After Katrina disaster last year and current increasing trend towards more complexity and uncertainty in supply chains, several solutions were suggested by consultancy firms and SCM experts, or let's say became highlighted (because they were already there !): Risk evaluation packages and lean supply chain solutions were among two most popular ones.

The question is: Do they really help us? In this post, I will look briefly at lean supply chain.

What caused the industry's $12 billion inventory overhang? Bad forecasting played a part. As did a build-to-forecast manufacturing model based on materials requirements planning (MRP II) principles. While MRP may have worked for vertically integrated manufacturers in slow-moving industries where demand was relatively constant, it never stood a chance in today's fast-paced, outsourced economy where demand fluctuates rapidly and product life-cycles are measured in months instead of years.

As long as companies continue to build to forecast using MRP II push-production methods, another inventory disaster is just a matter of time. Most companies are doing a better job keeping inventory in check right now because they were burned last time and senior management is paranoid. But it's not systematic. At some point another bubble will emerge, experienced senior managers will forget or be replaced, and disaster will strike again. It's only a matter of time.

A new point of view

John Rumasuglia from Extended Lean Solutions thinks Extended Lean Supply Chain may be a solution for that. In today's globally outsourced economy, competition is no longer company against company, but supply chain vs. supply chain. Companies that want to run Lean must learn to do it collaboratively, in groups. In a Lean supply chain, traditional forecasting and MRP production scheduling techniques are used only for planning - to run what-if scenarios and communicate trend analysis back to suppliers. But they are not used to order material or produce products. Only kanban signaling is allowed for that.

Kanban is a Japanese word that means "signal" or "billboard." It is the most fundamental concept in Lean manufacturing used to describe a material replenishment process in which every stage of production signals the one preceding it when more material is required or an act of production has been executed and a new one is ready to begin. Unlike MRP systems, which push material through production according to a pre-determined schedule that is based on a potentially inaccurate forecast, kanban is a pull-production process that is based on true customer demand. Kanban eliminates all but a small reserve of inventory or safety stock that functions as a re-order point while enabling the manufacturer to respond to unexpected surges in demand or interruptions in supply. When material drops below this re-order point, a kanban signal is sent to replenish it.

OEM executives love Extended Lean in a downturn because the only inventory in the pipeline (besides a small safety stock) represents actual customer demand. But how does a Lean supply chain respond during an upturn? Can Lean contract manufacturers and Lean component suppliers respond quickly to an unexpected upsurge in demand? Or will Lean OEMs find themselves stuck in first gear while competitors race ahead? In other words, how responsive is Extended Lean since, by definition, it must orchestrate complex activities across multiple tiers in a supply chain in which the OEM has relinquished centralized control?

It is a fair question, and until recently it was the Achilles Heel of Lean as it applied to outsourcing and supply chains. That is why most proponents of Traditional Lean sequester themselves within the four walls of the factory. Traditional Lean makes sense in a vertically-integrated enterprise, or within the confined space of a factory where managers can remove wasteful steps and redesign the lines. But Traditional Lean does not work in a modern supply chain. There is a need for using new tools like Statistical Kanban to apply it to supply chains.

What is statistical kanban?

The tool is developed by Gary Cortes and his colleagues at FlowVision:

"Statistical Kanban enables manufacturers to anticipate fluctuations in demand and meet virtually any guaranteed service level that a customer requires," says Cortes. "Let's say we have to carry some level of finished goods inventory to guarantee a specific level of service required by an OEM customer. This is inventory that the OEM has ordered and agreed to purchase. We can statistically determine the ideal level of inventory that is needed at each stage of the supply chain based on historical usage patterns and trends," says Cortes.

Statistical Kanban is used to guarantee a service level for which a customer is willing to pay. For example, FlowVision is working with a company in San Jose, Calif., that makes complex electronics-based systems with a long supply lead time and for which there is high demand. The company wants to guarantee that it can meet 99.7 percent of orders within a short delivery schedule. Using Statistical Kanban, FlowVision calculates the amount of finished goods inventory required to meet 99.7 percent of orders within that company's guaranteed time-frame. Using Statistical Kanban, the company guarantees that at most it will miss only 3/10ths of one percent of orders. Its customers are delighted with that level of service.

"In order to achieve that level of service, we need to have a certain amount of material in the pipeline," explains Cortes. "At a minimum, all of our components must achieve a 99.7 percent service level. When we statistically size the inventory, whether for finished goods or components, we mathematically calculate the variation in historical usage of those components and that finished product. We also look forward to account for any future anticipated changes in demand. Then we size the inventory to achieve a specific confidence level for which the OEM customer is willing to pay. Obviously, the higher the confidence level, the more inventory we will require, and the higher the cost to the customer. But the customer knows that up-front and can choose according to different scenarios. What is the financial impact of moving from a 99.5 percent service level to a 99.7 percent service level? With Statistical Kanban you can tell exactly what those additional two-tenths percent of certainty are going to cost."

Properly applied, Statistical Kanban is the key to implementing Extended Lean throughout a supply chain. Once the OEM, contract manufacturer and supplier agree on a guaranteed service level, they can mathematically determine the level of finished goods inventory. At that point, the only time they produce more of that particular product is when there is a signal from the distribution center or wherever the finished goods reside that the OEM has reached a re-order point. Then and only then does the supply chain produce more.

Says Cortes, "We still use forecasts to tell us where we think we're going, and we use MRP to establish our lead-time offset, so we know how long it will take to order, receive, build and ship a product, but we are not going to order or build anything unless the customer actually buys a product. It is a completely different mindset from how most manufacturers operate today, particularly in a complex supply chain where the OEMs talk to their sales guys, estimate demand, add a little extra, then buy material and fill up their finished goods inventory. And if the forecast is wrong? Hey, it's just another multibillion dollar write-off."