Tag: inventory
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How Fat is Your Supply Chain?
An overwhelming number of products today fit into one of these two categories: configurable products or products with a fixed bill of materials (BOM). Configurable products are also called Dynamic Configurations. Fixed bill of material products are also called Static Configurations (typically for off the shelf products like pencils, shampoo, etc).
Companies offer configurable products to allow customers the luxury of mixing and matching feature choices in order to customize the products they want to buy. continue reading »
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The Myth of Build-to-Order
Are You Looking At Top Selling Choice Combinations Before Stocking Inventory?
In working with manufacturers of configurable products, we have never met one that did not claim that they only build to order. “We don’t build until we have an order in hand” they all say. At first we believed them. A whole generation of companies has been transfixed by Michael Dell. No finished goods inventory; don’t assemble the parts until you know exactly what the customer wants; get the cash before you build the product.
Dell can assemble a computer in three minutes. A truck or a backhoe takes a little longer. But the same ideas should apply! Right?
Dell builds computers for final customers who come to its web site or its 1-800 phone line. Most manufacturers of expensive, complex products are once removed from their final customers. Their immediate customers are dealers. Final customers go to distributors and dealers to buy backhoes, tractors, work trucks, lighting fixtures, industrial fans, and so forth. The “customer orders” that the manufacturers so proudly wave are not final customer orders, they are actually channel/dealer orders. (Okay, this is an exaggeration, some are actual customer orders passed through by the dealers.) And how do the dealers place orders? They guess. They choose combinations of 30 or more options based on their experience. One manufacturer we worked with kept referring to these as “Christian orders”. After a while we asked them what they meant by “Christian orders”. With a big smile they said “Oh, we just take them on faith.”
So the dealers order certain product choice combinations to stock based on their intuition, and those units sit on their lots until they sell. Sure looks like finished goods inventory. There is some ambiguity about who actually owns the inventory. The manufacturer will say that the inventory belongs to the channel or dealer, so it’s not my problem any more. The dealer will say that the manufacturer finances his inventory; some cases has to take back the units and give his money back if a unit sits too long. In any case, the manufacturer knows that the dealer is not going to order any more units while his lot is full of “stale inventory” or “lot rocks”. (See Chrysler’s desperate attempt to force its dealers to accept more cars in 2008.)
So Dell computers are built to order. (And now also built-to-stock for their new retail model for stores such as Best Buy and Wal-Mart.) Jumbo jets are also built to order. But most configurable products are still a combination of build-to-order and build-to-stock, with manufacturers and dealers playing hot potato with the inventory. This means that somebody should be looking at the history of what combinations sold in the past, and trying to make sure that the stuff that they build is the stuff that sells! Looking at the sales patterns and trends is a very fast, efficient and intelligent way to determine what to carry. This is a more reliable than believing in Christian Orders or relying on dealers’ intuition. The manufacturers should be giving the dealers guidance on what to stock and order based on their global visibility into sales and customer buying trends. Customers buy combinations of features, and they do this in predictable ways. Detecting and using the patterns can make inventory turn faster, even if, technically it doesn’t exist.
Does Your Inventory Look Like Jurrasic Park?
Does Your Inventory Look Like Jurrasic Park?
I was working with a industrial manufacturer who made construction equipment, such as diggers and backhoes. They had a beautiful park-like setting around their factory. Artfully placed on manicured lawns around the ponds and fountains were quite a few backhoes . It reminded me of Jurassic Park. We discovered later that these backhoes were a lot like the dinosaurs – they had failed to adapt.
The backhoes in the park, though attractively displayed, were really just inventory. Those particular backhoes were there because they hadn’t sold. We soon understood why. The backhoe had about 40 features that the customer could choose. One of these features was a cup holder for the driver’s cab. There were two options: a stationary cup holder and a rotating cup holder that could be stowed under the dashboard. If a customer order matched a unit on the lot EXACTLY, except for the cup holder, then their inventory control system treated the two configurations as different. A whole new backhoe was scheduled and built, while the one with the wrong cup holder continued to sit on the lot, exposed to wind and rain and interest charges. Now, probably they should not have had two different cup holders in the first place. But if they did, the cost of giving away a rotating cup holder instead of a stationary one (about $20) was much smaller than all of the costs involved in building a whole new backhoe. And if the customer wanted a rotating one, he could probably have been persuaded to accept a stationary one today instead of waiting 3 weeks to get exactly what he wanted.
Two different configurations of a complex product might be “almost the same”, or “very similar”, or “quite different”, or “far apart”. Can we quantify these common sense terms? Surely two configurations that differ only on a cup holder, out of 40 features, are “almost the same”. If we can measure closeness, then we can see when a configuration in stock is “close enough” to what a customer wants.
