Title: Supply Chain Management
1Supply Chain Management
2Outline
- Today
- Finish Chapter 7 and start with Chapter 8
- Homework 3
- Due Thursday October 8 before class
- Next week Thursday
- Chapter 8 and 9
- No class on Tuesday October 13
- Network design simulation assignment
3Network Design Simulation Assignment
- Design the supply chain network for Jacobs
Industries on the fictional continent of Pangea - Jacobs only product is an industrial chemical
that can be mixed with air to form a foam (used
in air conditioner retrofit kits)
4ABCCorp
5Static Forecasting Method
- Deseasonalize demand
- Average seasonal cycle demand depending on p
being odd or even - Estimate level and trend using linear regression
- INTERCEPT(ys, xs)
- LINEST(ys, xs)
- Estimate seasonal factors
- St Dt / Dt
- Si ?j0r-1 Sjpi (average seasonality over all
seasonal cycles) - Forecast
- Ftn (L nT)Stn
6Winters Model
- Estimate levels
- The initial estimates of L0, T0, S1, S2, S3, and
S4 is obtained from static forecasting procedure - Revise the estimate of level for all periods
using smoothing constants ?, ? and ? - Lt1 ?(Dt1/St1) (1 ?)(Lt Tt)
- Tt1 ?(Lt1 Lt) (1 ?)Tt
- Stp1 ?(Dt1/Lt1) (1 ?)St1
- Forecast
- Forecast for future periods is expressed as
- Ftn (Lt nTt)Stn
7Characteristics of Forecasts
- Forecasts should include both the expected value
of the forecast and measure of forecast error - Forecast error estimates the random component of
demand and reveals how inaccurate a forecast is - Observed demand Systematic component random
component -
Why is forecast error important?
8Examples
9Measures of Forecast Error
- Forecast error
- Bias
- Absolute deviation
- Mean absolute deviation
- Tracking signal
- Mean absolute percentage error
- Mean squared error
10Forecast Error
- Error (E)
- Measures the difference between the forecast and
the actual demand in period t - Want error to be relatively small
Et Ft Dt
11Forecast Error
12Forecast Error
- Bias
- Measures the bias in the forecast error
- Want bias to be as close to zero as possible
- A large positive (negative) bias means that the
forecast is overshooting (undershooting) the
actual observations - Zero bias does not imply that the forecast is
perfect (no error) -- only that the mean of the
forecast is on target
biast
?n
?t1
Et
13Forecast Error
Forecast mean on target but not perfect
Undershooting
14Forecast Error
- Absolute deviation (A)
- Measures the absolute value of error in period t
- Want absolute deviation to be relatively small
At Et
15Forecast Error
- Mean absolute deviation (MAD)
- Measures absolute error
- Positive and negative errors do not cancel out
(as with bias) - Want MAD to be as small as possible
- No way to know if MAD error is large or small in
relation to the actual data
?n
MADn ?t1 At
? 1.25MAD
16Forecast Error
Not all that large relative to data
17Forecast Error
- Tracking signal (TS)
- Want tracking signal to stay within (6, 6)
- If at any period the tracking signal is outside
the range (6, 6) then the forecast is biased
TSt biast / MADt
18Forecast Error
Biased (underforecasting)
19Forecast Error
- Mean absolute percentage error (MAPE)
- Same as MAD, except ...
- Measures absolute deviation as a percentage of
actual demand - Want MAPE to be less than 10 (though values under
30 are common)
MAPEn
20Forecast Error
Smallest absolute deviation relative to demand
MAPE lt 10 is considered very good
21Forecast Error
- Mean squared error (MSE)
- Measures squared forecast error
- Recognizes that large errors are
disproportionately more expensive than small
errors - Not as easily interpreted as MAD, MAPE -- not as
intuitive
Et2
MSEn ?t1
?n
VAR MSE
22Measures of Forecast Error
?n
?n
23Measures of Forecast Error
24Summary
- What information does the bias and TS provide to
a manager? - The bias and TS are used to estimate if the
forecast consistently over- or underforecasts - What information does the MSE and MAD provide to
a manager? - MSE estimates the variance of the forecast error
- VAR(Forecast Error) MSEn
- MAD estimates the standard deviation of the
forecast error - STDEV(Forecast Error) 1.25 MADn
25Forecast Error in Excel
- Calculate absolute error At ABS(Et)
- Calculate mean absolute deviation
MADn SUM(A1An)/n AVERAGE(A1An) - Calculate mean absolute percentage error
MAPEn AVERAGE() - Calculate tracking signal TSt biast / MADt
- Calculate mean squared error MSEn SUMSQ(E1En)/n
26Forecast Error in Excel
Et Ft Dt
Forecast Error
27Forecast Error in Excel
biast
?n
?t1
Et
Bias
28Forecast Error in Excel
At Et
Absolute Error
29Forecast Error in Excel
MADn ?t1 At
?n
Mean Absolute Deviation
30Forecast Error in Excel
TSt biast / MADt
Tracking Signal
31Forecast Error in Excel
Errort
Error
32Forecast Error in Excel
Errort
MAPEn
n
Mean Absolute Percentage Error
33Forecast Error in Excel
?n
Et2
MSEn ?t1
Mean Squared Error
34Forecasting
What role does forecasting play in the supply
chain?
35From Forecasting to Planning
Capacity
How should a company best utilize the resources
that it currently has?