Managing Capacity and Demand

Transcription

1 Managing Capacity and Demand Shin Ming Guo 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

2 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 Service Capacity Capacity: amount of output over a period of time Participation: Need to be near customers Simultaneity: Inability to transport services Perishability: Inability to store services Heterogeneity: Volatility of demand 2

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 wait for service 5 Economic Consequences of Mismatch Supply Demand Air travel Emergency Room Retailing Seats on specific flight Medical service Travel for specific Urgent need for time & destination medical service Consumer electronics 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 6 3

4 7 Matching Supply and Demand for Services DEMAND Strategies Capacity Strategies 1 Managing Variability 3 Establishing price incentives 5 Developing complementary services 2 Partitioning demand 4 Promoting off peak demand 6 Developing reservation systems 11 Yield Management Sharing capacity 9 Crosstraining employees 10 Using part time employees 7 Increasing customer participation 8 Scheduling work shifts Creating adjustable capacity 8 4

5 1. Managing Customer-induced Variability Type of Accommodation Reduction Variability 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 9 2. Segmenting Demand Too many walk in patients on Mondays at a health clinic. 140 Smoothing Demand by Appointment Scheduling Day Appointments Monday 84 Tuesday 89 Wednesday 124 Thursday 129 Friday Mon. Tue. Wed. Thur. Fri. Before Smoothing After Smoothing 10 5

6 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 Discriminatory Pricing for Camping 12 6

7 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 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 14 7

8 Overbooking to Protect Revenue Overbooking accept more reservations than supply Example: On average there would be 10 cancellations or noshows. 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 15 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 = $

9 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. 17 Overbooking Solution Critical ratio C uc C u o Find x such that x is the largest number that satisfies P(number of no shows < x) Optimal number of overbooking = 2 There is about a 26% chance that the hotel will have more customers than rooms. 18 9

10 Strategies for Managing Capacity 7. Increasing customer participation 8. Creating adjustable capacity Different aircrafts, ability to move rental cars around. 9. Cross training employees 10. Using part time employees 11. Revenue Management Customer Participation Customer participates actively in the service process. Objectives: Cost reduction (less personnel is needed) Capacity becomes more variable, according to demand Disadvantages: Customer expects quicker service Customer expects low prices (compensation for his help) Quality of customers work cannot be controlled by company (e.g., customer can leave his waste on the table) 10

11 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. 21 Convert Demand and Schedule Shifts 22 11

12 Scheduling Consecutive Days Off Mon Tue Wed Thu Fri Sat Sun forecast A B C D Scheduling Hourly Work Times: First Hour Principle Requirement Assigned 4 On Duty Cross-training & Part-time Employees Training employees to be able to do different tasks Demand peaks: Each employee performs his specialized work (e.g., cashier in a supermarket) Low demand: Employee performs additional tasks: Job is enlarged (e.g., filling the shelves in a supermarket) Using part time employees When demand peaks can be foreseen: Additional staff can be employed for these times (e.g., lunchtime in restaurants) Skills needed low: Students can be taken (e.g., bakery) 12

13 11. 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. 25 Some U.S. Airline Industry Observations Carriers typically fill 72.4% of seats and have a break even load of 70.4%. From (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

14 Yield Management: Airline Pricing 27 Example: Blackjack Airline 95 seats d = demand for full fare ($69) ~ N(60, 15 2 ) 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 28 14

15 Optimal Booking Solution Cost of too many seats reserved: C o =$49 Cost of not enough seats reserved: C u =$20 C P( d x) uc C u o d d 60 ~ N(0,1) z 15 (z)=p(d < x)=0.29 z= z x x 60 ( 0.55) Optimal Revenue for Blackjack Airline Z= 0.55 Normal Loss Function L(z) =NORMDIST(z,0,1,0) z*(1 NORMSDIST(z)) = For full fare customer expected loss (due to not enough seats reserved) =L(z) = =10.99 expected sales + expected loss = expected full fare demand expected sales=expected demand expected loss = =49.01 Expected total revenue=49.01*69+(95 51)*49 =$

16 Yield Management for a Resort Hotel 31 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 32 16