Managing Capacity and Shin Ming Guo Demand NKFUST Managing - - PDF document

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Managing Capacity and Demand

• Managing dynamic demand
• Service capacity is perishable
• Yield Management

Shin‐Ming Guo NKFUST

Case: Increase Revenue with Fixed Capacity

• The Park Hyatt Philadelphia, 118 King/Queen rooms.
• Regular fare is rH= $225 (high fare) targeting business travelers.
• Hyatt offers a rL= $159 (low fare) discount fare for a mid‐week

stay targeting leisure travelers.

• Demand for low fare rooms is abundant.
• Most of the high fare demand occurs
• nly within a few days of the actual stay.

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Booking Limits and Yield Management

• Choice 1: Do not accept low fare reservation.

Hope that high fare customers will eventually show up.

• Choice 2: Accept low fare reservations

without any limit.

• Choice 3: Accept low fare reservations but

reserve rooms for high fare customers

• Objective: Maximize expected revenues by

controlling the sale of low fare rooms.

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Focus: Matching Capacity with Demand

• Demand can vary and is unpredictable.
• Capacity is inflexible and maybe costly.
• Demand < Capacity  Impossible to stock service
• Demand > Capacity  Customers may not want to wait

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Economic Consequences of Mismatch

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Air travel Emergency Room Retailing Supply

Seats on specific flight Medical service Consumer electronics

Demand

Travel for specific time & destination Urgent need for medical service Kids buying video games

Supply Exceeds Demand

Empty seat Doctors, nurses, and infrastructure are under‐utilized High inventory costs

Demand Exceeds Supply

Overbooking; Profit loss Crowding and delays in the ER, Deaths Foregone profit; Consumer dissatisfaction

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Matching Supply and Demand for Services

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DEMAND Strategies Partitioning demand Developing complementary services Establishing price incentives Developing reservation systems Promoting

• ff‐peak

demand

Yield Management

Capacity Strategies Cross‐ training employees Increasing customer participation Sharing capacity Scheduling work shifts Creating adjustable capacity Using part‐time employees Managing Variability

• 1. Managing Customer-induced Variability

Type of Variability Accommodation Reduction Arrival Provide generous staffing Require reservations Capability Adapt to customer skill levels Target customers based on capability Request Cross‐train employees Limit service breadth Effort Do work for customers Reward increased effort Subjective Preference Diagnose expectations and adapt Persuade customers to adjust expectations

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• 2. Segmenting Demand

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Smoothing Demand by Appointment Scheduling Day Appointments Monday 84 Tuesday 89 Wednesday 124 Thursday 129 Friday 114

Too many walk‐in patients on Mondays at a health clinic.

20 40 60 80 100 120 140

• Mon. Tue. Wed. Thur.

Fri. Before Smoothing After Smoothing

• 3. Offering Price Incentives
• Differential Pricing

– Weekend rates for phone calls. – Summer pricing by utility companies.

• Promoting Off‐Peak Demand

– Different sources of demand – Hotel: conventions for business or professional groups during the off‐season.

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• 4. Discriminatory Pricing for Camping

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• 5. Developing Complementary Services
• A new service is the complementor if customers value your

service more when they already have purchased the existing service.

• Movie theaters offer popcorns and soft drinks.
• A new service is the complementor if it results in a more

uniform demand.

• Restaurants offer the “afternoon tea” service.

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• 6. Reservation and Overbooking
• Taking reservations is like preselling the service.
• Reservations may benefit consumers by reducing waiting

and guarantee service availability.

• Approximately 50% of reservations get cancelled.
• Multiple reservations, late arrivals, no‐shows.

The company may fail to receive any revenue if a customer cancels the reservation or does not show up.

• Non‐refundable pre‐payment, overbooking

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Overbooking to Protect Revenue

Overbooking—accept more reservations than supply Example: On average there would be 10 cancellations or no‐

• shows. So the hotel can accept 10 more reservations.

