Tag Archives: Eli Goldratt

Precisely Wrong

preciselyLast Thursday marked the fourth anniversary of the passing of someone who, while not typically credited as a “Lean” thinker, nevertheless had a profound impact on many Lean implementers. Eliyahu Goldratt, or Eli, was an Israeli physicist whose PhD thesis on queuing theory led him and many followers on an improvement odyssey based on his first book, The Goal, that paralleled and eventually supplemented the Lean revolution. I do not believe there is a definitive biography of Eli Goldratt, but there are many individual memories and stories. In 2011, I wrote one in my blog just two months before Dr. Goldratt’s death entitled: Epiphanitis. Here is another to commemorate a great thinker and influencer:

Eli Goldratt’s passionate and sometimes-brash approach to teaching was a hallmark, yet he approached his audience with the logic of a physicist. Holding a lit cigar while he challenged listeners to reject status quo thinking, he sometimes accented his points with profanity. As English was not his first language, I think he may not have been aware of which expletives were appropriate for which crowds – or maybe he was.   He was all about confrontation and doing battle with the conventional concepts that he considered to be the root cause of low productivity. I attended a seminar once where Eli’s TOC model was described by a participant as “too complex due to the myriad and flux of constraints in a typical factory.”   Dr. Goldratt shot back with visible anger, “If you think this is too difficult, then think harder.”

“Cost accounting is public enemy #1 to productivity,” he declared nearly ten years before I’d ever heard of Lean accounting. By 1986, with one year of production management under my belt, I began to understand his reasoning: On a daily basis, my factory’s direct labor was being scrutinized, while waste, which ran rampant, was a periodic footnote on a variance report. This confusion led me to attend a five-day Goldratt workshop to seek an alternative approach to production. When Eli entered the classroom as a guest speaker at the workshop, I approached him immediately with questions about standard costing and variances. He responded, “Traditional cost accounting is precisely wrong,” a comment that instantly and forever changed my thinking. We were measuring labor to four decimal places, yet ignoring all but the biggest production problems.   This particular practice unfortunately continues to this day as a major impediment to productivity improvement.

In 1985, Eli did not explicitly align himself with the Toyota Production System. His Theory of Constraints, TOC, was seen by many as competitive to TPS. But his emphasis on the defective underpinnings of traditional manufacturing were mostly in concert with TPS. He focused at a deep level on the root causes of poor performance: behavioral, logistical and managerial (policy-based) constraints. Goldratt’s TOC Effect-Cause-Effect Technique, or ECET (a topic for a later blog post) provided a powerful means for setting improvement priorities that I have used now for thirty years. In his sixty-four years, Eli Goldratt went on to publish nearly twenty insightful books, each developing his Theory of Constraints and broadening its application beyond the factory floor.

In 2007, Eli Goldratt summed up a kind of unified field theory, including TOC and TPS, as well as the Ford System. Entitled “Standing on the Shoulders of Giants,” the clip paid homage to the science of improvement, from one of its greatest if not improbable proponents: a PhD physicist who to my knowledge never worked a day in a factory. It’s seven minutes long and little hard to understand, but worth a listen.

Are you an Eli Goldratt fan? Share a personal story.


BTW: Speaking of constraints, don’t miss “Teatime with the Toast Dude,” my free monthly webinar, which this month (July 7) will discuss The Politics of Organizational Change. Sign up here.

Also, GBMP has a full schedule of summer Lean learning and benchmarking opportunities – including Plant Tours, one day workshops for manufacturing and healthcare and, as a licensed affiliate of the Shingo Institute, several Shingo Institute workshops planned for Texas, Idaho and Massachusetts. See the full line up of events on our website.

And of course you won’t want to forget about our upcoming September conference – the 11th Annual Northeast L.E.A.N. Conference. Get a sneak peek of the preliminary agenda here or visit the official conference website to read lots more and register.

Artificial Ignorance

For a few years back in tart_inthe early ‘80’s I fell prey to information automation fascination. I managed an IT department transitioning first from a basic accounting system managed by an external service bureau to a batch inventory control system to an order processing and manufacturing control system running on a succession of minicomputers with names like Dec 1170 and HP3000.  If you recognize the names of these systems or if you are familiar with RPG, assembler, Cobol or FORTRAN, then you too may be an old lean dude. The hardware of that decade was slow, flimsy and subject to frequent crashes; the term “user-friendly” as applied to the user interface had not yet been invented.

