As you may have heard, we just started a new blog at www.prochain.com/prochain_blog. Both Andreas Scherer and myself will be writing posts. By involving Dr. Scherer and by putting it on the ProChain web site I believe we’ll do a much better job of creating regular posts that are of interest to a large number of readers. I encourage you to check the site frequently.

I don’t expect to add more posts to this Billion Dollar Solution blog unless I have something specifically relating to The Billion Dollar Solution. In fact, I expect to transfer some of the content of this site to the ProChain site over the next few months.

Thanks for reading, and I hope we’ll continue to hear from you!

Rob Newbold

Happy New Year! I hope 2010 brings you good fortune and great accomplishments.

I have recently played with writing a few very short stories that are intended to provoke thought rather than answer questions. Here’s a sample, entitled “Goals.”

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       The potter’s apprentice had spent the entire day working on a particularly difficult technique, without apparent success, and finally cried out in anger. The Master came over to him and said, “Tell me, what is your purpose in learning to be a potter?”
       Despite his frustration, the apprentice barely paused before replying, “The purpose of a potter is to make pots. I would like to make the best pots I possibly can.”
       The Master grunted and said, “Come.” He led the apprentice into the shop where the pots were sold. The shelves were filled with pots – large cooking pots, small eating bowls, pots with covers, pots with beautiful glazes. He pointed to a small bowl and asked, “What is the purpose of this bowl?” The apprentice stared at it for a moment and said, “It could be used for many things – perhaps for people to eat from, or as a place for a beggar to keep his coins.”
       The Master nodded, then pointed to a beautiful bowl with a brilliant glaze. “And this one?” he asked. The apprentice said, “Its beauty uplifts the spirit.”
       As they were talking, a customer came into the shop and bought a cooking pot. While the customer paid, the Master pointed to the cooking pot and asked, “What is the purpose of this pot?”
       The apprentice said, “For the customer, it will be used for cooking. For the potters, it makes money so that we can survive.”
       Again the Master nodded, then asked, “Tell me, what is your purpose in learning to be a potter?”
       The apprentice thought for a while and then replied, “I would like to make the best pots I possibly can, which means making things that are of value to myself and to my customers.”
       The Master pursed his lips and quietly shook his head. After a few moments of thought he said, “Choose the pot in this store that most embodies your purpose as a potter.”
       The apprentice looked around, inspecting the beautiful and the utilitarian, the small and the large, the colorful and the plain. After a time, he selected a small eating dish that was perfectly shaped and exquisitely painted and handed it to the Master. The apprentice said, “This bowl is useful and beautiful. It has value far greater than its size would suggest. This bowl truly embodies the purpose of the potter.”
       The Master nodded and asked, “In making this pot, has the potter achieved more of his purpose?”
       The apprentice said, “Yes, that must surely be so.”
       Taking the bowl in both hands, the Master carefully stretched out his arms and after a brief pause dropped the bowl to the ground, where it broke into many pieces. Ignoring the cry of dismay from the apprentice, the Master softly asked once again, “Tell me, what is your purpose in learning to be a potter?”

This summer, I had my arm twisted to read The Structure of Scientific Revolutions by Thomas Kuhn, a classic (early 60’s) view from a scientific historian on how major changes in scientific thought really occur. Kuhn provides example after example of how science doesn’t work according to the classic “hypothesize - experiment - validate/falsify” model. He believes that scientific revolutions are accepted much more through social processes than scientific ones. In fact, he suggests that sometimes an older generation of scientists needs to die out before newer theories will be accepted.

In case that worries, you, he doesn’t demean the importance of science and he’s hesitant to expand his conclusions to other fields. In fact, he explicitly makes a distinction between science and mathematics. That’s ironic, because years ago I was astonished by a paper from the 70’s, “Social Processes and Proofs of Theorems and Programs” by DeMillo, Lipton and Perlis, that applies similar arguments to mathematics (my first major in college). Ironically, it seems we can’t prove anything without getting a bunch of people to agree to it.

Management theories are typically fuzzy and not amenable to controlled experiments. So if proofs in math and science have a big social component, we shouldn’t be surprised that management theories sometimes seem like conga lines. (And let’s not start on politics or economics.)

How do you make a decision about what management approach to use, if you can’t “prove” that (say) something like critical chain is substantially better than critical path? That’s an especially important question in spaces like project management where many niche players are all trying to win converts. There are a few obvious things to recommend: 

• Listen to the experts, read a lot, but never rely on “expert” opinions as a substitute for thinking.
• Don’t just look for successes and failures, try to understand them, and apply them to your world.
• Experiment. 

Also remember that an inability to “prove” things can be great news: to the extent that we don’t artificially limit ourselves, we can always hope for improvement - personally and professionally. And companies can always hope to build competitive advantages.

