By Colin Kessinger, founder, Vivecon Corp

The fabled bubble of the last millennium culminated in leadtimes extending from weeks and months to months and quarters on a broad range of components, component markets going into allocation, and prices reaching all-time highs for many commodities. Not getting the parts created an immediate problem. Having leadtimes extend by months created a longer lasting problem. In some cases, suppliers required significant volume commitments over a longer horizon in exchange for favorable allocations in the near-term. With commitments to your suppliers for up to 6 months of forecast, a 50% drop in demand results in a pipeline of one year’s worth of material. Unfortunately, some businesses made even larger commitments and/or saw declines well in excess of 50% for some products, resulting in years of inventory. A good portion of the excess inventory generated in 2001 as forecasts crashed will never be sold. Another significant portion of it was sold at 20% or 30% of its original value. As the next upturn approaches, the burning question is how to structure relationships with suppliers to secure the requisite capacity without the exposure to the horrific downside.

Maximizing continuity of supply in tightening supply markets relies on two fundamental efforts, 1) ensuring that your supply base could respond, and 2) ensuring that your supply base will respond. That the supply base can respond is a function of the quality of information that is shared. That the supply base will respond is a function of the control over the assets that you have in your supply chain. Both are a function of having business and financial objectives aligned across the supply chain. Structured contracts provide the necessary information, control, and alignment to drive the necessary investment in capacity and inventory to meet the upside, while balancing the buyer’s and supplier’s cost structure and risk profile in the flat or down markets. Unfortunately, there are several current practices that work in conflict to this.

The first of these practices is that in most procurement organizations price is the dominant metric. This immediately has three negative effects from a continuity of supply perspective. First, many suppliers may extend leadtimes to compensate for the lower price, or will invest in less inventory or capacity to respond to upside demand. Second, in markets where prices rise in response to short capacity, the gains from your price reductions are immediately eliminated. Even worse, buyers may receive eleventh hour messages from their supplier that a higher-paying customer will receive their parts. Third, instead of raising the price in tight markets, some suppliers find it easier to extend leadtimes, explicitly reducing your flexibility, which both diminishes your upside continuity of supply and increases your downside exposures.

The second such practice is the expectation that visibility, both ways, will address these issues. One form of visibility is the sharing of forecasts. While this is important information, it is fairly limited in ability to help suppliers respond to upturns. For starters, the forecast is a business decision as much as it is a communication about the upside and downside potential in the market. There always is the question as to whether the forecast is a conservative or aggressive plan relative to the “real” forecast. Left to their own devices, the supplier may be considerably more cautious than the buyer would want, and prepare to hit only the plan plus a small upside. Second, as markets become constrained, buyers start to inflate their forecasts. Of course the supplier knows they are inflated, but has no idea by how much. So they discount them. It is not surprising that more formal contracts, in lieu of shared forecasts, emerged as a necessity during periods of constrained supply. Turning to visibility in the other direction, providing the buyer with upstream visibility, is very valuable for near-term execution, but is quite limited for medium-term planning processes. This is largely because it is a snapshot of a dynamic landscape over which the buyer has little formal control. The fact is that capacity is so dependent on mix, and that the suppliers’ other customers are changing their volumes and mix as often as you do.

The third such practice, “flex-fences”, is barely a practice because of its lack of operational adoption. The very fact that it is barely made operational is evidence enough that it does not solve the problem. However, even if they were made operational, they would run in to two major problems. First, they assume that all parts require the same level of flexibility. In practice, having evaluated this at many companies, different parts and products have very different flexibility requirements. Second, flex-fences assume upside and downside requirements remain constant through the business cycle. Common sense says that there is more downside when demand is at historical highs than when they are at historical lows. The same can be said for upsides. Finally, flex-fences work against most efforts to manage flexibility and risk because they provide the illusion that the problem is solved and, worse, that the problem was solved with a simple, one-size-fits-all, “evergreen” solution.

Now we can turn our attention to structured contracts. In order to solidify the communication between buyer and supplier, there are five essential questions to address when designing a contract to manage supply risk and flexibility. These are outlined in Figure 1. Note that in this example, the pricing for the 3-month leadtime, the 1-month lead-time and the firm commitment can vary. This is, in part, to emphasize that the supply “service” is tied both to delivering a quality part, and the leadtime with which it is delivered. Naturally, the buyer pays more for better (shorter leadtime) services. Additionally, the contract should prescribe and enforce reasonable consequences for non-performance. In the example shown below, the supplier penalties act as credit that the buyer can spend to fix the problem. For example, the buyer may ask the supplier to hold FGI, paid for by the credit, until the supplier demonstrates that the assurance of supply (AOS) problem is addressed. Additionally, the buyer’s firm commitment and penalties essentially cover the long leadtime raw materials that the supplier purchases, to provide assurance of supply. Finally, all of the terms are specified as quantities, not percentages relative to a forecast, for all of the reasons that we discussed regarding flex-fences.
You may claim that your business is too volatile to specify hard numbers, but a well-designed and managed contract will provide all of the flexibility your dynamic business needs.

Figure 1

In terms of actually specifying the terms of the contracts, there are three primary inputs: 1) commodity, product, division, and corporate business objectives, 2) range forecasts, and 3) supply chain maps. It should be obvious that the business goals must define your flexibility requirements. Unfortunately, in most cases, the business objectives are only connected at a high, vague level, and forecast accuracy is linked only conceptually, but not supported by data. What we see is that regardless of the targets on market share, service levels, or profitability, the flexibility terms remain the same.

Similarly, it should be obvious that your forecast accuracy also should define your flexibility requirements. Figure 2 provides a clear illustration of the importance of understanding demand uncertainty. The ability to identify fundamental floors, opportunities for significant upside, and the amount of advance warning in hitting either of them will drive the kind of contracts that you sign. Just as most investors balance their investments in longer term investments to generate higher returns (like mutual funds and maybe stocks) and shorter term investments (like cash, CD’s, or some bonds) to have access to cash to meet life’s unpredictable needs, a buyer’s portfolio of supply resources should incorporate less expensive sources for the stable part of demand, and more flexible, but expensive, sources for the unexpected events.

The supply chain maps chart the physical and financial constraints in the supply chain that will ultimately determine the “investment” options that the buyer can access. For example, a heavy assembly built in Asia and integrated in the US almost surely will rely on ocean freight for day-to-day needs to control costs; hence, a built-in 6 week obstacle. However, this may be supplemented with limited air freight support for short-term responsiveness. Given the cost differential, how should inventory be staged to support this hybrid strategy? Similarly, ASICS have leadtimes that can extend to four to six months, but inventory can be staged in die-banks to reduce the inventory risk in the supply chain. Of course, the material in the die-bank is application specific and the supplier will require a firm commitment for its consumption. What is the right trade-off between die-banking and regular orders?

In short, securing capacity to meet the upturn is a four-step process. The first step is to understand your requirements, by defining specific commodity and product business objectives and by carefully analyzing both your historical forecast performance, as well as upcoming market dynamics, to create a range forecast. The second step is to understand the current and potential constraints in your supply base and explore opportunities for mitigating them. The third step is to evaluate each of the alternatives against each of your objectives by quantifying their performance and the different risks that they create. And finally, the fourth step is to ensure that the supplier can and will perform to these expectations, by providing the necessary information and incentives. While this seems obvious (and it should), for most organizations it is a significant shift to quantify and act on forecast error information, specify explicit and detailed performance expectations through contracts, and rigorously quantify the performance and risks of different contract terms.

 



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©2004 ChainLink Research, Inc.