9. balancing demand & productive capacity

C
DIMPLE UDANI
BALANCING DEMAND AND
PRODUCTIVE CAPACITY
Fluctuations in Demand Threaten Service
Productivity
Productive Capacity and Service
Success
 Services cannot be stockpiled
 This is problematic for people or
physical possession services due to
wide swings in demand
 Goal is to utilize staff, equipment, and
facilities as productively as possible
Service Decision Framework:
Decisions on Matching Demand and
Capacity
What Business Are We In?
What Service Processes Can Be Used in
Our Operation? (PROCESS)
Who Are Our Customers and How Should We
Relate to Them?
What Price Should We Charge?
(PRICE AND OTHER USER OUTLAYS)
How to Communicate? (PROMOTION &
EDUCATION, PHYSICAL EVIDENCE)
Options for Delivery? (PLACE, CYBERSPACE
& TIME, PHYSICAL EVIDENCE)
How Can We Balance
?PRODUCTIVITY AND QUALITY
What Should be the Core and Supplementary Elements
of Our Service Product? (PRODUCT ELEMENTS)
HOW SHOULD WE MATCH DEMAND AND PRODUCTIVE CAPACITY?
What Are Appropriate Roles for People and Technology? (PEOPLE)
How Can Our Firm Achieve Service Leadership?
How Should We Match Demand and
Productive Capacity?
 How do we define our productive capacity?
(e.g., buildings, physical
space, machines, brawn, brains?)
 What are demand levels for our service and do they
exceed capacity at any time?
 What explains variations in demand?
 What strategies can we employ to match demand and
capacity?
 How should we design waiting lines and reservations
systems?
From Excess Demand to Excess
Capacity
Four conditions potentially
faced by fixed-capacity
services:
 Excess demand
 Too much demand relative
to capacity at a given time
 Demand exceeds optimum
capacity – 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
 Excess capacity
Addressing the Problem of
Fluctuating Demand
Two basic
approaches:
 Adjust level of
capacity to meet
demand
 Need to
understand
productive
capacity and
how it varies on
an incremental
Variations in Demand Relative to
Capacity
VOLUME DEMANDED
TIME CYCLE 1 TIME CYCLE 2
Maximum Available
Capacity
Optimum Capacity
(Demand and Supply
Well Balanced)
Low Utilization
(May Send Bad Signals)
Demand exceeds capacity
(business is lost)
Demand exceeds
optimum capacity
(quality declines)
Excess capacity
(wasted resources)
CAPACITY UTILIZED
 Use marketing strategies to
smooth out peaks, fill in
valleys
 Many firms use a mix of both
approaches
Many Service Organizations Are Capacity
Constrained
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
Alternative Capacity Management
Strategies
 Level capacity (fixed level at all times)
 Stretch and shrink
 Offer inferior extra capacity at peaks (e.g., bus/train
standees)
 Vary seated space per customer (e.g., elbow room, leg
room)
 Extend/cut hours of service
 Chase demand (adjust capacity to match demand)
 Flexible capacity (vary mix by segment)
Adjusting Capacity to Match Demand
 Schedule downtime during periods of low demand
 Use part-time employees
 Rent or share extra facilities and equipment
 Ask customers to share
 Invite customers to perform self-service
 Cross-train employees
Patterns and Determinants of Demand
Predictable Demand Patterns and
Their Underlying Causes
 day
 week
 month
 year
 other
 employment
 billing or tax
payments/refunds
 pay days
 school hours/holidays
 seasonal climate changes
 public/religious holidays
 natural cycles
(e.g., coastal tides)
Predictable Cycles
of Demand Levels
Underlying Causes of
Cyclical Variations
Causes of Seemingly
Random Changes in Demand
Levels
 Weather
 Health problems
 Accidents, Fires, Crime
 Natural disasters
Question: Which of these events can be predicted?
