### Haystack Syndrome 2

Tuesday, September 4th, 2007

In The Haystack Syndrome, which I was just discussing, Goldratt jokes about an enthusiastic process engineer who races to his boss to explain that he has a new way — for just a few thousand dollars — to produce a part not in 20 minutes, but in 21.

This “disprovement” certainly won’t earn him accolades; by the measurements used at the plant, he has reduced efficiency by five percent.

But what he has really done is “elevate the constraint” on the system. He has found a way to offload some of the work on the bottleneck, Resource B, to the “less efficient” Resource C, which has excess capacity, because it’s not the bottleneck:

Under the new system, a part that used to take 15 minutes at Resource B and 5 minutes at Resource C now takes 14 minutes at Resource B and 7 minutes at Resource C — one more minute, but one less minute where it counts.

A plant that has been producing 100 of Product P and 30 of Product Q can now produce the same 100 of Product P — that’s all the market demands — and 55 of Product Q.

Not bad for reducing effiency.

### Haystack Syndrome

Monday, September 3rd, 2007

When I recently read Kevin Fox‘s Blue Light anecdote, it spurred me to go back and read the stack of old Goldratt books I’d inherited. I loved The Goal, but, frankly, I wasn’t impressed with his Theory of Constraints (the book, not the idea), or The Race (which is little more than a proto-PowerPoint), or The Haystack Syndrome.

On the other hand, The Haystack Syndrome does have one good demonstration of Goldratt’s key point. Suppose we have a company that produces two products, P and Q, from three different raw materials and one purchased part:

How much money can our hypothetical company make in a week? Eyeballing the numbers, we see that it can sell 100 of Product P and 50 of Product Q.

Each P brings in \$90 but costs \$45 in materials, so it contributes \$45 to covering overhead. Each Q contributes \$60.

If we sell 100 of P, that’s \$4,500. If we sell 50 of Q, that’s \$3,000. If we then subtract out our \$6,000 in overhead from salaries and the like, that leaves us \$1,500 in profit.

Simple, but wrong — because we’ve ignored all our internal constraints. We can’t actually produce 100 of P and 50 of Q per week.

OK, so we produce some fraction of that. Naturally, we want to maximize the number of Product Q we produce; those are more profitable — \$60 versus \$45, 60-percent margins versus 50-percent margins.

Simple, but wrong again — because we’re still ignoring our constraints.

Well, how expensive are P and Q in terms of resources used? If we add it all up, each P requires 60 minutes of effort from various resources. Each Q requires just 50 minutes.

So Q requires less labor and less allocated overhead, too?

Sure, but none of that matters.

Our bottleneck is at Resource B. If we produce 100 of P, that uses 1,500 minutes of B’s time. If we produce 50 of Q, that uses another 1,500 minutes of B’s time. That adds up to 3,000 minutes per week, but we only have 2,400 minutes.

Our goal is to maximize the dollar throughput of our system, which means we need to maximize the dollar throughput of our bottleneck. In this case, our bottleneck is Resource B, so we need to look at the dollar throughput of producing Product P versus Product Q at that bottleneck.

Product P contributes \$45 for 15 minutes at Resource B. Product Q contributes \$60 for 30 minutes at Resource B. That’s \$3/minute versus \$2/minute.

There’s no comparison. Produce as much Product P as you can!

This may all be clear when you walk through a nice diagram, but imagine how a large organization tackles a problem like this. How is the sales team rewarded? Based on sales (revenue) over some threshold? Or revenue minus product cost (which includes labor and allocated overhead)? Or contribution margins?

### Blue Light

Monday, August 6th, 2007

Kevin Fox is a disciple of Eli Goldratt (The Goal) and an expert on his theory of constraints. As a young consultant he devised his Blue Light heuristic as a way to spot opportunities to create extra capacity on the plant floor:

The plant produces heavy metal bumpers for semi-trucks, and they had a major bottleneck in their welding department. Orders were backed up, and they were running at capacity around the clock seven days a week. The space in the plant was already tight, and they had plans to expand the building to add room for 3 more welding bays, doubling the current capacity.

The plant manager informed me early on that they were running at 93% efficiency in the department, basically telling me there was no room for me to help them improve. It was my experience that there was always at least 25% more capacity that could be exposed in any plant. Moreover, I was young and brash enough to tell this 30-year manufacturing veteran this and that sight unseen it was true in his operation too. He must have thought my math skills were pretty bad because he reiterated that they were already at 93% efficiency, so this wasn’t possible.

I wasn’t fazed and finally convinced him to take me out to at least look at the welding operation, since I had driven out to see them. Whenever I go out to look at an operation I had made the habit of formulating in my mind a simple picture or image of “what good looks like.” In other words, what you would expect to see if an operation really was working to its maximum performance capability. As I am a completely non-technical person the image I put in my head as we walked onto the shop-floor was “blue light”.

I was pretty sure that if the welding torch wasn’t turned on, emitting its funky blue light, that the welders couldn’t be welding anything. So I decided to look first for how much of the time there was blue light coming from each of the three welding stations. (Yes I know that even this is not yet the indicator of optimal performance, but as you will see, it was way more than good enough in this case.)

When we got to the welding area we watched for a few minutes quietly. The first thing I saw was one welder turning off his torch, taking off his protective gear and walking over to his buddy in the next booth. He waited until he got his attention and then he too stopped and took off his gear. Together they went back to the first guy’s booth and lifted the heavy finished bumper off the welding table and onto a pallet, and then put a new un-welded one from the queue onto the welding table. The other welder went back to his booth.

