Section E: Demand Management Flashcards
Demand can be
independent or dependent
Independent demand originates from
sources outside of the control of the organization
Dependent demand originates from
internal sources or sources the organization can control.
Often independent demand will be for items that the organization
sells as individual units and dependent demand will be for materials used to make those units.
Independent demand is determined using
forecasts and order management
Dependent demand is not forecasted; instead
it is calculated as part of the materials requirements planning process.
The demand for the item that is unrelated to the demand for other items. Demand for finished goods, parts required for destructive testing, and service parts requirements are examples
Independent Demand
Demand that is directly related to or derived from the bill-of-material structure for other items or end products. Such demands are therefore calculated and need not and should not be forecast. A given inventory item may have both dependent and independent demand at any give time. For example, a part may simultaneously be the component of an assembly and sold as a service part.
Dependent Demand
Independent demand comes from a number of internal and external sources:
- Forecasting
- end customers (finished goods and service parts)
- replenishment orders
- interplant demand or Intercompany transfers (e.g., between subsidiaries)
- internal use (research and development, quality control, destructive testing, marketing use)
When demand is recorded over time and then visualized in chart form,
patterns and trends may become apparent.
Several observations can be made about the patterns of demand for products and services:
- Seasonality
- Trend
- Cycle
- Random variation
Seasonality
A predictable repetitive pattern of demand measured within a year where demand grows and declines. These are calendar-related patterns that can appear annually, quarterly, monthly, weekly, daily, and/or hourly.
The key point about seasonality is that
it repeats over the analysis period and thus can be isolated from other sources of variation and removed temporarily so that it will not influence forecasting.
Trend
A general upward or downward movement of a variable over time (e.g., demand, process attribute). Trends can also be flat. If demand data are put into a program such as Microsoft Excel, both a chart and a trend can be automatically calculated.
Trends can be influenced to varying degrees internally by things like
promotions and externally by things outside one’s control, such as an economic cycle.
Cycle
Cycles usually refer to the wavelike patterns observed in the growth and recession trends of the economy over years. Unlike seasonality, economic cycles do not repeat over a predictable period of time, so this type of forecasting is left to economists.
Another example of a cycle that could influence a trend is
a product’s life cycle.
Random Variation
Random variation is any variation left over after seasonality and trends have been accounted for. Random variation reflects that customers vary when, where, and in what quantities they buy products; the level of variation can vary greatly. If random variation is all, forecasting will be fairly accurate. If it is large, errors will be high.
As the description of random variation indicates,
some demand patterns will be more volatile than others.
Stable demand patterns may have
fairly steady trends, predictable seasonality, and minimal random variation.
Products with stable demand patterns can be forecasted with
low error, so make-to-stock manufacturing environments can be used profitably.
Products and services with dynamic demand patterns, such as innovative products, may have
shifting trends, no seasonality or seasonality that shifts unpredictbly, and/or a high degree of random variation that masks trends and seasonality. In these cases, forecasting is trying to find only the base (average) demand for use in planning; more flexible manufacturing strategies may be needed. Another option might be to find ways to make a dynamic demand pattern more stable (e.g, communicate better to reduce or eliminate the bullwhip effect)
Forecast
an estimate of future demand. A forecast can be constructed using quantitative methods, qualitative methods, or a combination of methods, and it can be based on extrinsic (external) or intrinsic (internal) factors. Various forecasting techniques attempt to predict one or more of the four components of demand: cyclical, random, seasonal, or trend.
Forecasting
The business function that attempts to predict sales and use of products so they can be purchased or manufactured in appropriate quantities in advance.
From the perspective of manufacturing planning and control, forecasts are used as
inputs at strategic, tactical, and operational planning levels, and each forecast is for a diferent time horizon (how far out you are looking).
the bullwhip effect can lead to a great deal of variability in orders from the downstream supply chain.
This leads to the first principle of forecasting: forecasts are wrong most of the time.
Second principle of forecasting:
always be sure there is an estimate of forecast reliability or error rates for each forecast.
Wider ranges equate to lower confidence levels and more dynamic demand patterns.
narrower ranges equate to higher confidence and stable demand patterns.
Third principle of forecasting:
forecasts are more accurate for product families than for individual items.
fourth principle of forecasting:
forecasting is more accurate in the near term than in the long term.
