Guide to Supply Chain Management Read online

  Figure 7.3 The prisoner’s dilemma

  Source: Author

  Similarly, in supply chain collaboration, trading partners can reduce inventory more through collaboration than they could on their own. However, if each party makes their own production and inventory decisions, they will forgo the chance to dampen the bullwhip effect. Theoretically, the ideal solution would be to assign an omnipotent player to gather and optimise information from all the players in the supply chain, and instruct all parties on how much to order and when to order it. This party would be in a position to ensure that optimal decisions were made, while the parties would not have to share their information directly with each other.

  Theoretically, the ideal solution would be to assign an omnipotent player to gather and optimise information from all the players in the supply chain, and instruct all parties on how much to order and when to order it. This party would be in a position to ensure that optimal decisions were made, while the parties would not have to share their information directly with each other.

  Lack of trust and failure to share the investment, risks and benefits of integrated SCM are significant risks for its otherwise bright future. Game theory can address and resolve some of the most difficult challenges in behavioural dynamics. Future applications of game theory should include:

  dynamic games (in which player behaviour adapts to the decisions that other players make over time);

  co-operative games (in which players pool risk to improve returns for all players) and how signalling (which gives players information about the intentions of others) affects supply chain efficiency;

  screening (one player moves first without information);

  bargaining.

  In the interim, supply chain relationships favour the partnership model. The transition from transaction supply chain partner to strategic supply chain partner progresses through three basic stages: first, transactional, where most interactions are data-driven; second, alliance, where the companies are engaged in one or more joint projects; and third, strategic partner, in which there is a documented mutuality of corporate goals and objectives.

  Companies and individuals that excel at relationship management will exert more influence over the extended supply chain and move from transactional relationships to strategic partnerships. Because of the increasing focus on dealing with external partners, facilitation skills will be essential. Leaders should establish a governance model; establish mechanisms to communicate each others’ goals and objectives; establish joint goals, objectives and metrics; share information, management talent and tools; and initiate joint kaizen (continuous improvement) projects.

  Shifting demand and capacity

  Demand is unpredictable in every industry, and demand that is unsatisfied at moments of high demand sacrifices sales. Capacity management techniques address these problems.

  When building or buying capacity, companies may: first, ensure there is enough capacity to handle the peak demand; second, build capacity for average demand and shrink or stretch when needed; third, build capacity for low demand and supplement frequently. In periods of shifting demand, companies choose between chasing (building capacity ahead of demand), levelling (building capacity ahead of current demand but below expected future demand) and following (building capacity after demand has been demonstrated).

  Thoresen, a Thai shipping line, doubled the number of ships in its fleet by buying ahead of the demand – and won. Given the cost of vessels (a second-hand Handymax vessel cost around $20m in 2005 before the rise in steel prices), buying ships is a major asset management decision. The management team decided to increase the fleet significantly as various signs pointed to a strong rise in its business, thus providing the company with adequate capacity to cement its market leadership on the Asia–Middle East trade route. As the price of steel soared after it purchased the ships, Thoresen was in a much stronger business position than most of its competitors, who expanded their fleets at higher price points.

  However, building capacity beyond or ahead of demand is expensive and risky. So how can companies assure adequate capacity at a reasonable price when demand is fluctuating? Assuming that building capacity beyond or ahead of peak demand is an unrealistically expensive option and cutting capacity is not a problem, there are three ways to provide additional capacity during periods of peak demand: shift demand with peak period pricing; add resources during peak demand; and reduce cycle time to increase throughput.

  Peak period pricing can shift demand away from the peak period by discouraging demand then. Time-based differential pricing encourages demand during a period when capacity is available and discourages it when it is not. For example, to solve daytime congestion of trucks picking up containers, the port of Los Angeles has instituted a programme called Pierpass that charges lower access fees at night. Shippers through the port have been doing more night and weekend deliveries as a result of the programme. Airlines also shift demand with yield pricing, but since this is commonly used in conjunction with stratifying customers into different classes, it is covered in Chapter 9. So-called yield pricing is not always easy to determine since it usually involves pricing at marginal cost for a given facility, time period or customer and many companies do not know their true marginal costs.

  Augmenting capacity during peak demand is a second way to make capacity flexible while deploying a minimum level of capacity. Both FedEx and UPS do this at their Memphis and Louisville hubs, respectively. They hire students who work part-time but can extend their hours during peak periods, which are often school vacation periods for them. They ensure the students’ commitment to work during the peak periods by hiring them when they enter school and sponsoring their tuition.

