scm 453x Exam 1 – Iowa State University – Flashcards

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MTS Environment (Make-To-Stock)
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Focus on maintaining finished goods inventory ---When, how much, and how to replenish stock Customer service based on in-stock ---Trade-off between inventory and level of service Improvements are made by ---Improving forecasting ---Decreasing lead time ---Increasing flexibility
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ATO Environments (Assemble-to-order)
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Configuration management becomes key ---Understanding how components combine to become finished goods ---Huge number of possible configurations, many of which will never be ordered Focus on inventory of components ---Easier than inventory of finished goods Must manage customer order process ---Lead times, availability, etc.
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ETO/MTO (Make/Engineer-to-order)
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Engineering becomes a resource to be managed Order decoupling point may move to the supplier ---Coordination becomes essentiale is a manufacturing process in which manufacturing starts only after a customer's order is received
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Demand Management and SOP (sales operations planning)
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Demand Management provides forecasts to the SOP process SOP combines forecasts with resource planning to develop aggregate production plans
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Replacing Forecasts With Knowledge
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This situation reflects best practices in supplier relationships - customers provide suppliers with their longer-term production plans, not just current purchase orders. This allows suppliers to better plan their operations Provide suppliers with long-term production plans, not just current purchase orders. Suppliers can better plan their operations Must overcome trust issues Find ways to increase overall supply chain value
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Forecasting - Quantitative
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Quantitative Methods Used when situation is 'stable' & historical data exist Existing products Current technologies Involves mathematical models
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Forecasting - Qualitative
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Qualitative Methods Used when situation is vague & little data exist New products New technologies Involves Intuition Experience Judgment
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Types of Forecasting Models
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Associative ---Causal relationships ---When demand is driven by changes in other factors Time Series ---Identify historical patterns and forecast into the future. ---If we know that sales are 20% above average each January, the forecast for next January should be upward 20%. ---This is an inappropriate method for weekly sales fluctuations that are the result of price and advertising changes.
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4 components of time series demand
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Level Trend Seasonality Error
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Simple Moving Average - Choice of N in the forecast
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Large N Advantages: Smoothes out random variations in demand Disadvantage: reacts slowly to changes in demand Small N Advantages: Reacts quickly to shifts in demand Disadvantages: Doesn't smooth out random variation
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Exponential Smoothing
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Averaging method Weights most recent data more strongly Reacts more to recent changes Widely used, trusted method
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Trend Component
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Uses beta weight Trend changes from period to period
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To Start Double Exponential Smoothing
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Set Level = Demand Set Trend = 0 No Forecast for period 1 P2 Forecast = Level from P1 + Trend P1
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Triple Exponential Smoothing
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Need a whole cycle to initialize the model
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MAPE
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absolute error / actual
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