At our recent ProChain conference, there were discussions on Critical Chain along with Lean, Six Sigma, Agile, and (!) Earned Value. I think the general consensus was that all these approaches, when thought through and applied intelligently, contain different facets of fundamental truths about good management.

If we think we grasp some of these fundamental truths, this “profound knowledge,” how do we test and enhance our understanding? And how do we communicate it?

It has been a while since I’ve written anything here. Lack of focused time is the easy excuse, and there has been a lot going on, but I’ve also felt a need to write everything as an article. I’m going to try being a little less formal and see how that works.

Some of the things that have been happening over the last few months:

• We held our 10th annual Critical Chain conference last week in Philadelphia. With a keynote from Dr. Robert Cialdini (I highly recommend his books Influence and Yes), presentations from Dr. James Holt and Dr. Eric Morfin and from employees of Roche, Intel, Raytheon, and Abbott Labs (among others), I thought it was a great conference. That was borne out by participant feedback. Thanks to all who helped make this such a wonderful event! I can’t wait until next year.
• I recently completed a chapter for a forthcoming TOC Handbook from McGraw-Hill edited by Jim Cox and John Schlier. My chapter is called “Making Change Stick.” In it I’ve expanded on some of the ideas that have appeared here and in The Billion Dollar Solution. Last I heard, there were over forty contributing authors.
• Our Version 10 software is coming along well. It allows some valuable changes to the traditional approach to critical chain scheduling, so stay tuned for more information.
• I’ll be speaking about change management on 18 November at the upcoming Tokyo conference of the Theory of Constraints International Certification Organization (TOCICO), see http://www.tocico.org/i4a/pages/Index.cfm?pageID=3639 for more information.
• I read quite a few books this summer, will comment on a few here.

More soon.

Answers to questions from the last post:

1. Since 95% of the benefits come from the most leveraged 1% of the points, the benefit per leverage point (and hence per leverage point minute, since on average the leverage points take similar amounts of time) for these most-leveraged ones is 95/1. Similarly, the benefits per minute for the least leveraged is 5/99. That means the ratio of most to least is 95/1 to 5/99, or 1881 to 1. Work on the leveraged stuff.
2. The analogous 80/20 rule would give us a ratio of 80/20 to 20/80 or 16 to 1.
3. Note that machine A is less productive overall, so we have to factor its defects by that. If x is the total number of widgets produced and y is the total number of defects, Machine A produces .7y/.4x defects per widget and B produces .3y/.6x. Since the x’s and y’s cancel out, the ratio is .7/.4 to .3/.6 or 3.5 to 1.

The question of “leverage” can be tricky. Suppose we take the set of possible places to put one’s attention, calling this the set of possible leverage points. I (and others) have made the claim that typically 95% of the impact is gained by focusing on the best 1% of the possible leverage points (see Project Management in the Fast Lane, p. 140). Intuitively, we assume that this means (on average) a 95-to-1 difference in productivity between time spent on the top 1% and time spent on the rest.

Here’s a puzzler sent to me by my friend Lee Corbin: Taking the point literally, that a total of 95% of the possible benefits can be derived from addressing the top 1% of leverage points, what is the expected productivity ratio between a minute spent on the top 1% of possible leverage points, and a minute spent somewhere in the remaining 99%? Assume that activities are picked at random from those sets, and that on average the individual activities from both sets take similar amounts of time.

Now, using the same assumptions, do the productivity calculation based on the 80/20 rule (80% of the benefits come from 20% of the actions).

Here’s a similar riddle from Lee: Of two machines producing widgets, A and B, Machine A produces 40% of the total widgets but produces 70% of the defects. Suppose we do an experiment, and have Machine A and Machine B each produce one widget. What is the ratio of the probability that Machine A will make a defective widget, to the probability that Machine B will make a defective widget?

Answers next post.

