The purpose of this study is to identify the need for improved supplier management in Lean Enterprises by identifying the types of variation that are currently considered. This includes a discussion of Supplier Response Profiles as a tool in long lead-time management, and a discussion of current practices used in industry. As Lean Manufacturing techniques continue to grow in popularity, one must recognize the strain that this puts on the supply chain in early stages of adoption. When a supply chain begins to adopt Lean techniques, a champion member of that value stream usually initiates the change. That company must learn ways to maintain its continued improvement while its upstream partners lag in their adoption, assuming that acceptance comes at all. This idea is examined first in this study.

One tool used for the management of this relationship is the Supplier Response Profile (SRP). This tool will be defined, and an example of its development and use will be provided. While this tool provides a means to manage one aspect of variation, a detailed explanation of the different types of variation will be presented in this study as well.

Finally, it is important to understand how supplier and long lead-time management issues are practiced in industry. This study looks at four entirely different approaches to this function of supplier management. This will provide a benchmark to understand common practices, and a means to identify problems with the adoption of theorized management techniques such as the SRP.

Increased Need for Supplier Management

One tool used for managing supply chain issues is often taught in conjunction with Lean Manufacturing techniques. This tool is commonly known as a Supplier Response Profile (SRP). As companies begin to adopt a Rate Based Planning (RBP) procedure for managing customer demand, the more important it will be for these companies to develop methods for managing variability in demand including the upstream flow of information to suppliers. One primary goal of implementing Lean techniques in a manufacturing process is to eliminate waste in order to reduce lead-time to customers. As downstream lead-time is reduced, the larger the risk for upstream orders is. For companies that must make commitments to suppliers before their customers commit, it is that much more important to understand the ability of the supplier to react to variation.

Exhibit 1 gives a visible description of this relationship. In the ideal world, every customer demand would be determinate or commitments would be made before raw materials had to be ordered from suppliers. This leaves the company with virtually zero risk in terms of commitments to its suppliers. In reality, companies must often use forecasting techniques to estimate the necessary raw materials for upcoming customer orders. As more companies adopt Lean techniques, this gap between supplier and customer commitments will likely continue to grow. This assumes that the company initiates the effort to implement Lean, and its suppliers lag in their adoption of the process.

Virtually all companies boast, or complain, about their ability, or inability, to forecast customer demand (naturally, the complaints are more common). These forecasts, in MRP based systems, are used to place orders to their suppliers to ensure material is available to meet their demand. While companies must continue to formulate forecasts as accurately as possible, they must also adopt procedures for flexibly reacting to deviations from the forecast. This includes the upstream communication of variability to their suppliers.

Traditionally, it has been common for companies to operate on a “get what we can” relationship with their suppliers. In such a situation the relative power bases of the company and its supplier tends to determine who assumes the risk due to uncertain forecasts. As the gap between supplier commitment and customer commitment continues to increase, steps must be taken to better manage the procedure for requesting increased or decreased quantities from suppliers based on customer demand. One such method for doing this is the implementation and use of Supplier Response Profiles.

Supplier Response Profiles

One primary goal for increasing service to customers is increasing internal flexibility. A company’s flexibility is limited in many facets by the capabilities of its suppliers to respond to variation. One tool for managing the relationship between a company and its suppliers is the Supplier Response Profile. The objective of this tool is not only to identify lead-times from a supplier, but also to establish necessary abilities to respond to variation generated by customer demand.

Consider the following example. A company provides a forecast of its expected order to its suppliers twelve weeks in advance. Rate Based Planning meetings with the supplier have provided the following agreements:

· At twelve weeks out, the actual production will vary from the planned production by no more than ⁺_-30%.

· The bounds will be tightened to ⁺_-20% eight weeks prior to actual production

· The bounds will be tightened to ⁺_-10% four weeks prior to actual production

· The planned production schedule will be frozen one week prior to actual production.

· The bounds will be updated only when the flex range changes.

