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      Artikel

      The Complexity of Managing Complexity

      The Complexity of Managing Complexity

      More discriminating customers are forcing proliferation of product types and demanding service through more channels than ever. For suppliers, managing SKU profusion means more than just trimming fat.

      Von Miles Cook

      • Min. Lesezeit

      Artikel

      The Complexity of Managing Complexity
      en

      More discriminating customers are forcing proliferation of product types and demanding service through more channels than ever. For suppliers, managing SKU profusion means more than just trimming fat.

      In a recent survey by Bain & Co., two-thirds of executives said supply chain improvement initiatives and investments in systems are top corporate priorities. Successful initiatives have cut total supply chain management costs up to 50% and improved performance on inventory turns up to 100% among top industry performers.

      Advancements in Web-based optimization have convinced many executives that the time for breakthrough performance improvement is now.
      As companies are gaining experience with these initiatives, they are finding there is more to a solution than just installing software. Real gains depend on substantial changes in operating practices. One practice presenting challenges in supply chain is complexity management.

      Complexity in this context refers to proliferation of individual items, either in input components and subassemblies or finished goods. Excessive item counts can bring a supply chain improvement effort to its knees.

      Impact of SKU proliferation

      In production, SKU proliferation will lead to frequent setups and short production runs, driving up manufacturing costs. But there are more subtle impacts on supply chains. Proliferation of SKUs can cause difficulties in forecasting sales volumes and increase transportation costs.

      For example, one manufacturer of electronic products sought to improve accuracy of forecasted component requirements. One option was to use a Web-based software tool to link the manufacturer's forecasters with its suppliers' factories.

      But across almost 200 different finished goods, almost no commonality of board designs or component inputs existed. Therefore, the manufacturer's purchasing group had to prepare component-level requirement forecasts for approximately 3,000 different SKUs. A shortage of any one of these components could bring production to a halt. Yet there were simply too many components and vendors involved to permit any kind of rigorous analysis predicting demand or any real collaboration with suppliers on forecasting. To improve accuracy of forecasts, the manufacturer first had to reduce complexity.

      Similar problems with forecasting, due to SKU complexity, can arise in retail settings. Analysis at a major retail client showed that forecasts were four times less accurate at the SKU level than at the category level. Predictably, categories with greater numbers of SKUs had the worst overall performance in forecasting. Forecast errors in some of these lines were seriously degrading fill rates and customer service levels and significantly increasing supply chain costs.
      Unfortunately, companies commonly react to complexity by creating excessive safety stock, driven by uncertainty in demand at item level. In industries like electronics, the carrying cost of holding extra inventory can be 60-80% per year.

      Certainly, missed forecasts can result in high-cost freight expediting. But complexity can impact transportation costs in other ways. Item proliferation can lead to fragmented inbound materials deliveries (if production components are not adequately standardized). It also becomes more difficult to track cube size for each item. This results in load managers under-loading trucks because they have to allow a buffer for times when the size data is inaccurate. After implementing a complexity reduction effort, some companies have been pleasantly surprised with a 5-10% reduction in transportation spending.

      Complexity also causes difficulty in migrating to more advanced build-to-order supply chain structures. If component inputs are different across lines, it may be impossible to handle all the setups associated with build-to-order at a competitive price. In the case of one auto manufacturer, production steps like painting were huge economic barriers to a build-to-order move. The company's designers were offering 14 variations of white across the company's line. This was acceptable in a build-to-stock environment, but in the build-to-order world, such complexity leads to paint runs of just a handful of cars. That's impossible to execute competitively.

      Not as simple as just dropping SKUs

      It might seem the answer to all these problems is to narrow component selection and finished goods offerings to just a few items. After all, manufacturers frequently hear that 20% of products account for 80% of sales. But the answer is not so simple. If not managed carefully, the same steps that may help simplify the supply chain can more than offset that benefit by reducing revenue.

      Consider the high-tech hardware manufacturing sector, which suffers frequent supply disruptions. In one study, Bain & Co. discovered supply disruptions in 70% of input components for a typical desktop computer over a year. A range of factors can create long lead times and limited allocations for specific components. Examples include cyclical capacity shortages (notorious in memory chips), technology schedule slippages (for new CPUs, for example), and regional crises at suppliers, such as the earthquake in Taiwan that affected many categories of supply. If alternatives are not available in these cases, the financial implications can be devastating. A $2 capacitor in short supply can prevent production of a critical video card which, in turn, holds up production of a high-end workstation. Supply disruptions have cost high-tech OEMs hundreds of millions of dollars in foregone profits.

