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Chapter 9

Chapter 9. Balancing Demand and Capacity. Relating Demand to Capacity: Four Key Concepts. Excess demand : too much demand relative to capacity at a given time Excess capacity : too much capacity relative to demand at a given time

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Chapter 9

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  1. Chapter 9 Balancing Demand and Capacity

  2. Relating Demand to Capacity:Four Key Concepts • Excess demand: too much demand relative to capacity at a given time • Excess capacity: too much capacity relative to demand at a given time • Maximum capacity: upper limit to a firm’s ability to meet demand at a given time • Optimum capacity: point beyond which service quality declines as more customers are serviced

  3. Variations in Demand Relative to Capacity(Fig. 9-1) VOLUME DEMANDED Demand exceeds capacity (business is lost) CAPACITY UTILIZED Demand exceeds Maximum Available optimum capacity Capacity (quality declines) Optimum Capacity (Demand and Supply Well Balanced Excess capacity (wasted resources) Low Utilization (May Send Bad Signals) TIME CYCLE 2 TIME CYCLE 1

  4. Defining Productive Capacity in Services • Physical facilities to contain customers • Physical facilities to store or process goods • Physical equipment to process people, possessions, or information • Labor used for physical or mental work • Public/private infrastructure—e.g., highways, airports, electricity

  5. Alternative Capacity Management Strategies • Level capacity (fixed level at all times) • Stretch and shrink • offer inferior extra capacity at peaks (e.g. bus/metro standees) • vary seated space per customer (e.g. elbow room, leg room) • extend/cut hours of service • Chase demand (adjust capacity to match demand) • schedule downtime in low demand periods • use part-time employees • rent or share extra facilities and equipment • cross-train employees • Flexible Capacity (vary mix by segment)

  6. Predictable Cycles of Demand Levels day week month year other Underlying Causes of Cyclical Variations employment billing or tax payments/refunds pay days school hours/holidays seasonal climate changes public/religious holidays natural cycles (e.g. coastal tides) Predictable Demand Patterns and Their Underlying Causes (Table 9-1)

  7. Causes of Seemingly Random Changes in Demand Levels • Weather • Health problems • Accidents, Fires, Crime • Natural disasters Question: which of these events can be predicted?

  8. Alternative Demand Management Strategies (Table 9-2) • Take no action • let customers sort it out • Reduce demand • higher prices • communication promoting alternative times • Increase demand • lower prices • communication, including promotional incentives • vary product features to increase desirability • more convenient delivery times and places • Inventory demand by reservation system • Inventory demand by formalized queueing

  9. Hotel Room Demand Curves by Segment and by Season (Fig. 9-2) Price per Room Night Bl Bh Bh = business travelers in high season Th Bl = business travelers in low season Tl Th = tourist in high season Tl = tourist in low season Th Bh Bl Tl Quantity of Rooms Demanded at Each Price by Travelers in Each Segment in Each Season Note: hypothetical example

  10. Avoiding Burdensome Waits for Customers • Add extra capacity so that demand can be met at most times (problem: may add too many costs) • Rethink design of queuing system to give priority to certain customers or transactions • Redesign processes to shorten transaction time • Manage customer behavior and perceptions of wait • Install a reservations system

  11. Alternative Queuing Configurations (Fig. 9-4) Single line, single server, single stage Single line, single servers at sequential stages Parallel lines to multiple servers Designated lines to designated servers Single line to multiple servers (“snake”) 21 29 28 “Take a number” (single or multiple servers) 20 25 30 24 26 31 27 23 32

  12. Tailoring Queuing Systems to Market Segments: Criteria for Allocation to Designated Lines • Urgency of job • emergencies vs. non-emergencies • Duration of service transaction • number of items to transact • complexity of task • Payment of premium price • First class vs. economy • Importance of customer • frequent users/loyal customers vs. others

  13. Ten Propositions on the Psychology of Waiting Lines (Table 9-3) 1. Unoccupied time feels longer 2. Preprocess/postprocess waiting feel longer than in-process 3. Anxiety makes waiting seem longer 4. Uncertain waiting is longer than known, finite waiting 5. Unexplained waiting seems longer 6. Unfair waiting is longer than equitable waiting 7. People will wait longer for more valuable services 8. Waiting alone feels longer than in groups 9. Physically uncomfortable waiting feels longer 10. Waiting seems longer to new or occasional users Sources: Maister; Davis & Heineke; Jones & Peppiatt

  14. Benefits of Effective Reservations Systems • Controls and smoothes demand • Pre-sells service • Informs and educates customers in advance of arrival • Customers avoid waiting in line for service (if service times are honored) • Data capture helps organizations prepare financial projections

  15. Characteristics of Well-designed Reservations Systems • Fast and user friendly for customers and staff • Can answer customer questions • Offers options for self service (e.g. Web) • Accommodates preferences (e.g., room with view) • Deflects demand from unavailable first choices to alternative times and locations • Includes strategies for no-shows and overbooking • requiring deposits to discourage no-shows • canceling unpaid bookings after designated time • compensating victims of over-booking

  16. Setting Capacity Allocation Sales Targets for a Hotel by Segment and Time Period (Fig. 9-5) Week 7 Week 36 Capacity (% rooms) (Low Season) (High Season) 100% Out of commission for renovation Executive service guests Executive service guests Transient guests Weekend package W/E package 50% Transient guests Groups and conventions Groups (no conventions) Airline contracts Airline contracts Nights: M Tu W Th F S Sn M Tu W Th F S Sn Time

  17. Information Needed for Demand and Capacity Management Strategies • Historical data on demand level and composition, noting responses to marketing variables • Demand forecasts by segment under specified conditions • Fixed and variable cost data, profitability of incremental sales • Site-by-site demand variations • Customer attitudes towards queuing • Customer evaluations of quality at different levels of capacity utilization

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