Today, by comparison, I regularly carry around in my coat pocket a thumb drive with a million times the storage capacity accessible and one thousand times the speed of what was available to my entire company in 1980. And that’s puny compared to the multi-parallel processing power available to businesses today. Today’s super computers pile up so much logged data, that decision rules under the heading of “artificial ignorance” have been created to intentionally ignore data that has been deemed (by someone) to be insignificant. Amazing!

What’s more amazing, however, is that most of the software running on today’s super machines follows essentially the same network-scheduling model we were using in 1980. Call it MRP or ERP, it may be zippier and have more tentacles today than it did then, but the deterministic model that assumes we can know what to produce today based upon a forecast created weeks or months ago is still alive and well. Shigeo Shingo called this model “speculative production.” I call it computerized fortune telling. If production lead times are very long, the fact that we can now run that forecasting model one thousand times faster doesn’t improve its efficacy.

If we add to this model of forecasting and back scheduling a standard cost accounting system whose operating assumptions go back a century, then we have created a model that systematically optimizes local efficiency to four decimal places as it pyramids inventories. Eli Goldratt used to call these calculations “precisely wrong.”

I was at a company several weeks ago that is in the process of replacing a 1980’s MRP system with a later model ERP system. “We’ll be able to allocate our parts for specific orders,” the materials manager, Bob, explained to me. “Hmm,” I thought, “why is that a good thing?”

Bob continued, “We’ll have real-time data.” I reflected, “What does that mean? At best he’ll have a rear view mirror. He’ll be reading yesterday’s news.” Assuming the transactions have been completed correctly and in a timely fashion, Bob will still only know the last place the material has been. Is it still in department A or is it in transit? Or has it arrived in department B, but not yet been transacted? This out of phase situation causes many a supervisor to chase down either parts or transactions to enable production.

“What happened to the pull system you were implementing last year?”, I ask.

“We’ve had to put our continuous improvement activities on hold until we go live,” Bob apologized, “but things will run much smoother once the new system is completely rolled out. We’re discussing an electronic kanban – going paperless.”

And this is where I cringe. I know that it’s been months since the continuous improvement effort was mothballed in order to redeploy resources to the ERP implementation. And I also know that Bob will likely have many more reasons to postpone CI efforts once they do go live. There will be ugly discoveries regarding the differences in rules and assumptions between the new and legacy systems. Material will be over-planned to compensate for shortages arising from start-up misunderstandings. Overtime will be rampant to catch up late deliveries.

Pardon me for sounding cynical. I’ve witnessed it too many times. In the last three months alone, I’ve heard similar stories from nine different organizations large and small. Immense resources are consumed to install hardware and software that runs counter to the objectives of improvement efforts. Thousands of resource hours are spilled into the abyss of information automation with a promise of productivity improvement – hours that would be have been far better spent on simplifying or eliminating questionable business processes. But nobody wants to talk about it publicly. One executive confided recently, “We’ve spent too much money to turn this off now.”

In 1976, Joe Weizenbaum, one of the early leaders in the field of artificial intelligence warned in his landmark book, Computer Power and Human Reason (on Amazon for $.01) that while computers can make decisions based upon rules, only humans should make choices. I worry that with each step change in computer power, human reason takes a step back. Dr. Weizenbaum foresaw the era we now live in where choice is reduced to a set of rules that hide beneath the legitimacy of the “system.” Ironically, this system, built up of nothing more and 0’s and 1’s and once described by Weizenbaum as the “universal machine” because it could be programmed to do anything, has on the contrary become the hugest monument process in any organization. Today’s popular ERP systems, with more than a quarter-billion lines of code, have too often become the tails that wag the dogs.

Maybe I’m just old school, but it seems that thirty-five years after my first love affair with computerization I’m still feeling jilted. How about you? Is your IT strategy supporting productivity and competitiveness or is it the tail that wags the dog? Tell me I’m wrong. Or share a story.

Happy New Year.:)