Product configuration, ambidexterity and firm performance in the context of industrial equipment manufacturing
| Author | Aravind Chandrasekaran,Tashfeen Sohail,Fabrizio Salvador |
| Date | 01 May 2014 |
| Published date | 01 May 2014 |
| DOI | http://doi.org/10.1016/j.jom.2014.02.001 |
Journal
of
Operations
Management
32
(2014)
138–153
Contents
lists
available
at
ScienceDirect
Journal
of
Operations
Management
jo
ur
nal
ho
me
pa
ge:
www.elsevier.com/locate/jom
Product
configuration,
ambidexterity
and
firm
performance
in
the
context
of
industrial
equipment
manufacturing
Fabrizio
Salvadora,∗,
Aravind
Chandrasekaranb,
Tashfeen
Sohailc
aDepartment
of
Operations
and
Technology
Management,
IE
Business
School,
IE
University,
Calle
Maria
de
Molina,
12-5,
28006
Madrid,
Spain
bDepartment
of
Management
Science,
Fisher
College
of
Business,
Ohio
State
University,
650
Fisher
Hall,
2100
Neil
Avenue,
Columbus,
OH
43210,
United
States
cDepartment
of
Accounting,
Goodman
School
of
Business,
Brock
University,
248
Taro
Hall,
500
Glenridge
Avenue,
St.
Catharines,
ON
L2S
3A1,
Canada
a
r
t
i
c
l
e
i
n
f
o
Article
history:
Received
7
May
2013
Received
in
revised
form
19
February
2014
Accepted
24
February
2014
Available
online
5
March
2014
Keywords:
Product
configuration
Ambidexterity
Customization
Complexity
Organizational
capabilities
Firm
performance
a
b
s
t
r
a
c
t
The
practice
of
configuring
products
to
individual
customer
orders
has
found
application
in
a
variety
of
industry
contexts,
but
little
is
known
about
the
specific
capabilities
that
firms
develop
to
successfully
compete
when
offering
configurable
products.
Our
research
begins
to
fill
this
gap
in
the
context
of
indus-
trial
equipment
manufacturing.
Drawing
from
the
ambidexterity
literature,
we
argue
that
firms
have
to
balance
dual
goals
of
reducing
variation
and
promoting
variation
in
their
product
configuration
activities
by
fostering
two
distinct
firm-level
capabilities:
product
configuration
effectiveness
(PCE)
and
product
configuration
intelligence
(PCI).
Specifically,
we
hypothesize
that
the
simultaneous
presence
of
PCE
and
PCI—that
is,
product
configuration
ambidexterity
(PCA)—drives
superior
firm
responsiveness
and,
indi-
rectly
firm
sales
and
operating
margin.
However,
we
also
contend
that
responsiveness
gains
through
PCA
can
diminish
with
product
complexity
and
can
increase
operating
cost.
We
test
these
hypotheses
by
collecting
both
primary
and
secondary
data
from
a
sample
of
108
European
industrial
equipment
manufacturing
firms.
Results
from
our
analyses
indicate
that
PCA
has
an
indirect
effect
through
respon-
siveness
on
sales
and
operating
cost
but
not
on
operating
margin,
with
this
effect
diminishing
with
product
complexity.
Taken
together,
our
results
suggest
that
investment
in
developing
PCA
may
repre-
sent
a
conundrum
for
industrial
equipment
manufacturing
firms,
because
it
translates
into
market
but
not
financial
advantages,
and
it
is
intertwined
with
product
design
decisions.
We
conclude
this
study
with
a
discussion
of
the
findings
for
theory
and
practice.
©
2014
Elsevier
B.V.
All
rights
reserved.
1.
Introduction
How
do
firms
that
allow
each
customer
to
configure
his
or
her
own
products
succeed?
Companies
such
as
Dell,
Build-A-Bear,
Mini
Cooper,
Adidas
and
John
Deere
have
shown
that
configuring
prod-
ucts
to
order
is
a
viable
approach
to
offer
customized
product
categories
as
diverse
as
computers,
toys,
cars,
apparel
and
indus-
trial
products
(Davenport
and
Harris,
2007;
Eng,
2012;
Magretta,
1998;
Salvador
et
al.,
2009).
By
offering
configurable
products,
these
companies
on
the
one
hand
give
customers
unprecedented
pos-
sibilities
in
choosing
product
features.
On
the
other
hand,
they
constrain
such
product
features
to
a
pre-defined
set
of
solutions
(Hvam
et
al.,
2010)
in
order
to
reduce
uncertainty
and
variability
∗Corresponding
author.
Tel.:
+34
91
568
9856.
E-mail
addresses:
fabrizio.salvador@ie.edu
(F.
Salvador),
chandrasekaran.24@osu.edu
(A.
Chandrasekaran),
tsohail@brocku.ca
(T.
Sohail).
associated
to
the
generation
of
customized
product
variants
(Tenhiälä
and
Ketokivi,
2011).
To
date
studies
on
the
performance
effects
of
product
config-
uration
are
very
limited,
often
anecdotal,
and
surprisingly
yield
mixed
results.