Exhibit 2 provides a graphical solution for the generated SRP. (Example provided by Ken Gilbert, PhD, unpublished case study)

The SRP is an agreement between a company and its suppliers. Rather than providing the supplier with a given value, the goal is to establish a range for production quantities for future weeks. The range constricts as the time of production comes closer. The range is determined by the ability of the supplier to react to variations over time. If the company does not take advantage of the agreed upon flexibility, it may incur excess inventory or suffer from shortages (Costanza, 198).

There are essentially three periods identified on the SRP that are determined by the supplier’s ability to respond to variation. The first period is known as the Firm period. This period is identified as having no ability to respond to variation, and includes ship times, stable workforce, set schedules, etc. Second is the Flex Period, identified as the time needed to make minor changes in the schedule. A supplier’s finished goods inventory or flexible production capabilities account for this flexibility. Third is the Ramp Period, identified as the time needed to change workforce and materials requirements (Greenwood 2000, Lean Workshop III.ppt Ver. 02012001.1425ecs, 84).

Two Primary Forms of Variation

Supplier Response Profiles as they are used today help manage variation in orders as the due dates draw closer. However, the process of researching for this study identified two primary forms of variation a supplier can see from its customers, the latter being one. The other is the variation between orders. A brief example follows: this year’s demand for twenty-year-old Scotch Whiskey was forecasted twenty years ago. While an anticipated change in demand of 20% would not be difficult to handle if anticipated 20 years in advance, a change of only 5% would be difficult to handle if it came at the last minute. The factory could probably handle major swings up and down in the demand as long as the precise magnitudes were known in advance. However, even a modest unanticipated swing would leave the factory in a difficult position. This is due to the nature of the product. The distillery cannot go back twenty years and begin brewing more than what was previously expected. However, it would have much more flexibility to increase production by substantial amounts from one time period to the next time period, so long as 20 years of advance notice were provided.

Another function distinguishing the two forms of variation apart is the number of customers that make up a majority of the company’s business. As the number of crucial customers increases, the importance of between-order variation decreases. It is more important for suppliers with multiple customers to understand the impact of the aggregate demand fluctuating between periods rather than the importance of single customer variations between orders.

For example, Company X is the primary customer of Company Y - Company X generates 90% of Company Y’s demand. Company Y must pay close attention to fluctuations between orders from Company X due to the implications these fluctuations have on Company Y’s aggregate demand. These fluctuations could be the cause of rather drastic behavior by Company Y to rev-up or rev-down its capacity based entirely on variations in Company X’s demand.

In contrast, if Company X only makes up a very small portion of Company Y’s demand, and Company Y has no customer that makes up a significant percentage of its demand, then fluctuations in orders from Company X, considered individually, do not need to be considered as important to Company Y. Only when Company Y’s aggregate demand from its many customers swings up or down significantly, must it make plans to increase or decrease capacity appropriately.

Therefore, the importance of order-to-order, or between-order, variation appears to be a reflection of the nature of the supplier/customer relationship. As the number of crucial customers decreases, or approaches one, the more important it is for that supplier to recognize the importance of flexing its capabilities between orders. The obvious explanation for this is that the one customer is the aggregate demand in the first example, whereas the aggregate demand is made up of many customers in the second example. It is the aggregate demand that has direct effects on the supplier’s capacity. While SRPs serve the purpose of establishing the ranges that an order is allowed to fall between over time as it approaches the due date, they do nothing in terms of tracking or managing between-order variation. This is a possible area for improvement as the development and availability of operational tools for system management increases.

Industry Interviews

In order to better understand how variability should be managed, one is well advised to begin by understanding how variability is managed in industry. For the purposes of this study, build-to-order (BTO) and configure-to-order (CTO) product lines will be considered. A BTO business model exists when a company processes orders for their product before it begins to build the product. This differs from a CTO product in that a BTO has pre-existing models that can be ordered, where a CTO product is one that can be built from a pre-defined list of components that can be assembled in multiple combinations in order to create a unique model. In preparing for this study, a number of interviews were conducted with industry professionals to determine popular practices in dealing with long lead-time supply management. To narrow the scope of this analysis, companies that have recently implemented or are in the process of implementing Lean Manufacturing practices were targeted for interviews. The goal of this section is to provide a benchmark against which industry professionals can determine the best practices for the use of Supplier Response Profiles.

