As I mentioned earlier, I just read Eli Goldratt’s It’s Not Luck, and I found the concrete business solutions more intriguing than Jonah’s abstract and jargon-laden Thinking Processes.
As our story opens, Alex Rogo, our hero, has just turned around three companies — divisions within a larger conglomerate, really — and he has to take them from barely profitable to very profitable. They are a printing company, headed by Pete, a cosmetics company, headed by Bob, and a pressure-steam company, headed by Stacey.
The printing company prints cereal boxes and candy wrappers, and Pete has just turned it around by implementing the changes Alex learned about in The Goal — letting non-constraint resources go idle, reducing work-in-process inventory, elevating constraints, etc. At this point Pete is lamenting that his competitors have bigger, better, newer machines that have much greater economies of scale. (Hmm…)
At the cosmetics company, Bob has just turned things around by rationalizing his distribution system — just in time too, because the cosmetics industry is changing, and they’re expecting to introduce a new product line every year, which would be a disaster with three months’ obsolete product in the distribution pipeline.
Under the old system, even with three months’ inventory, with over 600 products, they were always missing something from a customer order, to the point that they were only able to deliver complete orders 30 percent of the time, and they’d have to ship missing items later.
Under the new system, they can respond to customers in one day, and they are able to deliver complete orders 90 percent of the time — all while holding just six weeks’ inventory in the system, half as much as before.
Under the old system, plants were treated as profit centers, and they recorded any production as a sale as soon as it was shipped to the regional warehouses, where it became somebody else’s responsibility.
Under the new system, stock stays at the plant, which acts as a central warehouse, with just 20 days’ stock at the regional warehouses, replenished every three days. This allows the plant to aggregate the forecast demand across all 25 regions — and when you aggregate demand across 25 regions, you do not get 25 times as much volatility (standard deviation); you get five times as much volatility. (Five is the square root of 25.) When demand is higher than expected in one region and lower in another, those errors cancel out — but only when aggregated.
Reducing inventory in the distribution pipeline doesn’t just reduce your carrying costs and obsolescence costs. When you have three months’ inventory in the distribution pipeline, that means you’re producing based on three-month-old forecasts.
Anyway, although the company has moved to its new distribution system, its customers, the shops, are still ordering in bulk, which puts a bigger strain on the system than if they ordered in smaller, more frequent batches.
Bob notes that they choose their inventory buffer size in the same way they’d set a buffer in front of a bottleneck in a manufacturing plant, based on expected consumption and expected replenishment time. What he does not mention is that real-life goods often have very different demand volatilities — or, more specifically, very different coefficients of variation of demand — so that 20 days’ average demand in one good may offer more than enough protection or far too little. Also, different goods present very different ratios of costs of overage (from holding too much inventory) to costs of underage (from holding too little inventory), especially when you realize that you’re not supplying independent goods but whole orders. You might want 99.9-percent safety on cheap parts that might hold up larger orders.
Which brings us to Stacey’s pressure-steam company. The pressure-steam company, like others in its industry, sells its pressure-steam equipment to manufacturing plants at cost, or thereabouts, and makes its money buy selling spare parts at high margins later — because the customers are locked in then. The pressure-steam company keeps the necessary spare parts at the client site, and it requires over 95-percent safety on those parts, because, when it needs a part, that means the client’s whole plant is down until the fix gets made. (Hmm…)
I wonder what the three companies will do…