For two configurations to be close to each other, there shouldn’t be too many features with different choices. Furthermore, some features are more important than others. In a backhoe, the engine, hydraulics, and buckets are very important. The cab is quite important. The cup holder is not so important. So two configurations are close to each other if they differ on a small number of features that are not very important.
The criteria for what is important can be based on knowledge about the product and what it is used for, and also on the cost in relation to other features. So “close enough” depends on how many features are different and how important those features are,. There might also be a probability of acceptance that depends on how many features are different. This can all be formalized, and we can compute a number that represents the closeness. If we can measure closeness, then we can automate the matching of orders and inventory in a much more nuanced way than “the same” or “not the same”. For complex products that are built to stock as well as built to order, this can substantially reduce inventory holding costs by keeping the inventory moving. This is the key to inventory optimization.
Each of those backhoes in the park had a story to tell. Stories like: “I could have been sold in October of 2007, but I didn’t have the rotating cup holder. Or in January of 2008, but I had flip-guard feet instead of street-guard feet.
Someday my perfect order will come, I know it will.”
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Unlock working capital by reducing inventory
More than half of companies recently surveyed by Aberdeen Group reduce inventory as their top response to tough times. The study, “Inventory Management: Three Key Strategies to Freeing Working Capital,” points out that using the right technology to manage inventory levels helps provide firms with a competitive advantage during the downturn and positions them well for better times ahead.
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Q&A with John Sloan, former director, Jeep Brand Global Product Marketing
In today’s post, John Sloan talks about challenges dealers face in ordering inventory that best matches customer demand.
Emcien: Describe the Chrysler-Emcien initiative that examined dealers’ struggles with complexity in the ordering process.
JS: In a soft “push” market where volume is driven by heavy incentives versus the merits of the brand / model, managing cost is paramount. A key piece to focus on is product inventory. Dealers get roughly 60 days of no-interest floor plan. In a soft market, vehicles can easily sit for longer than two months before being sold, so it’s critical that vehicles be easy to order, stock and sell. Simple is better.
Emcien worked on a model to simplify the Chrysler PT Cruiser product mix. There were thousands of possible build configurations for the PT Cruiser, creating significant complexity for engineering and the assembly plant, as well as the supplier extended enterprise. Emcien’s ability to accurately forecast demand is invaluable for a complicated product line because it can assist with reducing the build configurations to those that best match demand. The PT Cruiser initiative validated the power of the Emcien inventory model.
When the tide goes out, it exposes products that were under water
The number of companies with complexity reduction initiatives has skyrocketed. Unlike five years ago, these are serious initiatives with management sponsorship and timelines.
A good friend of mine, who is a salesperson at a Caterpillar dealership, told me that when times are good he can sell any machine. When the times are bad, the bad stuff just sits around exposed.
Companies have proliferated their product offerings – there are almost infinite variations of everything that they offer. The rationale is that they will make one more sale because of that variation. But as product variations grow, the cost structure grows very fast as well, and the probability of finding that one customer who wants the new variation is quite slim. This results in excess inventory across the supply chain. And when the economic tide goes out, it exposes the cost of those product variations.
The companies with complexity reduction initiatives recognize that during good times and bad, managing product variants makes good business sense. Companies are now starting to implement metrics to measure product complexity because we all know that what gets measured gets managed! Product complexity metrics quickly expose underwater products.
The comment by my friend at Caterpillar reminded me of a trip I took to the Bay of Fundy. It is amazing how much is exposed when the tide really goes out, just like in this economy. The good news is that when the tide turns, the bad product lines it once covered will be significantly fewer, resulting in healthier and more competitive companies.
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Stop product complexity at the door
In any manufacturing company that builds configurable products, there is a lot of discussion around what product complexity is. What’s interesting is that when times are good and there are lots of sales, the discussion is usually around how to simplify or streamline with the goal to sell more product even faster, that complexity is keeping sales from going even higher. In bad times, the discussion typically moves to how complexity is causing undue stress on the supply chain, creating problems with parts forecasting, quality and finished goods inventory.
Rarely do these discussions end with participants really agreeing about exactly what complexity is or how to reduce it. Solutions are attempted with internal projects like SKU reduction and part number reduction initiatives driven by Six Sigma teams that mean well and do good work, but usually are chasing the tail of the complexity dog, rather than leashing it for good and guiding it to higher profits, lower forecasting errors, even shorter sales cycles.
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Why product complexity matters
I was telling some friends at a brunch about what I do, and how variety drives cost in manufacturing. “But all the manufacturing has moved to China,” commented one person. I’ve heard this comment over and over.
A picture is worth a thousand words — and here’s one that fits the bill.
- Commoditization of labor in manufacturing
- Higher output per worker
- The percentage of cost in goods is much higher