Company A

The first example will be referred to as Company A, a component part supplier for OEMs that manufactures on a build-to-order basis. Its process includes parts manufacturing/stamping, contact machining, and a two-step assembly process. This company is in the process of implementing Lean in their manufacturing processes and has made initial efforts to communicate these changes with their suppliers and customers. In this process, an effort to adopt Rate Based Planning (RBP) procedures has been made. RBP is a method for managing short-term variations in demand. This includes the development of Planning Bills of Materials and rate-based schedules and sequences. This is done by identifying tiers of product demand (A, B, C analysis) and mixing the production schedule to provide the best solution for managing customer variation (Tom Greenwood, Lean Enterprise System Design Institute RBP0100, 29). One component of these procedures is the development of Supplier Response Profiles.

The goal of Company A is to reduce its promised lead-times to its customers from eight weeks down to two weeks. The Supply Chain Manager for this plant noted that multiple supply parts have longer than eight-week lead-times. As this plant continues to reduce its lead-times and approach their two-week goal, it will experience an increased risk – committing orders to its suppliers long before it receives commitments from its customers. This causes an increased need for an accurate forecast. Unfortunately, forecasts are never correct, and the company must counteract variation with good management techniques.

One primary effort that has been made by this plant is participation in customer and supplier sessions. This has led to the development of Supplier Response Profiles jointly with its customers. They have also allowed suppliers to develop their own Response Profiles. While these efforts have been made, there is still no formal usage of SRPs in daily operations even with these suppliers and customers.

“Conceptually, they are the right thing to do,” stated the Supply Chain Manager, “but they require people resources and system resources that just aren’t available. Especially in these economic times, it’s not realistic to acquire new personnel to manage this added function.” Rather, Company A operates on a “get what we can” relationship with its suppliers, with no generally accepted rev-up or rev-down allowances. This manager feels that “the forecast is crucial. We need to reduce variation upfront.”

Company B

The second example is that of an OEM of trailers who direct sells its product or deals it through an independent dealer. Unlike the previous example, Company B operates under an engineer-to-order business model. Here, there is only one supply product that represents a problem with lead-time issues. Aluminum is bought six months in advance, and is put through a extrusion process that lasts six to eights weeks. This is done while promising a four to six-week lead-time to its customers. This has led Company B to develop a hedging program that is based on historical data.

This Aluminum is purchased on the commodities market. The goal for engineering is to get the lightest weight trailer with the most cubic feet. This presumably meets the company’s need in taking out cost and the customer’s needs in reducing the cost of hauling a specified number of ton-miles. Knowing the specifications for these trailers allows the supply chain specialists to transform weight into Aluminum demand. If variation away from the forecast exceeds the supplier’s ability to rev-up, the manufacturer is forced to purchase its Aluminum on the open market from another customer of the supplier at a higher cost. There is also the threat that these other Aluminum customers will not have excess inventory that they can spear. For this manufacturer, this has only occurred about a half-dozen times in the past four years. While Aluminum causes a huge supplier response issue, every other of Company B’s supplier lead-times fall within the four to six-week lead-time that has been set for its customers.

Company B and its suppliers have unofficially agreed upon a forty-percent rev-up/rev-down allowance with very little regard for the due date. The determination of how much advance is needed for this rev-up or rev-down is based on the availability of the Aluminum. Thus far, there have been no incidents of missed orders due to insufficient notice for increased or decreased demand. This variation allowance is very tentative, and is in no way considered a guarantee for either the supplier or the customer. While this company’s representative believes that SRPs are a useful tool, and would prefer to use them in making operational decisions, “upper management has decided not to use [supplier response profiles].” This is most likely a reaction based on the type of variation that this company typically sees. As previously mentioned, SRPs provide a boundary by which an order can change as it approaches its due date. According to the company representative, very little variation occurs within an order once it is placed due to the highly engineered nature of the product. However, cases exist on highly engineered products where the customer assumes they can continue to refine the order, both in quantity and specifications, until the order ships. A more likely need for this company would be a tool to judge variation between orders.

