Michel Baudin's Blog

Jan 24 2022

Does Amazon Use Lean, Six Sigma, or Lean Six Sigma?

In 2019, Christoph Roser posted six articles on his blog about the inner workings of Amazon Fulfillment Centers, based on visits to locations in the US and Germany. His blog is called AllAboutLean but the word “Lean” appears nowhere in his articles about Amazon. “Six Sigma” does not appear either, and Christoph does not mention meeting any black belt.

In addition, in Working Backwards: Insights, Stories, and Secrets from Inside Amazon (2021), Amazon alumni Colin Bryar and Bill Carr make no reference to Lean, and all they report about Six Sigma is using DMAIC to define metrics.

Yet you find some published descriptions of Amazon as a showcase for Lean, Six Sigma, or Lean Six Sigma but, if you consider them without confirmation bias, the evidence is underwhelming. The keywords appear, along with a few more, like “Operational Excellence” or “Scrum.”

Based on the small amount of published data, the leaders of Amazon, starting with Jeff Bezos, “learned a bunch of techniques, like Six Sigma and lean manufacturing and other incredibly useful approaches.”

In other words, they learned everything they could get their hands on while staking out uncharted territory. Then they developed their own system. Now they are sharing with outsiders a few homilies but no details, as is their privilege. Their system is to retail as Toyota’s is to manufacturing. It’s not reducible to Lean, Six Sigma, or Lean Six Sigma.

By Michel Baudin • Blog clippings • 6 • Tags: Alibaba, Amazon, Lean, Lean Six Sigma, Six Sigma, Toyota

Jan 9 2022

Always the Hurricanes Blowing (Part 2)

This post and the previous one use Atlantic hurricanes as a vehicle to show what various visualizations can do. It’s not about second-guessing the data scientists at NOAA who have produced similar displays and much deeper analyses. The point is to show tools anyone can apply to data that may have nothing to do with hurricanes:

Processes, for spaghetti mapping.
A fleet of trucks and their freight, on a map.
Individual workpieces or part containers on a shop floor, if tracked.
The migration of sources of defects in a manufacturing process.
Projects going through phases.
…

While the previous post aimed to show richer visualizations than possible with 100-year old techniques but it was still limited to a few static displays. This means charts that look the same in print and on a screen. This post includes dynamic displays, with animation and interactivity, that you can only use on a screen, and analyses of more of the columns in the HURDAT2 database.

The technology I used to produce these charts takes work but didn’t cost me a dime in license fees. The resulting charts are trivially easy for readers to understand and routinely used in publications like the online New York Times.

By Michel Baudin • Data science • 0 • Tags: Data visualization, Dynamic Charts, Ridgelines

satellite-image-National-Oceanic-and-Atmospheric-Administration-August-28-2005.jpeg

Dec 25 2021

Always the Hurricanes Blowing

Atlantic hurricanes hurt people and destroy property around the Gulf of Mexico every year. Whether climate change is increasing their frequency is a serious question. Don Wheeler just had a column on this subject in the latest Quality Digest. It’s about Torturing the Data. He argues that we should be careful about not force-fitting models to arrive at pre-ordained conclusions.

His way of not torturing the history of hurricanes in the Atlantic is plotting yearly counts on, what else, an XmR chart. It’s just as he would for hole diameters in metal plates coming off a production line in 1945. Hurricanes and holes in metal plates, however, have different backstories.

By Michel Baudin • Press clippings • 2 • Tags: Backstory, data science, Hurricane, NOAA, Seasonality, Trend, XmR

Oct 27 2021

Culture Change | MIT Sloan Management Review | Rose Hollister et al.

How the authors see it: “We define culture as a shared set of values (what we care about), beliefs (what we believe to be true), and norms of behavior (how we do things). […] We developed a set of culture transformation principles that maximize the likelihood of success:

Recognize that responsibility for culture can’t be delegated.
Start with the “why.”
Define the target cultural values and behaviors.
Engage and get input.
Build a bridge to the future desired culture.
Build a culture road map.
Reinforce the desired culture in all organizational systems.
Rapidly reward the emerging culture. “

Source: Hollister, R., Tecosky, K., Watkins, M, & Wolpert, C. (2021) Why Every Executive Should Be Focusing on Culture Change Now, MIT Sloan Management Review, Reprint 63137

Michel Baudin‘s comments: I define culture more simply as “the way we do things around here.” You don’t change it by making it the goal of a change program. To do it, first, you change the work, and then employees’ perceptions follow.

Redesign shop floor layouts to facilitate flow, develop multiskilled operators, hire employees for whole careers and retain them through thick and thin, engage them in solving problems,…

Over time, employees realize it’s not idle talk about lofty goals but concrete changes to their daily experience, including teamwork. Then it becomes “the way we do things around here,” in other words, a new culture.

#corporateculture

By Michel Baudin • Press clippings • 7 • Tags: Culture change

Oct 22 2021

Introduction to Manufacturing: Textbook Authors Meet in Zürich

Torbjørn Netland and I met in person at ETH in Zurich on October 21-22 for the first time since 2019! In the meantime, we had met every week on Zoom, exchanged messages on Slack, and edited each other’s writings.

TorbjørnAndMichel — “This is what we want to say.”

By Michel Baudin • Announcements • 2 • Tags: industrial engineering, Operations Management, Textbook

Oct 8 2021

Sales Forecasts – Part 4. Generating Point Forecasts with Trends and Seasonality

This fourth post about sales forecasts addresses what you actually start with — that is, visualizing the time series of historical sales and generating point estimates for the future. Theyou analyze the residuals to determine the probability forecasts.

What prompted me to review this field is the realization based on news of the M5 forecasting competition that this field has been the object of intense developments in recent years. Some techniques from earlier decades are now accessible through open-source software that can crunch tens of thousands of data points on an ordinary office laptop.

Others are new developments. Thanks to Stefan de Kok, John Darlington, Nicolas Vandeput, and Bill Waddell for comments and questions on the previous posts, that made me dig deeper:

By Michel Baudin • Tools • 0 • Tags: Exponential Smoothing, Holt-Winters, Point Forecast, Probability Forecast, Sales Forecasting, Time Series

Does Amazon Use Lean, Six Sigma, or Lean Six Sigma?

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Always the Hurricanes Blowing

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Culture Change | MIT Sloan Management Review | Rose Hollister et al.

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Introduction to Manufacturing: Textbook Authors Meet in Zürich

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Sales Forecasts – Part 4. Generating Point Forecasts with Trends and Seasonality

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Does Amazon Use Lean, Six Sigma, or Lean Six Sigma?

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Always the Hurricanes Blowing (Part 2)

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Always the Hurricanes Blowing

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Culture Change | MIT Sloan Management Review | Rose Hollister et al.

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Introduction to Manufacturing: Textbook Authors Meet in Zürich

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