Analyzing Drivers of Demand
 Understand why customers from specific
market segments select this service
 Keep good records of transactions to
analyze demand patterns
 Sophisticated software can help to track
customer consumption patterns
 Record weather conditions and other
special factors that might influence
demand
Overall Usage Levels Comprise
Demand from Different Segments
 Not all demand is desirable
 Keep peak demand levels within service capacity of
organization
 Marketing cannot smooth out random fluctuations in
demand
 Fluctuations caused by factors beyond organization’s
control (for example: weather)
 Detailed market analysis may reveal that one segment’s
demand cycle is concealed within a broader, random
pattern
Analyzing Demand by Market
Segment
 Different customers have different demand
patterns by day or by season (e.g., business
travelers vs. tourists)
 Some users have little choice in timing of
demand, others are flexible (e.g. commuters vs.
shoppers)
 Some demand is undesirable and should be
discouraged (e.g., inappropriate calls to
emergency services)
Identifying Variations in Demand
by Time Period
Season of Year
Off-peak Shoulder Peak
Weekday
Weekend
Morning
peak
Midday
Afternoon
peak
Evening/
night
Time of Day
Day of Week
Demand Levels Can Be Managed
Alternative Demand-Management
Strategies
 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
queuing
Marketing Strategies Can
Reshape Some Demand Patterns
 Use price and other costs to manage demand
 Change product elements
 Modify place and time of delivery
 No change
 Vary times when service is available
 Offer service to customers at a new location
 Promotion and education
Hotel Room Demand Curves by
Segment and Season
Bh = business travelers in high season
Bl = business travelers in low season
Th = tourist in high season
Tl = tourist in low season
Bh
Bh
Bl
Bl
Th
Th
Tl
Tl
Price per
room night
Quantity of rooms demanded at each price
by travelers in each segment in each season
Note: hypothetical example
Inventory Demand through Waiting Lines
and Reservations
Waiting Is a Universal Phenomenon!
 An average person may spend up to 30 minutes/day
waiting in line—equivalent to over a week per year!
 Almost nobody likes to wait
 It's boring, time-wasting, and sometimes physically
uncomfortable
Why Do Waiting Lines Occur?
 Because the number of arrivals at a facility
exceeds capacity of system to process them at a
specific point in the process
 Queues are basically a symptom of unresolved
capacity management problems
 Not all queues take form of a physical waiting
line in a single location
Saving Customers from
Burdensome Waits
 Add extra capacity so that demand can be met at most
times (problem: may increase costs too much)
 Rethink design of queuing system to give priority to
certain customers or transactions
 Redesign processes to shorten transaction time
 Manage customer behaviour and perceptions of wait
 Install a reservations system
Alternative Queue Configurations
Single line, single server, single stage
Single line, single servers, sequential stages
Parallel lines to multiple servers
Designated lines to designated servers
Single line to multiple servers (―snake‖)
―Take a number‖ (single or multiple servers)
28
29
21
20
24
23
30 25
31
26
27
32
Criteria for Allocating Different
Market Segments to Designated
Lines
 Urgency of job
 Emergencies versus non-
emergencies
 Duration of service transaction
 Number of items to transact
 Complexity of task
 Payment of premium price
 First class versus economy
 Importance of customer
 Frequent users/high volume
purchasers versus others
Minimize Perceptions of Waiting Time
Ten Propositions on Psychology of
Waiting Lines
1.Unoccupied time feels longer than occupied time
2. Pre- and post-process waits feel longer than in-process waits
3. Anxiety makes waits seem longer
4. Uncertain waits are longer than known, finite waits
5. Unexplained waits are longer than explained waits
6. Unfair waits are longer than equitable waiting
7. People will wait longer for more valuable services
8. Waiting alone feels longer than waiting in groups
9. Physically uncomfortable waits feel longer
10. Waits seem longer to new or occasional users
Ten Propositions on Psychology of
Waiting Lines
Create an Effective Reservation System
Benefits of Reservations
 Controls and smoothes demand
 Pre-sells service
 Informs and educates customers in advance of arrival
 Saves customers from having to wait in line for service
(if reservation times are honored)
 Data captured helps organizations
 Prepare financial projections
 Plan operations and staffing levels
Characteristics of Well-Designed
Reservations System