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Too much overbooking: some customers may have to be denied a seat even though they have a confirmed reservation. Too little overbooking: waste of capacity, loss of revenue

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Example: Surfside Hotel

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expected number of no‐shows = 0(0.07)+1(0.19)+…+9)0.01)=3.04 Expected opportunity loss = 3.04 × $40 = $121.60

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Cost of too many overbooking: Co=$100 for accommodation at some other hotel and additional compensation. Cost of not enough overbooking: Cu=$40 per room.

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Overbooking Solution

• Critical ratio
• Find x such that x is the largest number that satisfies

P(number of no‐shows < x) ≤ 0.286

• Optimal number of overbooking = 2
• There is about a 26% chance that the hotel will have more

customers than rooms.

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286 . 100 40 40    

• u

u

C C C

Strategies for Managing Capacity

• 7. Increasing customer participation
• 8. Creating adjustable capacity

Different aircrafts, ability to move rental cars around.

• 9. Sharing Capacity
• 10. Cross‐training employees
• 11. Using part‐time employees
• 12. Revenue Management

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• 8. Workshift Scheduling
• The peak to valley variation is 125 to 1.
• Carefully schedule the workforce so that the required service

level can be maintained with the minimal cost.

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Convert Demand and Schedule Shifts

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Scheduling Consecutive Days Off

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Scheduling Hourly Work Times: First Hour Principle

10 11 12 1 2 3 4 5 6 7 8 9 Requirement 4 6 8 8 6 4 4 6 8 10 10 6 Assigned 4 On Duty 4 2 6 2 8 0 0 0 0 8 8 8 8 8 4 8 4 10 2 10 10

Mon Tue Wed Thu Fri Sat Sun forecast 4 3 4 2 3 1 2 A 4 3 4 2 3 1 2 B 3 2 3 1 2 1 2 C 2 1 2 2 1 1 D 1 1 1 1 1

• 12. Revenue Management
• Return = Revenue – Operations Cost

= Throughput  Price – Fixed Costs –Throughput  Variable Costs – Reduce fixed costs – Reduce variable costs – Increase price – Increase throughput

• If capacity is fixed and perishable, fixed costs are high and

variable costs are low, increasing price and/or throughput to improve profitability.

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Some U.S. Airline Industry Observations

• Carriers typically fill 72.4% of seats and have a break‐even load
• f 70.4%.
• From 1995‐1999 (the industry’s best 5 years ever) airlines

earned 3.5 cents on each dollar of sales

• Very high fixed costs and perishable capacity.
• More ticket sales means more revenue and more profit.
• American Airlines estimated a profit of $1.5B over 3 years

contributed by revenue management.

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Yield Management: Airline Pricing

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Example: Blackjack Airline

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d = demand for full fare ($69) ~ N(60, 152) Expected revenue=6960=$4140 Demand for “gamblers fare” ($49) is abundant Expected revenue=4995=$4655 Decision: x = seats reserved for full fare passengers

95 seats

Optimal Booking Solution

• (z)=P(d < x)=0.29  z= -0.55

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) 1 , ( ~ 15 60 N d d z       51 15 ) 55 . ( 60 55 . 15 60          x x z 29 . 49 20 20 ) (      

• u

u

C C C x d P

Cost of too many seats reserved: Co=$49 Cost of not enough seats reserved: Cu=$20

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Optimal Revenue for Blackjack Airline

• Z= ‐0.55
• Normal Loss Function

L(z)=NORMDIST(z,0,1,0)‐z*(1‐NORMSDIST(z)) =0.7328

• expected loss (due to not enough seats reserved)

=L(z)∙=0.7328=10.99

• expected demand = expected sales + expected loss

 expected sales=expected demand‐expected loss =60‐10.99=49.01

• expected revenue=49.01*69+(95‐49.01)*49 =$5635

Yield Management for a Resort Hotel

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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

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