This document discusses balancing demand and productive capacity in the service industry. It notes that services cannot be stockpiled like products, which causes issues with fluctuating demand. The goal is to utilize staff, equipment, and facilities as productively as possible. The document outlines different factors to consider when matching demand and capacity, including defining capacity, understanding demand levels and patterns, and employing strategies like adjusting capacity, marketing, queues and reservations systems. It discusses analyzing demand by segment, identifying predictable and random demand patterns, and managing demand through various approaches like pricing. Overall, the key is understanding demand in order to effectively match it with capacity.
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
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
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
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
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
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