SCHM 2301 LATEST 2026 REVISION EXAM QUESTIONS
AND ANSWERS MARKED A+
✔✔Supplier Relationship Management (SRM) - ✔✔technology enabled data gathering
about suppliers to manage strategic relationships
✔✔Demand Planning - ✔✔both forecasting and managing customer demand to reach
operational and financial goals
✔✔Demand Forecasting - ✔✔predicting future customer demand
✔✔Demand Management - ✔✔influencing either pattern or consistency of demand
✔✔Components of Demand - ✔✔patterns of demand over time
✔✔Autocorrelation - ✔✔relationship of past and current demand
✔✔Forecast error - ✔✔"unexplained" component of demand. Random in nature
✔✔Grassroots - ✔✔input from those close to products or customers
✔✔Executive Judgment - ✔✔input from those with experience
✔✔Historical Analogy - ✔✔assume past demand is a good predictor of future demand
✔✔Marketing Research - ✔✔examine patterns of current customers
✔✔Delphi Method - ✔✔input from panel of experts, usually very expensive
✔✔Time Series Analysis - ✔✔uses historical data arranged in order of occurrence
✔✔Causal Studies - ✔✔cause and effect relationships among variables
✔✔Simulation models - ✔✔create representations of previous events to evaluate future
outcomes
✔✔Moving Average - ✔✔simple average of demand from some number of past periods
• One way to forecast changes in demand while smoothing out variability as a simple
average of past demand outcomes.
• Used when the demand pattern is somewhat stable, without trend or seasonality.
Eliminating "noise" i.e. random variations.
, ✔✔Weighted Moving Average - ✔✔assigns different weights to each period's demand
based upon its importance
• emphasizes the impact of some observations over the others
• extremely common to add the higher weights to most recent data to capture current
market effects.
✔✔Exponential Smoothing Method - ✔✔puts less weight on further back in time data
more weight given to most recent demand
✔✔Determining Trend Factors - ✔✔The trend component of a time series normally
results from some variable that causes a general rise or decline in values over time.
A linear trend results when demand rises or falls at a constant rate
✔✔Forecast Accuracy - ✔✔measure of how closely forecast aligns with demand; actual
minus forecasted
✔✔A positive forecast error indicates - ✔✔overly pessimistic; sold more than forecasted
✔✔A negative value indicates - ✔✔overly optimistic; sold less than forecasted
✔✔Bias - ✔✔tendency to continually over or under predict future demand (forecast
error)
✔✔Mean Forecast Error - ✔✔the average forecast error over a number of periods
✔✔Mean Absolute Deviation (MAD) - ✔✔average of forecast errors, irrespective of
direction, magnitude/size of the deviation/error
✔✔Mean (average) Absolute Percentage Error (MAPE) - ✔✔the MAD adjusted to
measure how large errors are relative to the actual demand quantities (across products)
✔✔operational inefficiencies - ✔✔• Need for extra capacity resources
• Backlog
• Customer dissatisfaction
• System buffering
• safety stock, safety lead time, capacity cushions, etc.
✔✔Demand Management - ✔✔Requires coordination of many sources of demand info.
Ways to influence the timing or quantity of demand:
• pricing changes, promotions, or sales incentives
• increase demand during low periods
AND ANSWERS MARKED A+
✔✔Supplier Relationship Management (SRM) - ✔✔technology enabled data gathering
about suppliers to manage strategic relationships
✔✔Demand Planning - ✔✔both forecasting and managing customer demand to reach
operational and financial goals
✔✔Demand Forecasting - ✔✔predicting future customer demand
✔✔Demand Management - ✔✔influencing either pattern or consistency of demand
✔✔Components of Demand - ✔✔patterns of demand over time
✔✔Autocorrelation - ✔✔relationship of past and current demand
✔✔Forecast error - ✔✔"unexplained" component of demand. Random in nature
✔✔Grassroots - ✔✔input from those close to products or customers
✔✔Executive Judgment - ✔✔input from those with experience
✔✔Historical Analogy - ✔✔assume past demand is a good predictor of future demand
✔✔Marketing Research - ✔✔examine patterns of current customers
✔✔Delphi Method - ✔✔input from panel of experts, usually very expensive
✔✔Time Series Analysis - ✔✔uses historical data arranged in order of occurrence
✔✔Causal Studies - ✔✔cause and effect relationships among variables
✔✔Simulation models - ✔✔create representations of previous events to evaluate future
outcomes
✔✔Moving Average - ✔✔simple average of demand from some number of past periods
• One way to forecast changes in demand while smoothing out variability as a simple
average of past demand outcomes.
• Used when the demand pattern is somewhat stable, without trend or seasonality.
Eliminating "noise" i.e. random variations.
, ✔✔Weighted Moving Average - ✔✔assigns different weights to each period's demand
based upon its importance
• emphasizes the impact of some observations over the others
• extremely common to add the higher weights to most recent data to capture current
market effects.
✔✔Exponential Smoothing Method - ✔✔puts less weight on further back in time data
more weight given to most recent demand
✔✔Determining Trend Factors - ✔✔The trend component of a time series normally
results from some variable that causes a general rise or decline in values over time.
A linear trend results when demand rises or falls at a constant rate
✔✔Forecast Accuracy - ✔✔measure of how closely forecast aligns with demand; actual
minus forecasted
✔✔A positive forecast error indicates - ✔✔overly pessimistic; sold more than forecasted
✔✔A negative value indicates - ✔✔overly optimistic; sold less than forecasted
✔✔Bias - ✔✔tendency to continually over or under predict future demand (forecast
error)
✔✔Mean Forecast Error - ✔✔the average forecast error over a number of periods
✔✔Mean Absolute Deviation (MAD) - ✔✔average of forecast errors, irrespective of
direction, magnitude/size of the deviation/error
✔✔Mean (average) Absolute Percentage Error (MAPE) - ✔✔the MAD adjusted to
measure how large errors are relative to the actual demand quantities (across products)
✔✔operational inefficiencies - ✔✔• Need for extra capacity resources
• Backlog
• Customer dissatisfaction
• System buffering
• safety stock, safety lead time, capacity cushions, etc.
✔✔Demand Management - ✔✔Requires coordination of many sources of demand info.
Ways to influence the timing or quantity of demand:
• pricing changes, promotions, or sales incentives
• increase demand during low periods
