Variability, Randomness, And Uncertainty in Operations

This elaborates on the topics of randomness versus uncertainty that I briefly touched on in a prior post. Always skittish about using dreaded words like “probability” or “randomness,” writers on manufacturing or service operations, even Deming, prefer to use “variability” or “variation” for the way both demand and performance change over time, but it doesn’t mean the same thing. For example, a hotel room that goes for $100/night in November through March and $200/night from April to October has a price that is variable but not random. The rates are published, and you know them ahead of time.

By contrast, to a passenger, the airfare from San Francisco to Chicago is not only variable but random. The airlines change tens of thousands of fares every day in ways you discover when you book a flight. Based on having flown this route four times in the past 12 months, however, you expect the fare to be in the range of $400 to $800, with $600 as the most likely. The information you have is not complete enough for you to know what the price will be but it does enable you to have a confidence interval for it.

Beyond randomness, events like the 9/11 attack in 2001, the financial crisis in 2008, the Fukushima earthquake in 2011, or a toy that is a sudden hit for the Christmas season create uncertainty, a higher level of variability than randomness. Such large-scale, unprecedented events give you no basis to say, on 9/12/2001, when airliners would fly again, in 2008 how low the stock market would go, in 2011 when factories in northeastern Japan would restart, or how many units of the popular toy you should make.

In Manufacturing, you encounter all three types of variability, each requiring different management approaches. In production planning, for example:

  1. When the volume and mix of products to manufacture is known far in advance relative to your production lead time, you have a low-volume/high-mix but deterministic demand. The demand for commercial aircraft is known 18 months ahead of delivery. If you supply a variety of components to this industry that you can buy components for, build and ship within 6 weeks,  you still have to plan and schedule production but your planners don’t need to worry about randomness or uncertainty.
  2. When volume and mix fluctuate around constant levels or a predictable trend, you have a random demand. The amplitude of fluctuations in aggregate volume is smaller than for individual products. In this context, you can use many tools. You can, for example, manage a mixed-flow assembly line by operating it at a fixed takt time, revised periodically, using overtime to absorb fluctuations in aggregate volumes, heijunka to sequence the products within a shift, and kanbans to regulate the flow of routinely used components to the line.
  3. As recent history shows, uncertain events occur, that can double or halve your demand overnight. No business organization can have planned responses to or all emergencies, but it must be prepared to respond when it needs to. The resources needed in an emergency that need to be nurtured in normal times include a multi-skilled, loyal and motivated workforce, as well as a collaborative supply chain.
    In many cases, you have to improvise a response; in some, vigilance can help you mitigate the impact of the event. Warned by weather data, Toyota’s logistics group in Chicago anticipated the Mississippi flood of 1993. They were shipping parts by intermodal trains to the NUMMI plant in California and, two days before the flood covered the tracks, they reserved all the available trucking in the area, which cost them daily the equivalent of 6 minutes of production at NUMMI. They were then able to reroute the shipments south of the flooded area.

The distinction between random and uncertain is related to that between common and special causes introduced by Shewhart and Deming in the narrower context of quality control. In Deming’s red bead game,  operators plunge a paddle into a bowl containing both white and red beads with the goal of retrieving a set of white beads only, and most paddle loads are defective.

The problem has a common cause: the production system upstream from this operation is incapable of producing bowls without red beads. In Deming’s experiment, the managers assume is has a special cause: the operator is sloppy. They first try to motivate by slogans, then discipline and eventually fire the operator. The proper response would have been (1) as an immediate countermeasure, filtering the red beads before the operation and (2) for a permanent solution, working with the source to improve the process so that it provides batches with all white beads every time.

The imprecision — or randomness — of the process is summarized in terms of its capability, which sets limits on observable parameters of outgoing units. Observations outside of these limits indicate that, due to a special cause, to be identified, the capability model no longer matches reality. In the other cases discussed above, the cause is known: you felt the earthquake, or you heard on the news that war broke out… The only challenge you are facing is deciding how to respond.

Deming made “knowledge of variation” one of the pillars of his “system of profound knowledge.” One key part of this knowledge is recognition of the different types of variability described above and mastery of the tools available to deal with each.

#Variation, #Variability, #Randomness, #Uncertainty, #Toyota, #MississippiFloodOf1993, #Deming

Coaching Lean Without Knowing | Bob Emiliani

“I have long felt that people have listened too intently to the analysts who have not actually “played the game” – the interpreters of Toyota’s management system, not the people who actually created it. I think that it is easy for all to agree that someone who actually created something is a much better guide than someone who studied it second-hand.[…] Original sources are the best sources to learn from and should form the fundamental basis of your understanding of TPS and Lean. ”

Sourced through Bob Emiliani

Michel Baudin‘s comments: The originators of Toyota’s production and management system are all dead. This includes Sakichi, Kiichiro and Eiji Toyoda, Taiichi Ohno, Shigeo Shingo, and others, which makes it difficult to learn from them through personal communication. We can read what little they published, or rely on the generations that came after them. The people Emiliani shows to the right of Taiichi Ohno as “originators,” Fujio Cho and Chihiro Nakao, actually are disciples of the originators, which isn’t quite the same. As Emiliani sees it, the alternative to learning from these people is learning from “interpreters” who, as he implies in the title, don’t know what they are talking about because they had no hand in creating it. Are these really the only choices?

