Metters et al. (p. 76): "Services are now the dominant
economic
sector in most modern Western economies. With trends of increasing
globalization and new technologies, contemporary businesses realize
that in order to survive, they must continuously develop new services
and products."
Problem: do you see any
relationship between this statement and Prof. Raja's discussion of
service strategy?
Examples:
Convenience store in the gas station.
Coffee bar in the bookstore.
ATMs.
ATMs in the book store or the gas station.
On-line banking services:
On-line banking as additional service to 'normal'
branch
banking.
Customer handling (Table 5.2 p.79; customer handling vs.
tipping).
Etc.
Information infrastructure:
Required information flows (who needs to know what, when).
Access and security.
Business continuity plan?
Hardware, software, networking.
Etc.
Note that some of the above interact:
Automation & customer handling:
RockBottom Brewery: 'flashing disks.'
Metters et al. p.83: Wagamama: hand-held wireless
order.
Netflix, Hillsboro, OR example: from Web-based customer
support (automated, standardized), to human-contact customer support.
Facility location & customer handling, employment
infrastructure, information systems infrastructure (reliable power
supply!!).
Etc.
Service Blueprinting (p.84): see 'Process Modeling: process
reconstruction and diagrams' (week 4).
Excursion: Customer utility models:
Metters et al. p. 85-89: Customer Utility Models:
p.85: "Success often depends on a favorable market
response to a
new service configuration."
p. 85: "One of the more tantalizing promises of customer
utility
measurement is the ability to optimize the design of a service; i.e.,
specify a level for each price and nonprice attribute."
p. 87: "To evaluate a new service using the utility model,
conjoint analysis (CJA) and discrete choice analysis (DCA) are used to
model customer utility (preferences) in response to experimentally
designed profiles of service attributes."
Utility theory:
Utility (preference, attractiveness) of a choice
alternative is the composite
result of the utility of its attributes
(aspects, considerations, dimensions):
Ux
= f(Uxd): read: the utility of choice
alternative x is
some function f of
the utility of how x
scores on dimensions d.
Problem: Which coffee store?
Ucoffee
store = f(Udistance, Uwait_time, Uprice,
Uassortment, Uinterior, Uaccessories).
Umax=
P(choice)max: read: choice alternative with the
highest utility is most likely (≈
certain!!!!) to
be chosen.
Actors (customers) may attach different levels of utility to
different attributes:
Ux
= f(xd, wd): read:
the
utility of choice alternative x is some function f of the utility of how x scores on dimensions d (xd), whereby
the different dimensions contribute with a weight wd.
f: utility
function or combination rule:
combines the various attribute-specific utilities into an overall
utility.
"Tantalizing promise:"
IF... you know xd,
wd
and f, and
IF... you believe Umax= P(choice)max,
THEN... you can "specify a level for each price and
nonprice attribute" such that
you maximize your marketing objective; e.g.,
market
share, revenue, profit, etc.; e.g.
I can raise the price of my latte $0.25 as long as I
offer one more choice of coffee.
I can raise my total sales 3% by extending my
assortment
of coffee makers with 50%.
Etc.
However, to fulfill this promise, we must answer:
Which are the dimensions d?
Ask people.
Ordination: e.g.;
Ask people how different choice alternatives are; e.g.,
pairwise comparisons.
