to the relatively infrequent breakdowns. What he wants is not what he is saying.

To follow the Toyota Production System in the development of new products, it is necessary to apply the Toyota Production System analysis to your customer. For what activity is your customer paid? If you sell to a consumer and your customer is not paid for using your product, how is he rewarded? What is the actual cause of pleasure or reward, and what is getting in the way of achieving it? When you understand what the customer actually wants, you will understand what the customer will actually pay for. There is very little point in asking him what he wants (you’ll probably hear about faster horses and free pizza), but if you need to you might ask why he is doing as he is—you might even ask him five times to get to the root of it.

But you must know who your customer is – who you wish your customer was, to become more like what they want, and who is the customer that will pay you today for what you can do today. And this is why so many companies have struggled to implement the Toyota Production System: they don’t know who their customers are.

At the factory where Tom worked, we thought the customer was the end user of the product, or at least the distributor who ordered it from us. But we were wrong. The business was not run to satisfy that customer. That customer would not care at all whether the factory shipped the product this month or that month, this fiscal quarter or that fiscal quarter. The all-out effort to maximize shipments in a fiscal period was done for the actual customer, the one who cared about that result: and that is the shareholder.

As it turns out, the shareholder pays the CEO.

The shareholder may pay the CEO indirectly, through the board of directors, by means of the shareholder vote; or the shareholder may pay the CEO directly, in the form of stock options and grants. As the stock value goes up, the CEO gains wealth. What activity will make the stock price go up? That becomes the value-add activity.

And now in the factory things become very confused for the factory worker, because he is told that Toyota Production System is “customer focused” and will make the “customer” happy, but he is reprimanded if he does not make the shareholder happy. And some of the things he is told to do for Toyota Production System seem to make sense for the “customer,” like never make any defective products, but some of the things he is told do not seem to make any difference to the “customer” at all – such as that it is very important to ship on June 30 and not July 1. And so it seems like Toyota Production System is a bunch of nonsense that doesn’t actually make his boss happy, and so he treats it like nonsense, and before too long it goes away. And then another CEO wonders why Toyota Production System doesn’t work for his company, and he finds something different to try to promise his shareholders as a panacea.

And that CEO will never understand that the Toyota Production System does not consider inventory wasteful because it ties up your capital. If you can get paid to tie up your capital in inventory, by all means do it! (And thus warehousing exists as a profitable business.) Toyota Production System views inventory as waste because it hides waste. Inventory is a time buffer, and a time buffer exists to hide a variation in process time, and variation in process time exists because the worker does not know what to do or because the worker needs to fix a defect. And that is a much more serious problem than the negligible amount of overhead expense allocated to storing inventory.

The Toyota Production System is not a panacea. It is fundamentally designed to improve processes, and not everything worth doing is a process. But the Toyota Production System has “failed” far more often from being misunderstood, misconstrued and misapplied than it has from any real deficiency in its basic philosophy, which is to understand what your customer wants, and do that.

[Note: Tom is an alias.]

Excuses Enabling Waste

I first began learning about “Lean Manufacturing” in 2006, and since then I’ve had many opportunities to see this philosophy misunderstood and misapplied. Most recently I saw a variation on basic Lean terminology in a class meant to teach Lean Six Sigma principles for process improvement.

I’ve never been formally credentialed in Lean Manufacturing and it presently seemed like a good time to cross it off the list. I am taking an online program mainly consisting of recorded lectures, which means I did not have the opportunity to object when the professor started explaining the concept of “Value-Enabling Activity.”

In classical Lean Manufacturing (substantially derived from the Toyota Production System), an activity is classified as either Value Adding (VA) or Non-Value Adding (NVA). The simple rule of thumb is: would a customer reasonably pay you more money to do more of this activity?

In the case the professor was discussing, the setting was health care. Time spent in the waiting room was classified as Non-Value Adding, since nobody wants more time in the waiting room. Time spent with the physician was classified as Value Adding, since that’s the essential service that people are seeking.