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Is There An Ethical Dimension To Lean/TPS?

In Toyota’s Guiding Principles, last revised in 1997, Michael Ballé sees more than “goal-oriented efficiency.” While I would not use a phrase like “goal-oriented efficiency,” the principles do not strike me as anything beyond strategic guidelines to ensure the long-term, worldwide viability of the company. If they serve this purpose, great, but a car manufacturer is the wrong place to look for philosophical enlightenment.

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Hardship Accounting Of Jobs

France is implementing a new law requiring “hardship accounting,” for the purpose of giving special pension benefits to employees whose jobs impose physical, environmental and rhythm constraints beyond a given threshold in 10 categories. This is causing a dispute between employers, who balk at the detailed record keeping required, and the government, which insists that a duly voted law must be obeyed. What I find disturbing in this tug-of-war is that I hear no voice saying that the existence of hardship jobs is abnormal and that they should be eliminated. Giving special treatment to the holders of these jobs is better than nothing, but it is an immediate countermeasure, not a long-term solution.

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Lean 2.0: Faster, Better, Permanent | Jim Hudson | Lean Expert Academy

From leanexpertacademy.com Today, 10:16 AM

“The Lean that we all grew up with came to us completely wrong. Messengers Jones and Womack not only mislabeled it, but misinterpreted it too. In their roles as observer-reporters, they described what they saw through the old management paradigm and pretty much interpreted and documented everything from that perspective. They did that really well and Lean Thinking became the “go-to manual” as a result. But it wasn’t the right thing, so they pretty much missed the engine of Toyota’s management system. The result? 30+ years of misfires from nearly all corners of the earth, as leaders and consultants took what Jones and Womack observed and tried to implement it.”

Michel Baudin‘s comments:

I agree with your assessment, but I am not so sure about the remedy. About Womack and Jones, I would say that they authored one good book: “The Machine That Changed The World,” and leave it at that. To them, manufacturing was a spectator sport, and they shared the results of a worldwide benchmarking study of the auto industry.

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Project Manager Versus Chief Engineer: What’s The Difference?

Question put to Michael Ballé in his Gemba Coach column:

Management wants us to start lean in product development, but refuses to consider the difference in roles between our current project manager and a chief engineer – how important is that?

Project Manager and Chief Engineer are job titles covering different roles in different organizations. Before commenting on whether management in the questioner’s company should switch titles, we should know how they select their project managers, how much authority the project managers have, and what they are accountable for. Some companies do an outstanding job of product development under project managers; others don’t.

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The Tesla Way vs. The Toyota Way | M. Donovan & J. P. Womack | The Lean Post

Elon Musk Tesla

Given the ever-increasing barriers to entry in what Peter Drucker famously called the “industry of industries,” it’s a wonder that any automotive startups defy the long arc of consolidation by establishing themselves as viable competitors. And it’s even more notable when these newcomers present a model that just might challenge the incumbents to the core. Lean thinker Mark Donovan recently asked LEI founder Jim Womack whether the path taken by Tesla founder Elon Musk points to a new machine that can change the world. 

Sourced from The Lean Post

Michel Baudin‘s comments:

Are the barriers to entry into the auto industry “ever-increasing,” as asserted in the 2010 HBR article linked to above, or did this article get it wrong? Could it be that the barriers are actually falling, with advances in electronics and information technology leveling the field between incumbents and new entrants?

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The Internet of Things in Toyota Operations | Laura Putre | Industry Week

toyota-logo“… Trever White, divisional information officer, noted that his team is regularly on the plant floor, building good relationships so team members can articulate what their challenges are. One challenge they recently identified was the need to build a containment system to more quickly identify and contain a quality issue when it emerges…”

Sourced through Scoop.it

Michel Baudin‘s comments:

As described in this article, advanced IT for Manufacturing, at Toyota, starts from the needs of the shop floor and works its way up. First, you build systems that take root because they help in daily operations, Then you extract and summarized data from these systems for the benefit of managers and engineers.

ERP, on the other hand, starts from the needs of management and works its way down, and I think it is the key reason why ERP success stories are so hard to find.

How is Lean Different From Taylorism? | Michael Ballé | LEI

“They are completely different indeed. They differ in their purpose, their practice and their outcomes. Lean is about self-reflection and seeking smarter, less wasteful dynamic solutions together. Taylorism is about static optimization of work imposed by ‘those who know’ on ‘those who do.'”

Sourced through Scoop.it from: www.lean.org

 

Michel Baudin‘s comments:

Yes, “Scientific Management” was just a marketing label for theories that weren’t truly scientific but were instead based on a simplistic view of human nature. And Taylor’s stopwatch time studies were just aimed at increasing production at every operation with no consideration of flow. I would, however, ask for a more accurate and complete story

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