 Fast and user-friendly for customers and staff
 Answers customer questions
 Offers options for self service (e.g., the 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
Setting Hotel Room Sales Targets by
Segment and Time Period
Out of commission for renovation
Loyalty Program
Members
Transient guests
Weekend
package
Groups and conventions
Airline contracts
100%
50%
Week 7
(Low Season)
MNights: TuTime W Th F S Su
Loyalty Program Members
Transient guests
W/E
package
Groups (no conventions)
Airline contracts
Week 36
(High Season)
M Tu W Th F S Su
Capacity
(% rooms)
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
 Segment-by-segment data
 Fixed and variable cost data, profitability of incremental sales
 Meaningful location-by-location demand variations
 Customer attitudes toward queuing
 Customer opinions of quality at different levels of capacity utilization
DIMPLE UDANI
THANK YOU
1 von 38

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9. balancing demand & productive capacity

  • 1. DIMPLE UDANI BALANCING DEMAND AND PRODUCTIVE CAPACITY
  • 2. Fluctuations in Demand Threaten Service Productivity
  • 3. Productive Capacity and Service Success  Services cannot be stockpiled  This is problematic for people or physical possession services due to wide swings in demand  Goal is to utilize staff, equipment, and facilities as productively as possible
  • 4. Service Decision Framework: Decisions on Matching Demand and Capacity What Business Are We In? What Service Processes Can Be Used in Our Operation? (PROCESS) Who Are Our Customers and How Should We Relate to Them? What Price Should We Charge? (PRICE AND OTHER USER OUTLAYS) How to Communicate? (PROMOTION & EDUCATION, PHYSICAL EVIDENCE) Options for Delivery? (PLACE, CYBERSPACE & TIME, PHYSICAL EVIDENCE) How Can We Balance ?PRODUCTIVITY AND QUALITY What Should be the Core and Supplementary Elements of Our Service Product? (PRODUCT ELEMENTS) HOW SHOULD WE MATCH DEMAND AND PRODUCTIVE CAPACITY? What Are Appropriate Roles for People and Technology? (PEOPLE) How Can Our Firm Achieve Service Leadership?
  • 5. How Should We Match Demand and Productive Capacity?  How do we define our productive capacity? (e.g., buildings, physical space, machines, brawn, brains?)  What are demand levels for our service and do they exceed capacity at any time?  What explains variations in demand?  What strategies can we employ to match demand and capacity?  How should we design waiting lines and reservations systems?
  • 6. From Excess Demand to Excess Capacity Four conditions potentially faced by fixed-capacity services:  Excess demand  Too much demand relative to capacity at a given time  Demand exceeds optimum capacity – 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  Excess capacity
  • 7. Addressing the Problem of Fluctuating Demand Two basic approaches:  Adjust level of capacity to meet demand  Need to understand productive capacity and how it varies on an incremental
  • 8. Variations in Demand Relative to Capacity VOLUME DEMANDED TIME CYCLE 1 TIME CYCLE 2 Maximum Available Capacity Optimum Capacity (Demand and Supply Well Balanced) Low Utilization (May Send Bad Signals) Demand exceeds capacity (business is lost) Demand exceeds optimum capacity (quality declines) Excess capacity (wasted resources) CAPACITY UTILIZED  Use marketing strategies to smooth out peaks, fill in valleys  Many firms use a mix of both approaches
  • 9. Many Service Organizations Are Capacity Constrained
  • 10. 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
  • 11. Alternative Capacity Management Strategies  Level capacity (fixed level at all times)  Stretch and shrink  Offer inferior extra capacity at peaks (e.g., bus/train standees)  Vary seated space per customer (e.g., elbow room, leg room)  Extend/cut hours of service  Chase demand (adjust capacity to match demand)  Flexible capacity (vary mix by segment)
  • 12. Adjusting Capacity to Match Demand  Schedule downtime during periods of low demand  Use part-time employees  Rent or share extra facilities and equipment  Ask customers to share  Invite customers to perform self-service  Cross-train employees
  • 14. Predictable Demand Patterns and Their Underlying Causes  day  week  month  year  other  employment  billing or tax payments/refunds  pay days  school hours/holidays  seasonal climate changes  public/religious holidays  natural cycles (e.g., coastal tides) Predictable Cycles of Demand Levels Underlying Causes of Cyclical Variations
  • 15. Causes of Seemingly Random Changes in Demand Levels  Weather  Health problems  Accidents, Fires, Crime  Natural disasters Question: Which of these events can be predicted?