But for check-in activity the professor had a category previously unknown to me, “Value-Enabling”. The idea is that the health care provider cannot safely provide care without going through the check-in activity—checking for medical allergies, other health conditions, and so on. Even though it would be hard to find a customer willing to pay more for more time spent on check-in, this activity is considered essential and not properly described as “waste,” the other term for Non-Value Adding activity.

This is a basic perversion of the meaning and purpose of classifying activity as Value Adding or waste.

While it may be true that with today’s laws, customs, and technology there might not be at present any way to eliminate the check-in activity, the fact that the patient do not enjoy this activity and would happily be rid of it should never be forgotten. That is the entire purpose of classifying activities very simply as either value-adding or waste.

It is no defense to say that the activity is necessary. It is currently necessary to ship cars from the car factory to the customer – and typical to ship them not to the customer, but to the dealership. Transportation is absolutely one of the seven wastes. Transporting the car from the factory to the dealership is waste, because no customer would pay extra to have the car shipped back and forth several more times. It is necessary but unwanted – just like the waste you flush away every day.

A reflective person will realize that, really, the only way to have no waste is if the product materializes immediately upon the customer’s first realization that they want it. Anything else involves delays and is wasteful.

More specifically, consider the case of a chunk of metal being shaped into a widget. Modern CNC (Computer Numerical Control) machines can automatically switch between several different tools to shape a part. The process of switching between tools is Motion, and therefore waste.

In most analyses, the time a chunk of metal spends in a machine is all Value-Add time. Many people would balk at the idea of being so hyper-sensitive as to classify the time switching tooling as waste. Nevertheless it is true that if you somehow had one tool which could do it all, and therefore did not need to switch tools, the process would take less time; your machine would be more efficient and therefore more productive.

The correct reason not to worry about the time a machine spends automatically changing its tooling is that this small amount of time may not be where your real problems lie. And this is perfectly consistent with the principles of Lean Manufacturing; no practitioner of Lean Manufacturing would suggest chasing a waste of a few seconds when there are problems costing you hours of time you could resolve. There is absolutely no shame in working on the biggest problems first; the only way it might not be best to work on the biggest problem is if you are not actually capable of influencing it. Otherwise, always go for the biggest problem. If it’s too complex, figure out the major causes and pick the most significant; repeat as needed until you’ve got a problem you can work on.

Going back to the health care scenario, check-in time might currently be necessary. But what if a quick scan of your retina were enough to bring up your complete medical record and verify that it is really you? This would virtually eliminate the Non-Value time and leave only the valuable part of the check-in process.

Someone might object that in this particular case, there may be a potentially viable technology solution, but that, in general, there are some things that just have to be done in order to get to the good stuff, and those things are Value-Enabling. But that category allows you to justify and excuse activity your customer dislikes, turning a blind eye toward your own inefficiency and becoming systematically indifferent to what your customer wants.

Consider that it is still necessary today for products to be shipped from the factory to the consumer. If everybody just shrugged and said “Can’t be helped,” Amazon would not be the force in commerce that it is today. On the contrary, Amazon has patented anticipatory shipping – shipping you something before you tell them you want it, so that the shipping time gets even closer to zero. Service technicians do this all the time, keeping commonly needed replacement parts in their vans, but Amazon is the first major company to realize that this basic concept could be extended across the entire range of things ordinary retail consumers might want shipped to their house.

It’s not clear whether Amazon has actually implemented this idea yet. But, with delivery drones and delivery lockers and delivery to your trunk, it is very clear that Amazon hasn’t declared the time it takes to delivery an order “Value Enabling” and thus beyond criticism. Transportation is waste. Get rid of it whenever possible.

There is no business or process anywhere in the world that has achieved fully zero waste. Some of the causes of waste are laws of physics and some of the causes are laws of governments. It should never bother you to have some part of your process described as waste; if your feelings are hurt, you’ve misunderstood the message completely. And it’s easy to test: if you are right and it’s not waste, charge more for it; do it more often; increase the amount of it you have in proportion to the other parts of your process. If it’s actually valuable you’ll make more money. But if it will increase your costs – then yes, Virginia, it is waste.