Ch#8-Managing Capacity and Demand.pdf

CH#8: Managing Capacity and Demand OSCM 303 Learning Objective ✓ Strategies for matching capacity and demand for services. ✓ Overbooking strategy for a service that minimizes expected loss. ✓ Use Linear Programming model for scheduling. ✓ Yield management to establish the inventor...

CH#8: Managing Capacity and Demand OSCM 303 Learning Objective ✓ Strategies for matching capacity and demand for services. ✓ Overbooking strategy for a service that minimizes expected loss. ✓ Use Linear Programming model for scheduling. ✓ Yield management to establish the inventory level of a perishable resource.  Introduction After fixed capacity investment decisions are made, the challenge is to match service capacity with customer demand on a daily basis in a dynamic environment. How to best use resource to serve customer? Service capacity is a perishable commodity- plane flying with empty seats. A service is produced and consumed simultaneously – cannot be transferred from a person to another.  Introduction The variability in service demand is pronounced (noticeable). Our habits and culture contribute to this fluctuation. This fluctuation create period with idle service and periods with customer waiting. Need for Operating Strategies to increase capacity utilization and to better match capacity and demand. Strategies for Matching Supply and Demand DEMAND SUPPLY STRATEGIES STRATEGIES 1- Partitioning Increasing demand customer 4- Developing participation Sharing complementary capacity services 2- Establishing Scheduling price Cross- work shifts 5- Developing incentives reservation training systems employees 3- Promoting Creating off-peak adjustable Using capacity demand part-time employees Yield management Strategies for Managing Demand 1- Segmenting (Partitioning) Demand Demand for service seldom derives from homogeneous source. Ex: Weekday business travelers and weekend pleasure travelers for airline. Ex: Lunch and dinner at restaurants. Demand can often be grouped into random arrivals and planned arrivals. Offer special and appropriate service for each segment may reduce demand fluctuation and make it more consistent.  Strategies for Managing Demand Example: Segmenting demand at a health clinic Greatest number of walk-in patients on Monday 140 Fewer during the remaining days Percentage of average daily 130 Why not making appointments at the end of the Before smoothing 120 week to balance demand? physician visits 110 After smoothing 100 Results: 90 1. Number of patients increased by 13.4% 80 2. Decrease physician hours by 5.1% 70 3. Physician-patient time increased by 5.0% 60 1 2 3 4 5 4. Average waiting time remained the same Day of w eek 5. Physician morale increased Strategies for Managing Demand 2- Offering Price Incentives Offer different prices to encourage better use of scarce resource. Ex: Reduced prices for matinee (daytime) at theatres and cinema. Ex: Off-season hotel rates at resort locations. Identify off and peak times and adjust price accordingly. Discriminatory (different) pricing may fill in the valleys (period with low demand) instead of levelling off the peaks. The result is better overall utilization of a scarce resource and the potential for increased profit.  Example: Discriminatory Pricing for Camping Experience Days and Weeks of Camping Season Number of Days Daily Fee Type 1 Saturdays and Sundays of weeks 10 to 15 14 $6.00 2 Saturdays and Sundays of weeks 3 to 9 and 15 to 19 23 2.50 Fridays of weeks 3 to 15, plus all other days of weeks 9 to 15 that are 3 43 0.50 not in experience type 1 or 2 4 Rest of camping season 78 Free COMPARISON of EXISTING REVENUE VS PROJECTED REVENUE FROM DISCRIMINATORY PRICING Existing Fee of $2.50 Discriminatory Fee Camp-sites Camp-sites Experience 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 — — Total 25,977 $64,941 29,000 $59,000 Strategies for Managing Demand 3- Promoting Off-Peak Demand Creative use of off-peak capacity results from seeking different sources of demand. Ex: use a resort hotel during the off-season as a retreat location for business or professional groups. Strategies for Managing Demand 4- Developing Complementary Services Entertaining waiting customers during busy periods can be profitable. Ex: movie theatres include video games in their lobbies. Developing complementary services is a natural way to expand one’s market and it is attractive if the new demands for service are contra-cyclical and result in a more uniform aggregate demand i.e. When the new service demand is high, the original one is low. Strategies for Managing Demand 5- Reservation Systems and Overbooking − Taking reservations pre-sells the potential service. − Additional demand is deflected (changed) to other time or facility. − Reservation reduces waiting time. − Problems arise when “no-shows” – waste resources (airline, hotels, etc). ➔ Overbooking: Accept reservation for more than the available. ➔ Regulations: Ensure space for customers on different time or facility. ➔ What is the best level of overbooking?  