For
example,
Peng
et
al.,
2011
in
a
sample
of
266
manufacturing
plants
found
that
plants
with
a
sophisticated
product
configuration
technology
did
not
have
a
greater
mass
cus-
tomization
capability.
Conversely,
a
study
by
Trentin
et
al.,
2011
on
a
sample
of
238
manufacturing
plants
found
that
plants
with
a
more
sophisticated
product
configuration
technology
enjoyed
superior
time
performance,
measured
as
a
composite
of
on-time
delivery,
delivery
speed,
and
speed
of
new
product
introductions.
Even
in-depth
case
studies
report
mixed
findings
on
the
perfor-
mance
effects
of
IT
(Information
Technology)
and
expert
systems
supporting
product
configuration
activities.
For
example,
despite
Digital
Equipment
Corporation’s
technical
success
in
reducing
con-
figuration
errors
through
an
innovative
expert
system
(Barker
and
O‘Connor,
1989)
serious
implementation
issues
arose
due
to
http://dx.doi.org/10.1016/j.jom.2014.02.001
0272-6963/©
2014
Elsevier
B.V.
All
rights
reserved.
F.
Salvador
et
al.
/
Journal
of
Operations
Management
32
(2014)
138–153
139
resistance
and
dissatisfaction
within
large
groups
of
sales
people
(Leonard-Barton,
1987).
The
inconsistency
in
the
performance
benefits
reported
in
the
business
press
and
the
academic
research
calls
for
a
closer
examination
of
the
mechanisms
through
which
configure-to-order
businesses
achieve
superior
performance.
We
start
from
two
basic
premises
in
addressing
this
problem.
First,
we
argue
that
the
current
focus
in
the
extant
literature
on
IT
solutions
such
as
prod-
uct
configurators
and
expert
systems
(Aldanondo
et
al.,
2000;
Haug
et
al.,
2011;
Trentin
et
al.,
2012;
Pitiot
et
al.,
2013)
has
to
be
broadened
to
consider
firm-level
capabilities
that
support
configure-to-order
businesses.
IT
solutions,
by
themselves,
can-
not
ensure
that
firms
control
variation
in
selling
and
delivering
custom-specified
products
because
the
effectiveness
of
these
sys-
tems
depends
on
several
other
factors
such
as
adoption
and
use
by
the
firm
personnel
(Venkatesh
et
al.,
2003;
Amoako-Gyampah
and
Salam,
2004;
Bendoly
and
Cotteleer,
2008)
as
well
as
the
fit
between
these
systems
and
organizational
workflow
processes
(Van
Stijn
and
Wensley,
2001;
Bendoly
and
Jacobs,
2004).
Second,
we
argue
that
configure-to-order
business
models
should
not
only
rely
on
controlling
variation
in
the
generation
of
customized
products—an
unquestionably
important
require-
ment
that
has
been
the
focus
of
past
research
(Gunasekaran
and
Ngai,
2005)—but
should
also
promote
variation
and
adaptation
of
configurable
products
and
associated
production
processes
to
the
evolving
needs
of
the
customer.
This
line
of
reasoning
draws
support
from
organizational
learning
theories
that
link
firm
per-
formance
to
the
simultaneous
pursuit
of
activities
that
control
variation
(i.e.,
exploitation)
and
activities
that
foster
variation
(i.e.,
exploration)
(Benner
and
Tushman,
2003;
Tushman
and
O‘Reilly,
1996;
Chandrasekaran
et
al.
2012a).
The
synergies
from
simulta-
neously
pursuing
exploitation
and
exploration,
or
ambidexterity,
in
the
context
of
configurable
products
is
exemplified
by
Cap-
ital
One,
which
outperformed
its
competitors
for
a
decade
by
complementing
their
ability
to
(1)
rapidly
and
reliably
configure
financial
products
from
an
existing
set
of
solutions
for
each
individ-
ual
customer
with
their
ability
to
(2)
regularly
analyze
customers’
transaction
data
to
identify
new
product
and
process
innovation
opportunities
(Paige
et
al.,
2000).
Following
these
two
premises,
we
propose
that
configure-to-
order
firms
benefit
from
developing
two
distinct
organizational
capabilities,
namely
product
configuration
effectiveness
(PCE)
and
product
configuration
intelligence
(PCI).
We
refer
to
PCE
as
the
ability
of
a
firm’s
sales
personnel
to
autonomously
and
reliably
configure
exist-
ing
products
and
processes
in
response
to
customer
requirements.
PCE
controls
variation
in
products
and
processes
by
avoiding
errors
and
delays
from
poorly
informed
product
configuration
decisions
dur-
ing
order
acquisition
activities
(Forza
and
Salvador,
2002;
Tenhiälä
and
Ketokivi,
2011).
We
refer
to
PCI
as
the
ability
of
a
firm’s
personnel
to
identify
opportunities
for
product
and
process
innovation
by
sys-
tematically
analyzing
information
on
past
product
configurations.