  Reducing the cycle time that it takes for customers or orders to get through the process can also increase effective capacity. In cyclical upswings, suppliers to the oil and gas industry encounter extending lead times due to intense demand, often driven by rising oil prices. They frequently engineer their processes to reduce the order cycle time in order to increase throughput. One American power equipment supplier does this on multiple components that its customers consider critical in their supply chains – such as motors, compressors and turbines – in order to create a competitive advantage based on superior end-to-end supply chain performance.

  No matter what capacity strategy is chosen, to be successful capacity management needs to be done in close collaboration with suppliers. FMC Technologies’ Kongsberg Subsea division in Norway makes production systems for the oil and gas industry. Faced with a huge increase in orders following the big rise in the price of oil in 2007 and 2008, it needed to ensure capacity from its suppliers, which had all been tapped out of capacity for the foreseeable future because of the strong demand for oil-drilling equipment. It established frame agreements with key suppliers which secured capacity and quality in exchange for a share of the relevant equipment that FMC Technologies bought.

  Better forecasting, less emotion

  Emotion plays a considerable role in inventory ordering decisions. Nobody wants to get caught short of product or services to sell when the demand is hot, so the natural tendency is to overorder when demand appears to be increasing. However, if five supply chain partners in succession each order 10% extra, the company farthest from the customer (usually the manufacturer) ends up with 61% extra (1.105).

  Thus reducing the emotional bias in ordering can generate substantial efficiencies. The greater the historical accuracy of the forecasting system, the more confidence inventory planners will place in it, and therefore the less emotion and bias they are likely to inject into inventory planning decisions.

  Numbers-driven forecasting methods fall into three basic categories:

  Time series methods are the simplest forecasting method, but are the least accurate. This is why investment funds consistently advise their clients that past performance of a stock does not determine its future price. Such behaviour leads to extended runs in the market and con
sequent overcorrection to get to the right valuations – the same problem as the bullwhip effect in the supply chain.19

  Causal methods are more accurate. Econometric models relate parameters such as leading indicators and underlying variables to each other with coefficients that are carefully studied and include iterative feedback loops.

  Market intelligence methods can add granular company-specific (bottom-up) information to demand, supply and inventory models. These methods are particularly useful in rapidly changing markets where day-to-day news and information may affect the market as much as the underlying fundamentals.

  Risk mitigation

  The bullwhip effect is when small perturbations at one end of the whip cause larger ones at the other end, so avoiding the perturbations in the first place is of paramount importance. Therefore, reducing the risk of supply disruptions is crucial if synchronisation supply chain strategy is to be successful.

  To achieve effective supply chain risk management processes, it is necessary to take all or whichever steps are relevant from the following seven:20

  Classify, measure and monitor risk. Understand the stakes, using real examples of what has happened and what could happen. Map the risks and their severity.

  Make a risk management plan. Define management principles and a process for dealing with the key risks, including goals, objectives and formalised organisational accountability for risk management. Establish risk management metrics and triggers that should stimulate action by managers.

  Avoid risk by reducing consumption or passing costs on to customers.

  Hedge risk by buying options (or similar forward contracts) or insurance, or by studying and anticipating market conditions.

  Diversify risk by buying from more suppliers and dual sourcing.

  Minimise risk by buying in advance at the current price and/or signing long-term contracts at forecast rates.

  Mitigate the severity of potential disruption and disasters through contingency planning.

  Classify, measure and monitor risk

  Classify risk

  Risks that could affect the supply chain come from a wide range of sources. Terrorism and natural disasters can lead to physical and property damage, and hence an inability to function. Changes in the regulatory framework can affect costs and prices, as shippers and carriers implement new compliance measures. Volatile demand can be hard to accommodate or may cause cyclical overcorrections, as happens frequently in oil and gas markets. Labour strikes can shut down capacity, as happens repeatedly in the transport sector in France. Reliance on single suppliers can restrict availability, drive up prices or limit innovation. Price risk – including interest rate risk, commodity price risk and exchange-rate risk – can increase the cost of goods sold.

  Demand risk, the risk that demand will change unexpectedly, is increasing, as products have shorter life-cycles and more competition is resulting in more new or updated products. In addition, increases in sales promotions and sales incentives are making it more difficult to manage reorder quantities for consistent replenishment.

  Most supply chain risk factors (see Figure 7.4) have a direct impact on cost or price. Some of them can decrease availability, which may affect revenue. Revenue increases are not always good, especially if they are being driven by rising input prices: both carriers and shippers got squeezed by rising fuel costs on the US–Asia container shipping lane in 2008. Cost increases can affect quality, as producers look to substitute materials for ones whose price has risen, and may opt for a less expensive but lower-quality input – for example, auto manufacturers substituting plastic for metal or vinyl dashboards.