Example: Hotel Overbooking Loss Table During the past tourist season, Surfside Hotel did not achieve very high occupancy despite a reservation system that was designed to keep the hotel fully booked. Apparently, prospective guests were making reservations that, for one reason or another, they failed to honor. A review of front-desk records during the current peak period, when the hotel was fully booked, revealed the record of no- shows given in Table 11.6.  Example: Hotel Overbooking Loss Table TABLE 11.6 Surfside Hotel No-Show Experience Reservations Cumulative No-shows d Probability P(d) Overbooked x Probability P(d < x) 0.07 0 0 1.19 1.07 2.22 2.26 3.16 3.48 4.12 4.64 5.10 5.76 6.07 6.86 7.04 7.93 8.02 8.97 9.01 9.99 Expected Number of no shows = σ 𝑃 𝑑 ∗ 𝑑 =.07 0 +.19 1 +.22 2 + … +.01 9 = 3.04 Opportunity Loss for vacant rooms = 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑁𝑜 𝑆ℎ𝑜𝑤𝑠 ∗ 𝐿𝑜𝑠𝑠 𝑝𝑒𝑟 𝑟𝑜𝑜𝑚 = 3.04 ∗ 40$ = 121.60$  Example: Hotel Overbooking Loss Table To avoid some of this loss, overbooking policy was put in place. However, if a guest holding a reservation is turned away owing to overbooking, then other costs are incurred. Surfside has made arrangements with a nearby hotel to pay for the rooms of guests whom it cannot accommodate. Further, a penalty is associated with the loss of customer goodwill and the impact this has on future business. Management estimates this total loss to be approximately $100 per guest “walked” (a term used by the hotel industry). A good overbooking strategy should strike a balance between the opportunity cost of a vacant room and the cost of not honoring a reservation; the best overbooking strategy should minimize the expected cost in the long run.  Example: Hotel Overbooking Loss Table TABLE 11.7 Overbooking Loss Table Reservations Overbooked No- shows Probability 0 1 2 3 4 5 6 7 8 9 0.07 0 100 200 300 400 500 600 700 800 900 1.19 40 0 100 200 300 400 500 600 700 800 2.22 80 40 0 100 200 300 400 500 600 700 3.16 120 80 40 0 100 200 300 400 500 600 4.12 160 120 80 40 0 100 200 300 400 500 5.10 200 160 120 80 40 0 100 200 300 400 6.07 240 200 160 120 80 40 0 100 200 300 7.04 280 240 200 160 120 80 40 0 100 200 8.02 320 280 240 200 160 120 80 40 0 100 9.01 360 320 280 240 200 160 120 80 40 0 Expected — 121.60 91.40 87.80 115.00 164.60 231.00 311.40 401.60 497.40 560.00 loss ($) Expected Loss for overbooking 2 rooms = Strategies for Matching Supply and Demand DEMAND SUPPLY STRATEGIES STRATEGIES 1- Partitioning Increasing demand customer 4- Developing participation Sharing complementary capacity services 2- Establishing Scheduling price Cross- work shifts 5- Developing incentives reservation training systems employees 3- Promoting Creating off-peak adjustable Using capacity demand part-time employees Yield management Strategies for managing capacity For services with big fluctuation, demand cannot be smoothed effectively. Control must come from adjusting service capacity. 2500 2000 1500 Calls 1000 500 0 12am 5:30am Time Strategies for managing capacity 1- Daily Work-shifts Scheduling Important for service organizations with cyclical demand, hospitals (day and night), banks (different hours), etc. General approach based on 4 steps: 1. Forecast demand – on daily or an hour basis. 2. Convert to operator requirements – using a conventional queuing model to ensure required service level. 