  • 16. Analyzing Drivers of Demand  Understand why customers from specific market segments select this service  Keep good records of transactions to analyze demand patterns  Sophisticated software can help to track customer consumption patterns  Record weather conditions and other special factors that might influence demand
  • 17. Overall Usage Levels Comprise Demand from Different Segments  Not all demand is desirable  Keep peak demand levels within service capacity of organization  Marketing cannot smooth out random fluctuations in demand  Fluctuations caused by factors beyond organization’s control (for example: weather)  Detailed market analysis may reveal that one segment’s demand cycle is concealed within a broader, random pattern
  • 18. Analyzing Demand by Market Segment  Different customers have different demand patterns by day or by season (e.g., business travelers vs. tourists)  Some users have little choice in timing of demand, others are flexible (e.g. commuters vs. shoppers)  Some demand is undesirable and should be discouraged (e.g., inappropriate calls to emergency services)
  • 19. Identifying Variations in Demand by Time Period Season of Year Off-peak Shoulder Peak Weekday Weekend Morning peak Midday Afternoon peak Evening/ night Time of Day Day of Week
  • 20. Demand Levels Can Be Managed
  • 21. Alternative Demand-Management Strategies  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 queuing
  • 22. Marketing Strategies Can Reshape Some Demand Patterns  Use price and other costs to manage demand  Change product elements  Modify place and time of delivery  No change  Vary times when service is available  Offer service to customers at a new location  Promotion and education
  • 23. Hotel Room Demand Curves by Segment and Season Bh = business travelers in high season Bl = business travelers in low season Th = tourist in high season Tl = tourist in low season Bh Bh Bl Bl Th Th Tl Tl Price per room night Quantity of rooms demanded at each price by travelers in each segment in each season Note: hypothetical example
  • 24. Inventory Demand through Waiting Lines and Reservations
  • 25. Waiting Is a Universal Phenomenon!  An average person may spend up to 30 minutes/day waiting in line—equivalent to over a week per year!  Almost nobody likes to wait  It's boring, time-wasting, and sometimes physically uncomfortable
  • 26. Why Do Waiting Lines Occur?  Because the number of arrivals at a facility exceeds capacity of system to process them at a specific point in the process  Queues are basically a symptom of unresolved capacity management problems  Not all queues take form of a physical waiting line in a single location
  • 27. Saving Customers from Burdensome Waits  Add extra capacity so that demand can be met at most times (problem: may increase costs too much)  Rethink design of queuing system to give priority to certain customers or transactions  Redesign processes to shorten transaction time  Manage customer behaviour and perceptions of wait  Install a reservations system
  • 28. Alternative Queue Configurations Single line, single server, single stage Single line, single servers, sequential stages Parallel lines to multiple servers Designated lines to designated servers Single line to multiple servers (―snake‖) ―Take a number‖ (single or multiple servers) 28 29 21 20 24 23 30 25 31 26 27 32
  • 29. Criteria for Allocating Different Market Segments to Designated Lines  Urgency of job  Emergencies versus non- emergencies  Duration of service transaction  Number of items to transact  Complexity of task  Payment of premium price  First class versus economy  Importance of customer  Frequent users/high volume purchasers versus others
  • 30. Minimize Perceptions of Waiting Time
  • 31. Ten Propositions on Psychology of Waiting Lines 1.Unoccupied time feels longer than occupied time 2. Pre- and post-process waits feel longer than in-process waits 3. Anxiety makes waits seem longer 4. Uncertain waits are longer than known, finite waits 5. Unexplained waits are longer than explained waits
  • 32. 6. Unfair waits are longer than equitable waiting 7. People will wait longer for more valuable services 8. Waiting alone feels longer than waiting in groups 9. Physically uncomfortable waits feel longer 10. Waits seem longer to new or occasional users Ten Propositions on Psychology of Waiting Lines
  • 33. Create an Effective Reservation System
  • 34. Benefits of Reservations  Controls and smoothes demand  Pre-sells service  Informs and educates customers in advance of arrival  Saves customers from having to wait in line for service (if reservation times are honored)  Data captured helps organizations  Prepare financial projections  Plan operations and staffing levels
  • 35. Characteristics of Well-Designed Reservations System  Fast and user-friendly for customers and staff  Answers customer questions  Offers options for self service (e.g., the 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
  • 36. Setting Hotel Room Sales Targets by Segment and Time Period Out of commission for renovation Loyalty Program Members Transient guests Weekend package Groups and conventions Airline contracts 100% 50% Week 7 (Low Season) MNights: TuTime W Th F S Su Loyalty Program Members Transient guests W/E package Groups (no conventions) Airline contracts Week 36 (High Season) M Tu W Th F S Su Capacity (% rooms)
  • 37. 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  Segment-by-segment data  Fixed and variable cost data, profitability of incremental sales  Meaningful location-by-location demand variations  Customer attitudes toward queuing  Customer opinions of quality at different levels of capacity utilization