mod 7

Question 1

impact of forecasting on supply chain

Answer 1

allows to better predict demand: better inventory management, production planning, and reducing costs w/o overstocking

Question 2

best forecasting method

Answer 2

depends on product, planning, costs, resources

Question 3

Delphi Method vs. Expert Opinions

Answer 3

delphi: multiple forecasts
expert: one time input from an individual

Question 4

weakness of sales forces opinions and market research

Answer 4

sales force: biased due to personal beliefs and performance targets
Market research: costly and time consuming, and not always accurate due to changes in market

Question 5

historical life cycle analogy

Answer 5

looks at demand patterns of similar products to predict life cycle of product (good for new products)

Question 6

plotting past demand data

Answer 6

helps to see trends and seasonal patterns/ fluctuations

Question 7

responsive v smoothing time series

Answer 7

responsive methods: smaller moving avg window allows for faster adaptation to market conditions
smoothing: using larger moving average clearer long term trend

Question 8

smoothing

Answer 8

used to reduce flucations in data providing cleaer signal or trend

Question 9

naive forecasr

Answer 9

if last months demand was x then this months forecast is x

Question 10

smoothing in moving average forecast (n of 3 v 5)

Answer 10

n of 5 more smoothing then n of 3 (avg over longer period)

Question 11

smoothing in exponential forecast
a=.1 and a=.5

Answer 11

a=.1 offers more then a=.5 (lower values gives more weight)

Question 12

linear trend v linear regression

Answer 12

linear trend: for time series data (predicting future values based on past trends)
linear regression: used to find relationship between independent and dependent variables

Question 13

correlation in regression output

Answer 13

correlation coefficient shows strength and direction of linear relationship

Question 14

coefficient of determination in regression output

Answer 14

r^2 value shows variation

Question 15

MSE vs MAD

Answer 15

MSE (mean squared error) preferred when larger errors are penalized

MAD (mean absolute deviation) less sensitive to larger outliers

Question 16

MAPE vs MAD

Answer 16

MAPE (mean absolute % error) used when error is needed as a %

MAD (mean absolute deviation) shows magnitude of error