Company C

The third example that will be presented here is that of a large, multi-national paint manufacturer, known here as Company C. A large part of this company’s business comes from store sells, but a portion of their business is considered build-to-order, or “make and ship” as they call it. Their primary lead-time problems stem from their metal can suppliers; a special can that has the label printed directly on it, called lithographed packaging.

When asked if variation from its customers affects the plant’s service level, one VP of Operations stated: “It doesn’t affect our service level, it affects our WIP.” This means that the company is willing to incur the expense of high WIP to maintain its high standard of service level. The nature of the product has more affect on the variation seen at the plant than that which is caused by the customer. The rules that have been set are very different for this manufacturer’s customers, than those set by its suppliers. The company states that it allows for customer variation up to the moment before an order goes into the tank – it allows same change thirty minutes prior to mixing as it would two weeks prior. A lower limit always exists due to the batching process (E.g. a customer cannot change its order to one can), but the company tries to “maintain its customer focus at all times.” While large variation is allowed downstream to its customers, the company’s lithographed can supplier has set a plus or minus ten-percent allowance in variation in orders.

Company C does not subscribe to the use of SRP at this time. Currently its rules for rev-up/rev-down is based strictly upon previously agreed upon ranges of variation without regard to the notice interval, assuming that the change is made before the order goes into the tank for mixing. Due to the large amount of this company’s business that is build-to-stock, it is more likely that variation can be offset by filling days with a variety of order types. This is similar to the traditional ABC analysis. “A” products being the BTS paints that are a majority of this company’s business. “B” products are low demand BTS or high demand BTO products. “C” products are the low demand BTO products. Having a variety of products allows for RBP efforts that reserve a certain amount of capacity for each product category. By smoothing the demand for products, this allows for less variation, and the ability to counteract variation with other variation in the opposite direction.

Company D

The fourth and final example is that of a large manufacturer of government equipment – primarily aircraft production. Company D has served as an Industry Co-lead in the MIT Lean Aerospace Initiative (LAI) Supplier Networks since 1994. This industry is very different from the previous examples in terms of the lead-time issues that it faces in its operations. In terms of the supplier lead-time issues that it faces, some are controlled by the government. This leads to very little leverage to affect these lead-times. An example that was provided follows: an explosive devise that is used to eject the canopy of an aircraft. This product had to go through a government test site that boasted a six to nine-month lead-time. A similar issue exists with radar equipment.

Company D has many years of experience in the development of Lean systems and has used this experience to create ways in which to improve their supplier relationships. This study was provided detail of five initiatives that have been taken to improve supplier responsiveness to variation:

· Lean Engagements – This company has completed sixty of these three to five-day events to date. The process includes the detailed value-stream mapping of the supplier’s processes (usually for one product line at a time). The facilitating team baselines the process and identifies wastes. The overriding goal is to reduce lead times and create cost savings for their suppliers. Over the past six events combined, a forty-four percent reduction in lead-times, and a sixty-percent in administration time have been accomplished. This company will host multiple events for the same supplier, but their goal is to have their suppliers become self-sufficient in identifying and implementing these processes.

· Right-to-buy Contracting – Company D will negotiate contracts for its suppliers, in order to allow them the right to buy on the quoted price and lead-time. Due to Company D’s size and market presence, it is much easier for it to leverage suppliers for reduced prices and lead-times. An example follows: Both Company D and three of its smaller suppliers use steel. Company D approaches and negotiates a price and lead-time from the steel supplier. The terms of the contract will allow for the three other suppliers to buy at the same price and lead-time as would be provided to Company D.

· Purchased time – Company D purchases an amount of its supplier’s time, guaranteeing them a specific amount of their suppliers resources.

· Supplier Capacity Management – Company D’s buyers keep detailed capacity charts of distributors and machining houses. This allows the buyers to distribute orders across multiple suppliers of the same product, in order not to overload one and cause lead-time issues. This distribution of orders across suppliers is determined by actual piece volume and percent of capacity. The former rather than the latter is generally how a determination is made.