      This is the flip side of the argument above, in which reducing component complexity helps improve requirements forecasting. In a situation where the availability of supply may be disrupted, it might be worth suffering costs of less accurate forecasts to get availability insurance from qualifying a broader list of suppliers. Indeed, supply stability for select components may be worth more in revenues than it costs in lost simplicity.

      Another situation where complexity may pay for itself is consumer sales. Here, SKU proliferation can drive manufacturer revenues two ways: First, multiple SKUs often win more shelf space, encouraging higher sales. Second, in categories where consumers are unwilling to settle for something close to their choice, SKU proliferation is essential. For example, consumers looking for pistachio ice cream are not likely to switch to butter pecan out of brand loyalty; they are more likely to switch to a competing brand that makes pistachio.
      Savings associated with SKU reduction are sometimes insignificant, particularly where manufacturing costs remain unaffected. A company doesn't spend significantly less on raw materials or on marketing simply because it reduces SKUs. Typically, these costs are simply spread across remaining lines.

      Solving the dilemma

      Clearly, tradeoffs are involved. Solving the dilemma depends on knowing some strategic rules of thumb and being prepared to do the gritty analysis required in some categories to see where costs of complexity are justified.

      In consumer goods, the first step is to recognize some categories as premium, meaning investment in branding is high, and branded products sell for sizable premiums above unbranded items. Beer, coffee, and cereal are good examples. In premium categories, profits are driven more by shelf space and meeting the needs of a range of market segments than by cost position. Even competitors with trailing market shares are almost always better off proliferating their offerings and focusing on innovation rather than trimming their product line to extract costs.

      On the other hand, in non-premium categories, consumers don't usually reward investments in branding or differentiation. Meats are good examples. In non-premium categories, profits go to lowest cost producers, and complexity reduction generally deserves more attention than investments in innovation and line extensions.

      In high tech, there's more need for painstaking analysis. Managing complexity at the input component level starts with knowing which items are at risk of high-cost disruptions. Where items are supplied by second- and third-tier vendors-for example, suppliers of capacitors or controller circuits-it's essential to understand how availability affects items further down the chain. Items that have potential to disrupt a lot of subassemblies, are subject to frequent innovations, and have few substitutes are poor candidates for complexity-management initiatives.

      Postponement-putting complexity where it costs less
      Strategies that postpone complexity until late in the production cycle, where it is less expensive to manage, are worth exploring. These have been successful approaches in PC production and auto assembly. In PCs, end customers want units with customized combinations of hard-disc size, memory, processor, and other components, but many large OEMs manufacture in large batches. Rather than disrupting manufacturing, IBM and Compaq have invested in channel assembly, allowing downstream distributors to customize components that drive complexity. This postpones complexity and customization and reduces the risk of being caught with the wrong product in inventory.

      Similarly, in the auto industry, Toyota forged a path for postponing supply chain complexity to benefit producers, distributors, and consumers. Toyota was an early mover in modular wiring harnesses that allow dealers to plug-and-play features such as power windows or locks for individual customers. This removed complexity from Toyota's production lines in Japan and gave dealers an opportunity to upsell and consumers quick turnaround on their orders.

      Postponement can be just as valuable in low-tech categories. Bain worked with a manufacturer of mechanical fasteners whose fragmented supply base, resulting forecasting difficulties, and ensuing short product runs were driving up manufacturing costs. At the same time, the manufacturer's customers-large retailers such as Home Depot-were asking for more options. The solution turned out to be a version of postponement. Now, distribution centers assemble modularized components and undertake special-order packaging and kitting at the final stage in the supply chain. These postponements significantly reduced upstream complexity involved with sourcing, manufacturing, and transportation and caused a radical drop in dead inventory. At the same time, the postponements actually broadened the range of offerings to retailers.

      A critical step in improving supply chain performance is often reducing the complexity of the problem by reducing the number of parts and vendors to manage. But success requires careful analysis. Ruthless SKU-reduction initiatives can result in lost revenues that cancel out cost savings. Manufacturers of high-tech and consumer goods need to look carefully at drivers of profitability in their sectors and determine the extent to which SKU proliferation is affecting their bottom lines. Then, before wielding the knife, they must be certain they know consequences on production costs and customer revenues. And they must evaluate options for postponing complexity to a less painful position in the supply chain-one that maximizes the value to manufacturers and consumers.

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