3. Schedule Shifts – Tours representing various starts and end times of work. Computer Heuristic is available to find solution → set of shifts 4. Assign operators to shifts – Complex (24/7, equity, policies). Computer Heuristic is available for assignment. Strategies for managing capacity Weekly Work-shifts Scheduling with Days-Off Constraints Police, fire protection, hospitals must be available 24/7. Typical employee works 5 days/week with 2 consecutive days off. Management is interested in developing work schedule that meet the varying employee requirements with the smallest number of staff members possible. Use of Integer Linear Programming (ILP) - Determine the minimum number of employees required to assign to each of the 7 days. Example: Hospital Emergency room Example: Hospital Emergency room  Strategies for managing capacity 2- Increasing Customer Participation This strategy is best illustrated by the fast-food restaurants that have eliminated personnel who serve food and clear table. Naturally the customer expects faster service and less expensive meals to compensate for his help. The service provider benefits in the following ways: → Customer provides labor just at the time it is required. → Capacity to serve is not fixed, it varies with demand. Drawback: the quality of labor is not completely under the service manager’s control.  Strategies for managing capacity 3- Creating Adjustable Capacity Through design, a portion of capacity can be made variable. e.g. Hospital emergency, Parking. Capacity at peak periods can be expanded by the effective use of slack times. → Performing supportive tasks during slower periods of demands allows employees to concentrate on essential tasks during rush periods. This strategy requires some cross training of employees to allow performance on different tasks.  Strategies for managing capacity 4- Cross-Training Employees Some services are made up of several operations. Cross-training employees to perform tasks in several operations creates flexible capacity to use in peak periods. → Seen clearly in supermarkets: when queues develop at cash register, stockers can operate registers; likewise cashier can stock shelves for slow periods. This strategy is employee centric while creating adjustable capacity is more physical- design centric.  Strategies for managing capacity 5- Sharing Capacity Service delivery system often requires a large investment in equipments and facilities. It is possible to find other ways to use of this capacity during underutilisation periods. → Airlines share the same gates, ramp (slope), baggage handling equipment, and ground personnel. → Lease their aircraft to others during the off-season.  Strategies for managing capacity 6- Using part-time employees Useful when peaks of activity are persistent (continuous) and predictable. → Mealtimes in restaurants, paydays in bank. Ideally, a pool of ready part-time labor with the required skills and training is available. → Part-time faculty ☺ How to schedule part-time tellers?  Strategies for managing capacity 6- Using part-time employees Scheduling Part-Time Tellers at a Drive-In Bank. Drive-In banks experience predictable variations in activities on different days of the week. To reduce tellers costs, management decided to employ part-time tellers and to reduce full-time ones.  Strategies for managing capacity Procedure: 1. Determine the minimum number of Part-time tellers needed. 2. Develop a decreasing-demand histogram. Re-sequence the days in order of decreasing demand. 3. Assign tellers to the histogram Assign the first part-time teller to the first block in the histogram, the second to the second block, and so on. Repeat the assignment strategy for the next block and carry over the remaining tellers into the next block. Continue so on until last block.  Scheduling Part-time Bank Tellers 7 5 6 Tellers required Decreasing part-time teller demand histogram Tellers required 0 1 2 3 4 5 5 2 3 4 4 4 3 3 2 2 1 Two Full-time Tellers 1 1 5 2 1 Fri. Mon. Wed. Thurs Tues. 0 Mon. Tues. Wed. Thurs. Fri. Object ive funct io n: Minimize x1 + x2 +x3 +x4 +x5 +x6 +x7 Co nst raint s: Sunday x2 +x3 +x4 +x5 +x6  b1 Mo nday x3 +x4 +x5 +x6 +x7  b2 DAILY PART-TIME WORK SCHEDULE, X=workday Teller Mon. Tues. Wed. Thurs. Fri. 1 x …. x …. x 2 x …. …. x x 3,4 x …. …. …. x 5 …. …. x …. x  Yield Management Yield management: is a comprehensive system to maximize revenue for capacity- constrained services using reservation systems, overbooking, and partitioning (segmenting) demand. Airlines were the first to develop yield management. → because of the perishable nature of airline seats and the potential revenue associated to each seat → offering a discount on fares becomes attractive. Service characteristics for yield management: 1. Relatively fixed capacity. 2. Ability to segment market. 3. Perishable inventory. 4. Product sold in advance - (reservation system). 5. Fluctuating demand - (open and close capacity by segment as desired).