I then watched the first welder begin to peel the protective plastic coating off the bumper in the places he had to weld. It took a good bit of time picking with his fingernails to get it done. Then he grabbed the parts and clamped the onto the bumper, put on his gear and welder for no more than 30 seconds. before he was done. I looked at my watch, we had been there almost 5 minutes and he had welded for 30 seconds of it.

Meanwhile another welder had just returned to his empty booth pushing a trolley, which he used to jack up and move his finished pallet to the next operation. He returned after several more minutes and consulted his schedule to see what job was next for him to do. Of course it turned out to be the skid of bumpers located against the wall blocked in by two other skids he had to move. After finding the right skid he moved the two other pallets out, got his to his booth and then moved the other two back out of the aisle. All this time zero blue light.

He disappeared again with the trolley to go and get the parts he had to weld onto the bumpers from the store room, returning only several minutes later with them. Meanwhile the other two welders had repeated several times over the two-man bumper lifting dance described above. Just from this casual observation I estimated that the “blue light time” couldn’t have been more than 10% and was probably far lower.

As I watched all I could think about was “wow, did I sand bag this guy” (meaning the plant manager), I told him 25% more capacity. I missed it by one or two ZEROES! Just about then the plant manager turned to me and said something I have never forgotten. He said, “you see, they’re busy all of the time!” And he was right, the guys were working all of the time and working steadily and hard at that.

What amazed me is how the two of us could be looking at exactly the same things and see it entirely different. He had in his head an assumption of what good looked like that was based on the people being busy, whereas I looked at it from the perspective of the operation and the work it did, the blue light. His perspective totally blocked him from seeing any solution other than adding people, which was going to require him to invest in expanding the plant and worse still take months to implement during which they would anger more customers and lose hunderds of thousands in potential profits.

To make an already long story a little shorter, we ultimately brought them to implement a very simple solution. They had a summer worker in another department (a non-constraint area of course) who knew nothing about welding, that they moved into the department to be the “helper” for the welders. We gave him a simple image to know if he was doing a good job. We told him we wanted to see more and more blue light from the welders’ torches. His job was to lift bumpers with the welder, move pallets of bumpers around, stage the next jobs for each welder, and get all of the parts they needed ready for them. If he had extra time after this (which it turned out he did) he was to peel the plastic for the welder, and do anything else that would generate more blue light time.

In less than three weeks they had totally cleared the area of work-in-process. This big backlog shipped out along with the on-going flow that was coming to welding, producing a record shipping month. I don’t know how much capacity was actually created but it was more than enough to break the bottleneck, and if more had been needed it could have been generated just as easily.

What limits us as individuals and as organizations are the assumptions we hold, and are failure to recognize them as just that “assumptions” and not facts.

### The Personal MBA 40

Thursday, July 21st, 2005

Josh Kaufman has finalized The Personal MBA 40, the 40 books he thinks you should read to learn what you’d learn in business school (instead of wasting all that time and money):

1. Mastery by George Leonard
2. Now, Discover Your Strengths by Marcus Buckingham & Donald O. Clifton
3. Getting Things Done by David Allen
4. The 7 Habits of Highly Effective People by Stephen Covey
5. What the CEO Wants You to Know by Ram Charan
6. Profitable Growth Is Everyone’s Business by Ram Charan
7. On Competition by Michael Porter
8. Blue Ocean Strategy by W. Chan Kim, Renee Mauborgne
9. Seeing What’s Next by Clayton M. Christensen, Erik A. Roth, Scott D. Anthony
10. The Essential Drucker by Peter Drucker
11. First, Break All the Rules by Marcus Buckingham & Curt Coffman
12. The One Thing You Need to Know by Marcus Buckingham
13. The Essays of Warren Buffett by Warren Buffett & Lawrence Cunningham
14. Poor Charlie’s Almanack by Charlie Munger
15. The McGraw-Hill 36-Hour Course in Finance for Nonfinancial Managers by Robert A. Cooke
16. Essentials of Accounting by Robert Newton Anthony and Leslie K. Pearlman
17. The Goal: A Process of Ongoing Improvement by Eliyahu Goldratt & Jeff Cox
18. Lean Thinking by James Womack & Daniel Jones
19. The Substance of Style by Virginia Postrel
20. The Design of Everyday Things by Donald A. Norman
21. Economics in One Lesson by Harry Hazlitt
22. The Marketing Playbook by John Zagula & Richard Tong
23. Purple Cow by Seth Godin
24. Free Prize Inside by Seth Godin
25. The Art of the Start by Guy Kawasaki
26. The Bootstrapper’s Bible by Seth Godin
27. Crucial Conversations by Kerry Patterson, Joseph Grenny, Ron McMillan, and Al Switzler
28. On Writing Well by William Zinsser
29. How To Win Friends and Influence People by Dale Carnegie
30. Influence by Robert B. Cialdini
31. The Little Red Book of Selling by Jeffrey Gitomer
32. Flawless Consulting by Peter Block
33. Real Estate Principles for the New Economy by Norman Miller & David Geltner
34. Getting To Yes by Fisher, Ury, and Patton
35. Principles of Statistics by M.G. Bulmer
36. A Primer on Business Ethics by Tibor Machan & James Chesher
37. Brand New by Nancy F. Koehn
38. American Business, 1920-2000 by Thomas K. McCraw, John H. Franklin, and A. S. Eisenstadt
39. The Little Book of Business Wisdom by Peter Krass (Editor)
40. Re-imagine by Tom Peters