How do I re-size supermarkets when demand changes or to keep pace with seasonality?
Dear Gemba Coach,
How do I calculate re-sizing supermarkets when demand changes or to keep pace with seasonality?
There are two very different ways to look at this. The most common perspective I see on the shop floor is SAP thinking with lean tools. In this sense, the question is: we have calibrated our supermarkets and kanban cards for a certain level of demand, at which point has the demand changed so much that we need to recalibrate. The assumption here is that the pull system should work the most effectively way possible and tinkered with when conditions change. In this perspective, kaizen is necessary to keep the kanban working.
And then there is the path less travelled: using kanban as a tool for kaizen. It’s a question of perspective. Let me try and clarify, I’ve recently come across a 1970s story about Taiichi Ohno visiting a Toyota supplier to whom the company was buying seventy thousand parts per month. The plant manager tried to convince Ohno the company had enough capacity and manpower to cope with 100,000 parts if need be. “Then,” Ohno asked, “do you close your operations ten days a month since we are only buying seventy thousand parts?”
“We wouldn’t do anything that silly,” the man answered. “We are building a warehouse for the excess production.” Ohno then explained that if he built the warehouse he probably would lose his contract to Toyota since the additional overhead would make his parts too expensive. The idea, Ohno said, was to have only the equipment and workers needed to produce what was actually sold. Future production increases should be obtained by kaizen. (Against all odds, Togo & Wartman).
Although predictable lean gospel, this story struck me (the book is about Toyoda history, and this is the only mention of TPS) because it goes to the heart of the matter and it is still as relevant today as it was when it occurred in 1974. The size of a supermarket to make the flow work was never Ohno’s concern. His unique perspective was a keen sense that any unnecessary overhead added itself to the cost of making each product. In other words, it’s easy to resize supermarkets when demand increases – just increase them. Or when demand decreases, simply let them as they are.
Back at the Gemba, I know a service operation that needs a stock of service parts to supply maintenance technicians over a wide area. In the first year of doing lean, they divided the parts inventory by three mostly by isolating obsoletes. They realized in doing so that a small percentage of parts were used frequently out of the total of thousand possible parts in the catalogue. Without changing anything drastic, they installed a supermarket for high runners, which improved service OTD and reduced inventory. But then what?
The next step was to go all the way to the plan per part, a simple spreadsheet in which each part in the supermarket is defined by the vendor, minimal purchasing quantity, delivery lead-time from vendor and price. The vision was a sort of Amazon same-day delivery service: how could they purchase parts as they were needed by technicians so that they could be received singly in one day at a competitive price?
What came out of this hard work was a realization that the company wasn’t too good at:
- Estimating technician demand – the technicians often changed their mind while in the field about the number of parts they needed for one component, which made it difficult to procure and get it to them;
- Long lead-time from suppliers – some orders to vendors could take weeks before getting to the warehouse;
- Large packaging – many traditional industrial vendors would only sell the parts in large packages, which made the cost per part ridiculously low, but also created months of inventory of one part at any one purchase. This means that the cost per part is lower than purchasing a single part elsewhere, but the cost of the entire packet is much higher than a single purchased part (even though single purchase will be expensive), and the n-1 parts will sit forever on the shelves.
- Bad parts and other mistakes – typically, when one opens a large packet a high number of parts in there are of dodgy quality. When one supplies parts one by one, the reactivity on quality is much better.
TLC for inventory
The insight from this exercise was that the inventory was a living thing that needed tender loving care. So rather than adjust it when demand varied, the guys decided that they would re-simulate their inventory once a month using the plan by part to better understand how it behaved, and to learn how to better deal with specific items. The radical change of thinking here is that the monthly simulation of how the inventory behaves according to the expected demand conditions drives specific kaizen topics:
- How do we better understand field demand (there is seasonality), and do we have a plan per every equipment in the field?
- How can we get closer to a instant part by part supply?
- How can we further reduce the inventory and at what immediate price?
There is no set method to recalculate the supermarket of high runners. There is a monthly scratch-your-head exercise of looking at it line by line and wondering what we’re going to try with each part. There is no set formula, no function of lead-time and packaging size precisely because we want to challenge assumptions about procuring each component, not apply across the board formulae.
- Demand surprises, where the real demand is suddenly higher than expected and we’re short of parts, or when demand plummets and we don’t know what to do with the parts on hand
- Insufficient machine uptime (whether because of equipment or labor availability problems), making it necessary to produce ahead of demand
- Slow change overs, making it difficult to shift resources instantaneously from one component to another
- Large batches that multiply the lead time to get a component since time of production of A is non-production time for B, C, D and etc.
Internal supermarkets are regulated by kanbans, so the previous thinking applies: every month we look at part-by-part behavior and simulate how the kanban generates this behavior with the twin goals of no missed-deliveries while reducing the overall inventory.
Here again, there are several formulae to calculate the link between kanban cards and parts, and some are useful, but that’s not the point. The point is taking kanban cards out, reducing the supermarkets and identifying the resulting kaizen projects, such as:
- Better understand demand (and seasonality is part of this, we treat seasonality as a special customer which we can level through the year)
- Reliability of equipment in terms of quality and uptime
- Flexibility of equipment
- The internal logistics or running trains and issuing kanban cards
In other words: the usual suspects. To your question, I would not advise you to try and find a standard method to resize supermarkets according to demand changes or seasonality.
Lean Is About Leaning
I would set up a demanding monthly review board to constantly challenge how each supermarket works and push to reduce them (sure, in exceptional circumstances, we can extend supermarkets to fend off a crisis, but that is profoundly bad!). One of the main temptations of any pull system is simply to replace the existing MRP with a supermarket/kanban mechanical system without changing the underlying thinking. Lean is not a state, it’s a process: you’re never lean, you lean what there is.
Too many manufacturers put in supermarkets, kanban and trains, and think, “Hey, we’re lean now, what’s next?” Lean is about leaning, which is about having the discipline to consider the question you ask seriously on a regular basis, and use the size of supermarkets as a driver to kaizen deeper technical questions such as our understanding of customer behavior, our understanding of our technical skills and our ability to improve flexibility. There is only one way to resize a supermarket: cut it by half!
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Kanban functions as a trust machine because everyone using it must understand what they have to do and why, says Michael Balle: "Our purpose here is to share our ideas on what we believe is important in lean thinking."
The Sanity of Just-in-Time
Path dependence is the worst enemy of smart resolution, argue the authors, who suggest greater "frame control" with enabling tools such as just-in-time to respect people on the frontline and respect the facts they share about what is happening to them. "Mastering the path as opposed to being led by it, means looking up frequently to reevaluate both destination and way as new information comes to light."
5S, Hygiene, and Healthy Habits
5S-like practice can uncover hidden beliefs and misconceptions, and pave the way to adopting new hygiene practices – as opposed to arbitrary imposition, argues Michael Balle, adding: In this community, we, of all people, have been trained to do so. Now is the time to start acting on it.