Demand volatility

With respect to demand certainty, demand is forecasted with bid character and is not stochastic following for example a normal distribution pattern, since demand is influenced by the price development. With respect to demand volatility, demand prices and quantities are not stable but monthly volatile. The total demand elasticity is smaller or equal to 1 with respect to average prices. That means that average prices for total demand can change, if more or less sales quantity is sold in the market. 

Commodity-related models focus on demand volatility and uncertainty in volumes and prices as with sales quantity flexibility. Several authors proposed models to handle demand uncertainty in general focusing on quantities (Cheng et al. 2003 Gupta/Maranas 2003 Cheng et al. 2004 Chen/Lee 2004). Uncertainty is reflected by demand quantity scenarios and/or probabilities. Proposed models maximize expected or robust profit. Process industry-specific models use simulation to address demand uncertainty and to determine optimal inventory levels (Jung et al. 2004). 

Supply chains made hastily will fail. They are unequal to the test of demand volatility. They cannot meet the challenges of global risk management or the pressure to produce new products quickly to enter a new market. It is only when the supply chain is made of the right bricks that it can maximize opportunity and weather market-to-market volatility. 

Like the story of the three little pigs, supply chain leaders wanted to build supply chains that could withstand the winds of demand volatility or the pressure of supply disruption. These supply chains were built to sense outside-in and change the supply chain response based on market conditions. Supply chain leaders that built resilient supply... 

In 2004, Scotts Miracle-Gro faced a crisis. Retailers were unhappy, sales were lagging, and on-shelf availability was an issue. Because of demand volatility (a combination of season, climate, weather, consumer preference and competifive behavior), Scotts traditional supply chain systems were just not up to the task of delivering the right product at the right time at the right place. The lack of supply chain reliability had become a major issue in their three major retail relationships Home Depot, Lowe s, and Walmart. This was significant. These three relationships represented more than 80 percent of the company s channel volume. 

Traditional supply chains are operationally disconnected and reactive to demand. Demand volatility and operational complexity require supply chains to become more resilient. Market-driven value networks begin with conscious choices that integrate and synchronize supply with demand channels and product portfolios. 

Marketing programs can introdnce demand volatility and transform a snpply chain that is nsnally in quadrant II to a quadrant I response. Inventory pre-bnilds are necessary, cross-fnnctional coordination is an imperative, and supply chain excellence is defined by qnick cycles and excellence in demand sensing. 

Quadrant IV. In this supply chain, products have high demand volatility and low volumes. In this situation, the first question that should be asked is "Should these products be made at all "... 

In the early years, there were many ups and downs. In 2000, the company was taken private to re-enter the market in 2002. Over 15 years, the Seagate supply chain was redefined to improve agility for a high-volume business with high-demand volatility. There were four stages. 

In the period from 1995 to 1998, the focus was on efficient operations. The company built products to forecast. The high-demand volatility drove up inventory levels. 

Today, technology is helping companies to maintain inventory levels in the face of increasing complexity in the number of products, changes in channels, and increasing demand volatility. 

Historically, agility has not been a design element of most corporate strategies. (Achieving agility often requires a cost trade-off.) As a result, in the face of supply and demand volatility, the company is less resilient. In the research for this book, three things quickly became obvious ... 

Regarding market-related factors, product demand volatility specifies to what extent the products is made to order or to stock. Thus, if volatility is high, forecasting is relatively difficult and products are typically made to order. Conversely, low volatility means the items can be forecast driven. 

Various factors can be named that affect the choice of the most suitable manufacturing structure and hence the positioning of the CODP (Olhager 2003) market-related factors such as demand volatility, lead time or product differentiation expectations product-related factors as, for example, product architecture (modularity) and production-related factors, such as production lead time or the flexibility of internal processes. 

In the Olhager model the position of the CODP is determined by two variables on one hand, the production to delivery time ratio (P/D ratio) and, on the other, the relative demand volatility (RDV). If the two different factors are arranged as in Fig. 4.10, it is possible to choose one of the four different manufacturing strategies. 

Relative demand volatility Production to delivery tine ratio... 

Tighten forecasts by regularly reviewing that factors that drive demand volatility (e.g. promotion and pricing) and using forecast tools. 

Availability of the resources depends primarily, on their selection (choosing resources respondent to company s goal and scope) and number, but also on their condition—Whence they need to be well maintained so that they were available whenever needed. In agile manufacturing conditions it is especially important as manufacturing jobs are difficult to forecast and plan because of demands volatility and customer-orientation. 

The evidence from most markets is that demand volatility is tending to increase, often due to competitive activity, sometimes due to unexpected responses to promotions or price changes and as a result of intermediaries reordering policies. In situations such as these there are very few forecasting methods that will be able to predict short-term changes in demand with any accuracy. 

Companies can take a number of actions to cope with demand volatility. These include, as shown in Fig. 2.5, holding inventory, building excess capacity, using flexible technology, and managing risk with financial securities. 

Inadequate inventory causes delays to customers, resulting in negative utility. Therefore, a popular way to cope with demand volatility is to hold inventory, which can be expensive. Inventory acts as a hedge against demand volatility as suppliers can dip into it in times of high demand. The used items are made up and inventory is built up to its original level during periods of low demand, thereby... 

Using the principle of order decoupling (order penetration point) is one way of responding to demand volatility in real time. For example, in a build-to-order (BTO) environment the supplier builds the product from scratch (component... 

The third factor in the supply network configuration is the position of a firm in the network. Each supplier has a specific position in the network that can range from the initial source of raw materials to the consumer. A company s position in the supply network can affect its experiences and consequently its interactions with others in the network. For example, the demand volatility in a network is at its highest at the raw materials tier and the least at the retailer tier (bullwhip effect). Amplification of demand volatility can be reduced through information transparency all the way from the upstream supplier to the downstream customer. As we shall see in Chap. 6, upstream suppliers can be shielded from demand volatility by decoupling him from the downstream companies. 

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