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

Managing Capacity and Shin ‐ Ming Guo Demand NKFUST • Managing dynamic demand • Service capacity is perishable • Yield Management Case: Increase Revenue with Fixed Capacity • The Park Hyatt Philadelphia, 118 King/Queen rooms. • Regular fare is r H = $225 (high fare) targeting business travelers. • Hyatt offers a r L = $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 only within a few days of the actual stay. 2 1

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. 3 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 4 2

Economic Consequences of Mismatch Air travel Emergency Room Retailing Supply Seats on specific Medical service Consumer flight electronics Demand Travel for specific Urgent need for Kids buying video time & destination medical service games Supply Empty seat Doctors, nurses, High inventory Exceeds and infrastructure costs Demand are under ‐ utilized Demand Overbooking; Crowding and delays Foregone profit; Profit loss Exceeds in the ER, Deaths Consumer Supply dissatisfaction 5 6 3

Matching Supply and Demand for Services DEMAND Capacity Strategies Strategies Partitioning Sharing demand capacity Increasing Managing customer Variability Cross ‐ Establishing participation training price Developing employees incentives Scheduling reservation work shifts Using systems Promoting part ‐ time off ‐ peak Creating employees Developing demand adjustable complementary capacity services Yield Management 7 1. Managing Customer-induced Variability Type of Accommodation Reduction Variability Arrival Provide generous staffing Require reservations Capability Adapt to customer skill Target customers based on levels capability Request Cross ‐ train employees Limit service breadth Effort Do work for customers Reward increased effort Subjective Diagnose expectations Persuade customers to adjust Preference and adapt expectations 8 4

2. Segmenting Demand Too many walk ‐ in patients on Mondays at a health clinic. 140 Smoothing Demand by Appointment Scheduling 120 100 Day Appointments Before 80 Smoothing 60 Monday 84 After Smoothing Tuesday 89 40 Wednesday 124 20 Thursday 129 0 Friday 114 Mon. Tue. Wed. Thur. Fri. 9 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. 10 5

4. Discriminatory Pricing for Camping 11 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. 12 6

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 13 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. 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 14 7

Example: Surfside Hotel expected number of no ‐ shows = 0(0.07)+1(0.19)+…+9)0.01)=3.04 Expected opportunity loss = 3.04 × $40 = $121.60 15 Cost of too many overbooking: C o =$100 for accommodation at some other hotel and additional compensation. Cost of not enough overbooking: C u =$40 per room. 16 8

Overbooking Solution C 40   • Critical ratio u 0 . 286   C C 40 100 u o • 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. 17 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 18 9

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. 19 Convert Demand and Schedule Shifts 20 10

Scheduling Consecutive Days Off 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 0 2 1 1 D 1 0 1 0 1 1 1 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 2 2 0 0 0 0 0 4 4 2 0 On Duty 4 6 8 8 8 8 8 8 8 10 10 10 21 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. 22 11

Some U.S. Airline Industry Observations • Carriers typically fill 72.4% of seats and have a break ‐ even load of 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. 23 Yield Management: Airline Pricing 24 12

Example: Blackjack Airline d = demand for full fare ($69) ~ N (60, 15 2 ) Expected revenue=69  60=$4140 95 seats Demand for “gamblers fare” ($49) is abundant Expected revenue=49  95=$4655 Decision: x = seats reserved for full fare passengers 25 Optimal Booking Solution Cost of too many seats reserved: C o =$49 Cost of not enough seats reserved: C u =$20 C 20     u P ( d x ) 0 . 29   C C 20 49 u o    d d 60   z ~ N ( 0 , 1 ) •  15 •  (z)=P( d < x )=0.29  z= -0.55 x  60 z    0 . 55 15      x 60 ( 0 . 55 ) 15 51 26 13

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 28 14

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 29 15