· Internal Value Stream Mapping – Company D has restructured to standardize terms and conditions of its supplier contracts. General contract certificates are available online. A move toward online order processing has been made, creating a standardized PL for all three sites. Company D is also using advanced radio frequency and bar-coding technology. As products are received at plant locations, the transaction is logged, the supplier is immediately paid, and the inventory is updated.

By working proactively with its suppliers, Company D has been able to make significant headway toward lead-time issue resolution. However, not every company operates in the low variability market of government contractors. While Company D’s efforts to help suppliers improve their processes is very impressive, the lack of short and medium-term variation in its demand probably has a positive impact on their ability to focus on these efforts.

Conclusions

The purpose of this study was to identify the need for improved supplier management in Lean Enterprises by identifying the types of variation that are currently considered. This included a discussion of Supplier Response Profiles as a tool in long lead-time management, and a discussion of current practices used in industry. After identifying these types of variation, one can see the possible need to develop a tool to manage between-order variation along with the within-order variation. While SRPs provide a means to manage the latter, nothing formal has been written or developed to provide a tool for managing the former.

This is most likely a result of the supplier/customer relationship. As mentioned earlier, it is less likely to impact a company with no dominant customer if one customer’s order due eleven weeks from now is a 50% increase from its order due ten weeks from now. As the number of customers increases, overall variation as a percentage of the mean decreases for the supplier, meaning that the variations cancel one another out leaving the supplier with little concern over the necessity of an overall capacity increase. However, if this were the only customer of the supplier, this would require a 50% increase in capacity for the supplier. This relationship is rare, which is the most probable reason for there not being more done to manage this type of variation.

Overall, there are many practices being performed by industry professionals to manage supplier response issues to variation. While a company must find the best technique for itself and its suppliers, it appears that the implementation of many procedures may be necessary. With most companies having a broad range of suppliers in terms of size and capabilities, there is no one step solution that will provide the best answer. Rather, continuous and conscious efforts must be made on a daily bases.

Annotated Bibliography

John R. Costanza, The Quantum Leap . . . In Speed-to-Market. Mr. Costanza is an internationally recognized author, educator, advisor, and designer of the Demand Flowâ Technology. At the forefront of this strategic management technology, he pioneered a new generation of manufacturing systems. He continues to direct DFT implementations throughout the world.

Kenneth C. Gilbert, PhD, Unpublished case study. Dr. Gilbert is a Professor in the Management Department at The University of Tennessee. He is a lead faculty member and previous chairman of the Management Science Program within the College of Business. Dr. Gilbert's research and consulting interests are focused in the areas of production management systems, inventory control systems, supply chain integration, and lean manufacturing. He has worked with numerous organizations, including PepsiCo, Inc. and Georgia Pacific.

Thomas G. Greenwood, PhD, Lean Workshop III.ppt, Ver. 02012001.1425ecs. Tom Greenwood is Director of the University of Tennessee Lean Enterprise Forum. Dr. Greenwood formerly served as the Director of Global Manufacturing Systems for Carrier Corporation in Syracuse, New York. As Director of Global Manufacturing Systems he was responsible for the implementation and continual improvement of lean production systems for more than forty plants worldwide. He has consulted with numerous organizations in the areas of time-based competitiveness, just-in-time production methods, total quality management and process simulation modeling. Dr. Greenwood has conducted seminars and published articles in both academic and professional journals on implementation strategies for deploying lean production concepts and using activity-based models to improve business processes.

Greenwood, Lean Enterprise System Design Institute. Presentation RBP0100, slide 29. The focus of the Lean Enterprise Systems Design Institute is on improving competitiveness of products and on enhancing long term profitability by redesigning business processes to achieve drastic improvements in the value delivered to customers. The Lean Enterprise Systems Design Institute provides a blueprint for building a lean enterprise focused on the entire value stream - from suppliers to customers.

Appendices

Exhibit 1

Exhibit 2

Week #	1	2	3	4	5	6	7	8	9	10	11	12
Upper Limit	13	14	14	14	14	14	14	14	15	15	15	15
Base Line	13	13	13	14	12	12	12	12	12	12	12	12
Lower Limit	13	13	13	13	10	10	10	10	9	9	9	9