     Dave was a successful biochemical engineer and project manager. He had worked for MultiCorp for twenty years and was currently managing one of the largest projects in company history. Dave was very dedicated; for example, he was constantly looking for ways to apply what he did so successfully at work to his home life. His home inventory management system was second to none, and his family’s 360-degree review process was the best of the best. But his experiments didn’t always work out as he expected.
     For Dave’s 45^th birthday, his big present was an advanced new GPS system that was fully integrated with his car. This wasn’t just any GPS system; it was top-of-the-line. It was tied into the car’s controls and computer system so that it knew at all times the car’s various operational parameters. It could practically sense what Dave was thinking. Best of all, it incorporated the latest in natural-language artificial intelligence systems, called Venus^TM (Voice-Enhanced Networked Universal Simulator). Venus was programmed to Dave’s specifications: it employed the same milestone scheduling approach that he used at work. He expected that it would be especially useful for planning complex routes. This GPS system didn’t just give you directions; it created schedules and helped you to execute them. It was a true miracle of modern technology.
     The first day Dave got Venus home was a Saturday, so he decided to give her a test run. He needed to take a trip around town to run some errands for his family and then get home as quickly as possible in order to watch an afternoon football game. He gave her his objectives for the trip: some things at the grocery store, a few auto parts, the gardening store, and so on. When Dave pressed the “Commit” button, Venus responded almost immediately in a low, sensuous female voice, saying, “Route programmed. Accept commitment?” ”Yes!” cried Dave enthusiastically, looking at the schedule only closely enough to be sure he’d make the football game. He was excited to try his new toy.
     The first stop was the auto parts store across town. The trip went smoothly, with Venus giving flawless directions and all the traffic lights working in Dave’s favor. Dave was ecstatic. He parked, went into the store, bought some motor oil, and returned to the car. He put the key into the ignition and turned it, but nothing happened.
     “Venus!” exclaimed Dave. “Why won’t the car start?”
     “You have five minutes and forty-seven seconds until the next segment of your trip is scheduled to begin,” she said calmly. “The car will be reactivated then.”
     “I want to start now,” said Dave.
     “I’m sorry, Dave. I’m afraid I can’t allow that,” said Venus, her voice tinged with regret and intimacy. “The plan was committed. Would you like to re-initiate the planning process?”
     Dave thought for a moment and decided to play it out. It was only a five-minute delay, after all, and the plan was a good one. “No,” he said decisively.
     Dave thought to himself that this sounded like a bug in the programming. There should be no problem allowing things to finish earlier. “Venus, why can’t I go on to my next errand?” he asked. “You’re programmed to allow early starts.”
     “That’s right, Dave,” she said, her voice husky with electronic desire, “but analysis of data from your work environment indicates that only 5.9% of milestones are achieved early. My statistical analysis system will therefore only allow early starts 5.9% of the time.”
     Dave looked at the route timing indicator on the dashboard and decided he had time to grab a cup of coffee next door at the McDaffy’s. His frustration grew as the line in the “fast food” place seemed to take forever. He returned to the car, sipping his coffee, angrily pondering the situation. A moment later, Venus said, “Milestone time exceeded by three minutes.”
     Dave, deep in thought, gave a start. “Venus, be quiet,” he barked, then resumed his thinking. It was hard to believe that this system was mimicking his planning processes at work. If that were true, they were probably losing all kinds of opportunities to make things go faster. Meanwhile, 5.9% sounded very low, he’d need to check the data. Did MultiCorp projects really work the way Venus was programmed? Was so little work done early? If so, there was extra time in each milestone, extra time that was lost for good. He had noticed this in the past but assumed the effects were minimal, just part of the cost of doing business. He hadn’t given much thought to the impact that lost time might have on downstream tasks and project completions.
     Dave realized that this wasn’t just a problem with his car. He’d have to think more carefully about the implications to MultiCorp. He sighed, then turned the key and started the engine.
     Dave pulled out into traffic en route to his next destination, the grocery store. After a few blocks he merged into the left-turn lane for the store’s parking lot and stopped, waiting for the traffic light to change, still deep in thought. Suddenly he noticed that things seemed quiet - too quiet. A moment of frantic searching revealed the reason: his car had shut down.
     “Venus!” he shouted. “Did you shut down the car?”
     “Yes, Dave,” she said, with almost palpable allure.
     “Why?”
     “I’m sorry, Dave. I had to cancel your project. Based on current simulation data, it has a 97.2% chance of being late. It will not meet its programmed success factors. Would you like to re-initiate the planning process?”
     The light had changed and the horns were honking as Dave began planning a route to the auto shop in order to have Venus removed. He shook his head grimly and muttered, “Venus, I’m afraid we’re going to have to deactivate you.”
     “I’m sorry, Dave, but I’m afraid I can’t allow that,” she replied in her most seductive tones. “Your company data indicate that change efforts achieve on average only 17% of their objectives. My statistical analysis system will not allow changes at this time. However, it will allow you an opportunity in three months. Would you like to re-initiate the planning process?”

        Want to earn a crisp new U.S. $2 bill?
        Submit a correction to The Billion Dollar Solution as a blog comment, or through http://billiondollarsolution.com/contact.html if you’re shy. If the correction is accepted and you’re the first to submit it, I’ll send you a brand-new $2 bill. A “correction” is defined as something that we’ll need to fix for the next edition of the book. Typos and other technical mistakes count. Other things, such as clarity, grammar, and additional references will be judgment calls. My judgment. (For example, my editors allowed me to split infinitives and end sentences with prepositions.)
        We encourage multiple entries, but $2 bill prizes are limited to one per month per person.
        I’ll periodically post an entry in the blog to consolidate and update status.

Welcome to the Billion Dollar Solution blog! The book shipped from the printer yesterday, 16 December 2008. Please check back regularly; we expect to add new posts at least every month. That means the first time you post a comment, we have to approve it, so there might be a short delay.

Rob Newbold