Valuing Lead Time
Valuing Lead Time
When do short lead times warrant a cost premium? Decision makers generally agree that short lead times enhance competitiveness, but have struggled to quantify their benefits. Blackburn (2012) argued that the marginal value of time is low when demand is predictable and salvage values are high. de Treville et al. (2014) used real-options theory to quantify the relationship between mismatch cost and demand volatility, demonstrating that the marginal value of time increases with demand volatility, and with the volatility of demand volatility. We use the de Treville et al. model to explore the marginal value of time in three industrial supply chains facing relatively low demand volatility, extending the model to incorporate factors such as tender-loss risk, demand clustering in an order-up-to model, and use of a target fill rate that exceeded the newsvendor profit-maximizing order quantity. Each of these factors substantially increases the marginal value of time. In all of the companies under study, managers had underestimated the mismatch costs arising from lead time, so had underinvested in cutting lead times.
Option-based costing and
the volatility portfolio
It has been clearly established that a cost premium for responsiveness may be justified for profitable time-sensitive products, and that this cost premium may suffice to render production in a high-cost environment competitive. Time-insensitive products considered in isolation seldom justify a cost premium, leading many decision makers to conclude that their production does not belong in a high-cost environment. This leads to a manufacturing-location decision in which profitable and time-sensitive products are produced in a high-cost environment and time-insensitive products are transferred to a low-cost environment. Responsiveness, however, requires a capacity buffer that provides the option to meet a demand peak for a profitable, time-sensitive product. Leftover capacity can then be ideally deployed to manufacture time-insensitive products to stock. We propose that the cost of the capacity buffer be considered as an option cost and assigned to the time-sensitive product: “option-based costing”. We then demonstrate use of demand volatility to create a portfolio of products that are time sensitive and insensitive to generate profit and increase competitiveness. Option-based costing combined with a volatility portfolio reveals opportunities to produce competitively in high-cost environments that have typically been considered unfeasible.
Competitive Manufacturing
in a High-Cost Environment
The special issue emerges at a time of intense debate concerning the role of manufacturing in the developed world. A general consensus that manufacturing strengthens the economy in which it is carried out and that innovation follows manufacturing combines with a recognition that manufacturing carried out in a high-cost environment must pay its own way, as governments and shareholders are not willing to make up for unprofitable activities. There is also considerable skepticism as to whether manufacturing has a role to play in a developed economy. In this lead article, we summarize the contributions to the special issue and the solution space that they provide in which manufacturing in a high-cost environment ends up being the low-cost alternative.
Valuing Supply-Chain Responsiveness
Under Demand Jumps
As the time between the decision about what to produce and the moment when demand is observed (the decision lead time) increases, the demand forecast becomes more uncertain. Uncertainty can increase gradually in decision lead time, or can increase as a dramatic change in median demand. Whether the forecast evolves gradually or in jumps has important implications for the value of responsiveness, which we model as the cost premium worth paying to reduce the decision lead time (the justi fied cost premium). Demand uncertainty arising from jumps rather than from constant volatility increases the justifi ed cost premium when an average jump increases median demand, but decreases the justifi ed cost premium when an average jump decreases median demand. We fi t our model to two data sets, fi rst publicly available demand data from Reebok, then point-of-sale data from a supermarket chain. Finally, we present two special cases of the model, one covering a sudden loss of demand, and the other a one-time adjustment to median demand.
Optimal Sourcing and Lead-Time Reduction
under Evolutionary Demand Risk
We develop a real-options model for optimizing production and sourcing choices under evolutionary supply-chain risk. We model lead time as an endogenous decision and calculate the cost differential required to compensate for the risk exposure coming from lead time. The shape of the resulting cost-differential frontier reveals the term structure of supply-chain risk premiums and provides guidance as to the potential value of lead-time reduction. Under constant demand volatility, the break-even cost differential increases in volatility and lead time at a decreasing rate, making incremental lead-time reduction less valuable than full lead-time reduction. Stochastic demand volatility increases the relative value of incremental lead-time reduction. When demand has a heavy right tail, the value of lead-time reduction depends on how extreme values of demand are incorporated into the forecasting process. The cost-differential frontier is invariant to discount rates, making the cost of capital irrelevant for choosing between lead times. We demonstrate the managerial implications of the model by applying it first to the classic Sport-Obermeyer case and then to a supplier-selection problem faced by a global manufacturer.
A Lean View of Lean
Over the past 40 years, Lean and the Toyota Production System (TPS) from which it originated have sourced much of the research on how to manage, improve, and connect operations. What began as a term chosen to highlight some salient characteristics of the TPS has evolved into a broad description of everything that improves operations management (OM). Yet, despite decades of effort, our two Forum articles show that scholars still do not agree on what Lean is. Should there be a difference between operational excellence (a general ideal) and Lean (a particular way to achieve it under particular circumstances)? When anything that improves OM and inter-operational connections is classified as Lean, do we lose sight of key tradeoffs that underlie competitive advantage? How do we reconcile Lean as operational excellence with the new appreciation of the value of “fat”—capacity or inventory buffers held to protect against variability or extreme events—under the current increase in recognition of the value of resilience in the OM community? Proponents of Lean claim that it has evolved much over the past 40 years, even apart from the TPS—but, in its evolution, when does Lean outgrow its name? In this editorial our aim is to be provocative and “stir the waters,” seeking to direct and deploy the energy generated by the exciting conversation started by these two Forum articles into a research agenda.
It May Be Cheaper to
Manufacture at Home
Conventional financial tools can lead to supply chain mistakes. Most managers use the discounted cash flow (DCF) model to help them make decisions such as where to locate a new manufacturing plant or whether to use a foreign or domestic supplier. But DCF typically undervalues flexibility—and as a result, companies may end up with supply chains that are low cost as long as everything proceeds according to plan but extremely expensive if problems arise.
De Treville, of the University of Lausanne, and Trigeorgis, of the University of Cyprus, argue that you can avoid this pitfall by complementing a DCF analysis with a real options valuation. This technique lets you put a dollar figure on flexibility in the supply chain and helps you assess the value of having direct control.
The authors explain how a real options approach helped the Swiss company Flexcell decide whether to locate a new plant at home or abroad. The CEO was able to show his board that the flexibility afforded by a factory near company headquarters would more than make up for the 15% per unit cost savings that would have been realized at a factory elsewhere. He also demonstrated that the costs resulting from a disruption to a Swiss plant would be much lower than those resulting from a disruption to a foreign plant. The decision to manufacture at home has paid off handsomely, especially in view of the uncertainties created by the current economic crisis.