  Figure 7.4 Supply chain risk factors

  Source: Author

  Mentzer has elaborated on the terrorism and natural disaster risks cited above in a “security risk cube” that classifies risks (Figure 7.5).

  Figure 7.5 The security risk cube

  Source: Mentzer, John T., Myers, Matthew B. and Stank, Theodore P., Handbook of Global Supply Chain Management, Sage, 2006

  Supply chain risk can be exacerbated by a wide number of company-specific factors. Highly specialised materials are more prone to price volatility since there are narrower markets for them. Long supply chains are more prone to the risk of congestion (which is a form of supplier capacity constraint) and, unless it is removed by hedging or fixed-price contracts, to price risk because of the time that passes between shipment and receipt of goods.

  Internal processes can make matters worse. Inflexible organisations take longer to respond, during which time prices may increase, materials may become more difficult to obtain, or quality problems may make their way through the supply chain to an unhappy customer. Flawed information systems or poor data quality make it difficult or impossible to be aware of supply chain problems. Managers at many large organisations do not have access to their prices, costs and logistical or production information. Finally, unusual customer sensitivity to price, quality or availability can make adjusting to supply chain disruptions more difficult.

  Lack of transparency in internal processes is a risk that is specifically addressed by the Sarbanes-Oxley Act in the United States and the European Union (EU) Company Law Directive in Europe. Although Sarbanes-Oxley leaves a lot of details unspecified, which has irked many companies, experts and lawyers since its inception, several supply chain aspects are important to note. For example, the act addresses the risk of invalid or improper accounting for inventory write-offs, price escalations in contracts, the promptness of posting of material acquisitions and transfers, lease obligations and contingent contractual obligations with suppliers (such as shared investment of shared risk clauses).

  Because of the failure of risk management that contributed to the global financial and economic crisis that erupted in 2008, subsequent legislation has encouraged companies to pay more attention to internal process risk. Under the Sarbanes-Oxley Act, long-term contracts and vendor-managed inventory (VMI) are both technically reportable off-balance-sheet transactions.

  Measure risk

  At a simple level, risk can be measured in categorical terms. Is the risk present or not (yes/no)? At a more complex level, ratings can capture a lot of the factors in an intuitive sense. The Economist Intelligence Unit and other organisations rate countries’ political and economic risk, and some consulting firms measure supplier risk in this way.

  Risk can be measured in terms of probabilities (see Figure 7.6). This approach is well-suited to relatively low probability events with high pay-offs, for example drilling for oil.

  Figure 7.6 Probability assessment of risk using Monte Carlo simulations

  Source: Boston Strategies International

  Risk is the possibility of an undesirable outcome, but there is always some risk, and no organisation will or should try to eliminate all of it, not least because of the insurance cost of so doing. If the oil firms were totally risk-averse, they would never drill for oil. Actuaries often quantify the odds that risky events will happen by using statistical indices. Consultants often use risk models to compare chances with the associated costs, for example the costs of exploration against the chance of a positive payoff, or the cost of avoidance or mitigation against the chance of a negative outcome.

  Monitor risk

  To manage risk, it needs to be transparent. Intelligence should be gathered at three levels: company-specific supply chain partners; industry-specific supply chain bottlenecks and opportunities; and economic opportunities and risks.

  Trading partner data should be managed in a database that is used to score and select suppliers based on ratings, qualifications, performance history, financials, and records of personal interactions and contract negotiations.

  Industry data should be monitored to identify risk factors and deal with them. Ongoing monitoring should include capacity utilisation and bottlenecks, order lead time, cost structures, productivity, prices and regulatory developments.

  Economic data should be monitored to identify the
potential for new markets and for broad-based changes in the composition of demand. Such data should include demand, growth rates, regional conditions, risk factors and the price of broad-based cross-industry input costs such as energy.

  Although early warning systems would not have prevented the massive 2004 Indian Ocean earthquake and subsequent tsunami, they could have allowed enough time for people to seek higher ground. This might have saved some of the 225,000 people who died in the disaster.

  The value of monitoring supply chain risk is exemplified by the case of a fire in a Mexican microchip plant that supplied both Nokia and Ericsson. The fire, which occurred in 2000, ruined thousands of chips destined for use in mobile phones built by Nokia and Ericsson. Nokia, which had a close relationship with the supplier, noticed the disruption in inbound supply immediately and used top management connections to assure its share of the limited supply of good microchips coming from the Mexican plant. In contrast, Ericsson did not notice the disruption until the delays halted its production, which cost the company $400m of sales, according to its claim in a subsequent lawsuit.21