Quiz 2 (Sessions 9-12 excl. Fixed-Period or Periodic (P) system and excel)

Question 1

forecasting

Answer 1

process of predicting a future event

Underlying basis of all business decisions
For example:
– Production
– Inventory
– Personnel
– Facilities

Question 2

qualitative forecasting

Answer 2

typically used when the situation is vague and little data exits
-eg, new products, new tech
-involves intuition and experience

Question 3

quantitative methods

Answer 3

Typically used when the situation is ‘stable’ & historical data exists
-eg, existing products, current tech
-involves mathematical equations

Question 4

types of quantitative approach

Answer 4

time series forecasting
-naive approach
-moving average, weighted moving average
-exponential smoothing
-(trend projection)
-multiplicative seasonal model

(associative forecasting methods)
-(linear regression)
-(correlation analysis)

Question 5

time series

Answer 5

-set of evenly spaced numerical data
–obtained by observing the variable of interest at a regular time periods

-use data from previous periods to predict results in future periods
-most appropriate (accurate) when near-future periods results are influenced by similar conditions as those in the past

Question 6

naive approach

Answer 6

-assumed demand in the next period us the same as demand in the most recent period
-eg, if may sales were 48, then June sales will be 48
-Ft = At-1 -> forecast in time t = actual demand in time t-1

-often acts as a starting point that we can use as a comparison to other forecasting approaches
-primarily used for its efficiency

Question 7

moving average method

Answer 7

-MA is series of arithmetic means
-useful when we can assume that market demands will stay fairly steady over time; tends to smooth out short term irregularities in the data series
-less reactive than the naive approach to random changes in demand; using more periods reduced reactiveness

Question 8

WMA

Answer 8

-often used to make the moving average forecast more reactive
–ie, older data is considered less important so has less weight

Question 9

exponential smoothing method

Answer 9

-special form of weighted moving average
–weights decline exponentially; heaviest weight is most recent

-reqs smoothing constant (alpha)
–ranges from 0 to 1

-involves little record keeping of past data

-know rewritten formula

Question 10

smoothing constant

Answer 10

-between 0 and 1; typically between 0.05 and 0.50 for business

–alpha closer to 0: heavily weights past periods (less reactive)
–closer to 1: heavily weights recent data - highly reactive

-evaluating forecasting error helps to select the most effective alpha value

Question 11

forecasting error equation

Answer 11

forecast error = actual - forecast

-also know mean absolute deviation (MAD) equation

Question 12

multiplicative seasonal model (steps to develop seasonal forecast)

Answer 12

1. find avg historical demand for each season
2. compute avg teman over all seasons
3. seasonal index for each season
4. estimate next period’s total demand (eg, next years annual demand)
5. divide this estimate by the number of seasons and then multiply the resulting value by each seasonal index to provide seasonal forecasts

Question 13

inventory types

Answer 13

• raw materials (RM)
• work in process (WIP)
• finished goods inventory (FG)
• maintenance/repaid/operating supplies (MRO)

Question 14

IM decisions

Answer 14

-what, how much, when to order
- how to monitor

Question 15

IC: holding costs

Answer 15

VC that increase proportionally with volume held

Question 16

IC: ordering costs

Answer 16

associated w costs of placing orders and receiving goods

Question 17

IC: setup costs

Answer 17

cost to prepare a machine or process for producing an order

Question 18

inventory expense

Answer 18

-costs incl shrinkage, obsolescence, interest payments for working capital, insurance, storage-space rental etc that increase proportionally w volume and value of inventory items

-firms can only est. holding cost rates; typically set annually, generally between 20-30% of the items’s value, calculated on the avg volume held

-rates may be higher where inventory is perishable, subject to rapid obsolescence, or prone to shrinkage

Question 19

hold down avg volume

Answer 19

for same annual inventory volume buying frequently in small lots reduces age inventory level

Question 20

reduce annual ordering costs

Answer 20

buying many small lots means more ordering costs annually - may offset holding cost savings