News Vendor Model Explanation

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Newsvendor Model
Chapter 9

1 utdallas.edu/~metin Learning Goals
 Determine

the optimal level of product availability

– Demand forecasting – Profit maximization
 Other

measures such as a fill rate

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2

O‟Neill‟s Hammer 3/2 wetsuit

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3

Hammer 3/2 timeline and economics
Generate forecast of demand and submit an order to TEC

Economics:
• • • Each suit sells for p = $180 TEC charges c = $110/suit Discounted suits sell for v = $90

Spring selling season

Nov Dec Jan

Feb Mar Apr May Jun

Jul Aug

Receive order from TEC at the end of the month


Left over units are discounted

The “too much/too little problem”:
– Order too much and inventory is left
…show more content…
– Prob{demand is Q or lower} = Prob{the outcome of a standard normal is z or lower}, where

z

Qm

s

or Q  m  z  s

– (The above are two ways to write the same equation, the first allows you to calculate z from Q and the second lets you calculate Q from z.) – Look up Prob{the outcome of a standard normal is z or lower} in the Standard Normal Distribution Function Table. utdallas.edu/~metin

10

Using historical A/F ratios to choose a Normal distribution for the demand forecast
 Start

with an initial forecast generated from hunches, guesses, etc.
– O‟Neill‟s initial forecast for the Hammer 3/2 = 3200 units.

 Evaluate

the A/F ratios of the historical data:
A/F ratio  Actual demand Forecast

 Set

the mean of the normal distribution to
Expected actual demand  Expected A/F ratio  Forecast

 Set

the standard deviation of the normal distribution to
Standard deviation of actual demand  Standard deviation of A/F ratios  Forecast
11

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O‟Neill‟s Hammer 3/2 normal distribution forecast
Product description JR ZEN FL 3/2 EPIC 5/3 W/HD JR ZEN 3/2 WMS ZEN-ZIP 4/3 Forecast Actual demand 90 140 120 83 140 143 170 156 Error -50 37 -3 14 1995 521 2817 A/F Ratio 1.5556 0.6917 1.0214 0.9176


ZEN 3/2 ZEN-ZIP 4/3 WMS HAMMER 3/2 FULL Average Standard deviation


3190 3810 6490

… …
1195 3289 3673


0.3746 0.8633 0.5659 0.9975 0.3690

Expected actual demand  0.9975  3200 
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