Managing Supply and Demand

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Managing Supply and Demand

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Title: Managing Supply and Demand Author: James Fitzsimmons Last modified by: a.ruiz.torres Created Date: 3/8/1996 3:54:18 PM Document presentation format – PowerPoint PPT presentation

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Title: Managing Supply and Demand


1
Managing Supply and Demand
2
Strategies for Matching Supply and Demand for
Services

DEMAND STRATEGIES
SUPPLY STRATEGIES
Partitioning demand
Increasing customer participation
Developing complementary services
Sharing capacity
Establishing price incentives
Scheduling work shifts
Cross- training employees
Developing reservation systems
Creating adjustable capacity
Promoting off-peak demand
Using part-time employees
Yield management
3
Partitioning Demand at a Health Clinic

Smoothing Demand by Appointment Scheduling Day
Appointments Monday
84 Tuesday
89 Wednesday
124 Thursday
129 Friday
114
4
Discriminatory Fee Schedule for Camping
  • Experience

    No. of Daily
  • type Days and
    weeks of camping season
    days fee
  • 1 Saturdays and
    Sundays of weeks 10 to 15, plus
    14 6.00
  • Dominion Day
    and civic holidays
  • 2 Saturdays and
    Sundays of weeks 3 to 9 and 15 to 19, 23
    2.50
  • plus
    Victoria Day
  • 3 Fridays of weeks
    3 to 15, plus all other days of weeks 43
    0.50
  • 9 to 15 that
    are not in experience type 1 or 2
  • 4 Rest of camping
    season
    78 free
  • EXISTING REVENUE VS PROJECTED REVENUE FROM
    DISCRIMINATORY PRICING

  • Existing flat fee of 2.50
    Discriminatory fee
  • Experience Campsites

    Campsites
  • type occupied
    Revenue
    occupied (est.) Revenue
  • 1 5.891
    14,727
    5,000 30,000
  • 2 8,978
    22,445
    8,500 21,250
  • 3 6,129
    15,322
    15,500 7.750
  • 4 4,979
    12,447
    . .

5
Hotel Overbooking Decision Matrix

  • Number of Reservations Overbooked
  • No- Prob-
  • shows ability 0 1
    2 3 4 5
    6 7 8 9
  • 0 .07 0
    100 200 300 400 500
    600 700 800 900
  • 1 .19 40 0
    100 200 300 400
    500 600 700 800
  • 2 .22 80
    40 0 100 200 300
    400 500 600 700
  • 3 .16 120 80
    40 0 100 200
    300 400 500 600
  • 4 .12 160 120
    80 40 0 100
    200 300 400 500
  • 5 .10 200 160
    120 80 40 0
    100 200 300 400
  • 6 .07 240 200
    160 120 80 40
    0 100 200 300
  • 7 .04 280 240
    200 160 120 80
    40 0 100 200
  • 8 .02 320 280
    240 200 160 120
    80 40 0 100
  • 9 .01 360 320
    280 240 200 160
    120 80 40 0
  • Expected loss, 121.60 91.40 87.80
    115.00 164.60 231.00 311.40 401.60
    497.40 560.00

6
Scheduling Part-time Bank Tellers


Decreasing part-time teller demand histogram
Tellers required
5
4
4
0 1 2 3 4 5 6 7
Tellers required
3
3
0 1 2 3 4 5
2
2
1
Two Full-time Tellers
1
1
5
2
Fri. Mon. Wed. Thurs Tues.
Mon. Tues. Wed. Thurs. Fri.
DAILY PART-TIME WORK SCHEDULE, Xworkday Teller
Mon. Tues.
Wed. Thurs.
Fri. 1 x
. x
. x 2
x .
. x
x 3,4 x
. .
. x 5
. . x
. x
7
Daily Scheduling of Telephone Operator Workshifts

Topline profile
Scheduler program assigns tours so that the
number of operators present each half hour
adds up to the number required
Tour
12 2 4 6 8 10
12 2 4 6 8 10
12
12 2 4 6 8 10
12 2 4 6 8 10
12
8
Weekly Workshift Scheduling with Days-off


Schedule matrix, x day off Operator
Su M Tu W
Th F Sa 1
x x
...
2 x
x
3
... x x
4
... x x
5

x x
6
x x
7
x
x 8
x
x Total
6 6 5
6 5 5
7 Required 3 6
5 6 5 5
5 Excess 3
0 0 0 0
0 2
9
Seasonal Allocation of Rooms by Service Class for
Resort Hotel

First class Standard Budget
20
20
20
30
50
30
50
60
Percentage of capacity allocated to different
service classes
50
30
30
10
Peak Shoulder
Off-peak Shoulder (30)
(20) (40)
(10) Summer Fall
Winter
Spring Percentage of capacity allocated to
different seasons
10
Ideal Characteristics for Yield Management
  • Relatively Fixed Capacity
  • Ability to Segment Markets
  • Perishable Inventory
  • Product Sold in Advance
  • Fluctuating Demand
  • Low Marginal Sales Cost and High Capacity
    Change Cost

11
Demand Control Chart for a Hotel

Expected Reservation Accumulation
2 standard deviation control limits
12
Yield Management Using the Critical Fractile
Model

Where x seats reserved for full-fare
passengers d demand for full-fare
tickets p proportion of economizing
(discount) passengers Cu lost revenue
associated with reserving one too few seats at
full fare (underestimating demand). The lost
opportunity is the difference between the fares
(F-D) assuming a passenger, willing to pay
full-fare (F), purchased a seat at the discount
(D) price. Co cost of reserving one to
many seats for sale at full-fare (overestimating
demand). Assume the empty full-fare seat
would have been sold at the discount price.
However, Co takes on two values, depending on
the buying behavior of the passenger who would
have purchased the seat if not reserved for
full-fare.
if an economizing passenger
if a full fare
passenger (marginal gain) Expected value of Co
pD-(1-p)(F-D) pF - (F-D)
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