PCI
promotes
variation
in
the
firms’
products
and
processes
by
gener-
ating
insights
during
the
early
stages
of
NPD
activities
wherein
firm
personnel
from
both
sales
and
technical
areas
(e.g.,
R&D,
production
and
purchasing)
interact
to
define
new
product
and
process
specifi-
cations
(Davenport
and
Harris,
2007;
Kruschwitz,
2011).
Consistent
with
the
ambidexterity
literature
we
define
product
configuration
ambidexterity
(PCA)
as
the
simultaneous
presence
of
these
two
capabilities
within
the
firm.
The
purpose
of
this
research
is
to
understand
how
PCA,
or
the
simultaneous
development
of
PCE
and
PCI,
impact
firm
performance
in
the
context
of
industrial
equipment
manufacturing.
Building
on
the
concept
of
ambidexterity
developed
from
individuals
(Lubatkin
et
al.,
2006;
Gibson
and
Birkinshaw,
2004),
we
argue
that
PCA
benefits
firm
performance
by
creating
synergies
between
sales
personnel’s
efforts
to
configure
existing
products
and
sales
and
technical
personnel’s
efforts
to
specify
future
configurable
products
and
processes.
We
further
contend
that
these
synergies
diminish
with
increase
in
the
complexity
of
products
offered
by
the
firm.
Finally,
we
argue
that
the
relationship
between
PCA
and
firm
per-
formance
is
indirect
and
mediated
through
responsiveness,
defined
as
the
speed
and
reliability
with
which
the
firm
serves
its
customers’.
That
is,
PCA
drives
firm
performance
by
improving
responsiveness.
Industrial
equipment
manufacturing
context
is
chosen
because
of
two
main
reasons.
First,
unlike
apparel,
cars
and
toys
industries,
a
vast
majority
of
industrial
equipment
manufacturers
compete
primarily
through
configure-to-order
products
(Mazzoleni,
1999).
Hence,
sampling
from
this
industry
is
more
likely
to
include
firms
for
which
developing
both
PCE
and
PCI
(i.e.,
PCA)
is
a
meaning-
ful
concern.
Second,
industrial
equipment
manufacturing
firms
are
predominantly
small-and-medium
enterprises
(NCMM,
2012)
for
which
developing
both
PCE
and
PCI
(i.e.,
PCA)
is
a
non-trivial
effort
due
to
resource
constraints
(Zahra
et
al.,
2000).
Moreover
it
is
com-
mon
for
sales
and
technical
personnel
to
encounter
learning
and
information
processing
difficulties
when
selling
and
developing
configurable
industrial
products
(Salvador
and
Forza,
2004).
There-
fore,
PCA
can
differentiate
firms
in
this
context
and
may
have
a
stronger
association
with
firm
performance.
We
test
our
hypotheses
on
a
sample
of
European
indus-
trial
equipment
manufacturers
by
combining
two
different
data
sources:
(1)
primary
survey
data
on
PCE,
PCI
and
other
variables
from
108
industrial
equipment
manufacturers
and
(2)
financial
performance
data
collected
from
secondary
data
sources.
Results
from
our
analyses
suggest
three
main
contributions.
First,
we
broaden
the
variation-reduction
focus
(i.e.,
PCE)
in
the
product
cus-
tomization
literature
(e.g.,
see
Liechty
et
al.,
2001;
Zipkin,
2001)
by
empirically
demonstrating
the
synergies
derived
from
developing
capabilities
that
also
promote
variance
in
product
configuration
(i.e.,
PCI).
We
also
show
that
such
synergies
are
hindered
by
prod-
uct
complexity,
shedding
new
light
on
the
interaction
of
product
and
process
design
decisions
in
the
context
of
configure-to-order
businesses.
Second,
our
study
empirically
examines
on
a
large
sam-
ple
the
effect
of
product
configuration
capabilities
on
objective
firm
performance,
addressing
Fogliatto
et
al.,
2012
call
for
more
research
on
this
topic.
Specifically,
we
provide
novel
insights
relative
to
the
conundrum
of
competing
via
configurable
products,
showing
that
firm
responsiveness
gains
obtained
through
PCA
are
reflected
in
higher
sales
but
not
in
higher
margins,
due
to
linear
growth
in
manufacturers’
operating
cost.
Third
and
last,
this
study
contributes
to
Raisch’s
et
al.
(2009)
call
for
more
fine-grained
research
on
the
ambidexterity-performance
link.
That
is,
we
show
that
decisions
to
pursue
ambidexterity
in
the
context
of
industrial
equipment
man-
ufacturers
should
be
taken
with
due
caution
because
PCA
unevenly
impacts
different
dimensions
of
firm
performance,
and
such
impact
is
indirect
and
subject
to
contingencies.
2.
Theoretical
background
We
provide
a
brief
overview
of
the
industrial
equipment
manu-
facturing
setting
and
discuss
how
these
firms
develop
PCE
and
PCI
capabilities
as
well
as
their
connections
to
the
dual
goals
of
control-
ling
and
promoting
variation
within
the
manufacturer’s
products
and
processes.
We
also
review
findings
from
the
ambidexterity
literature
that
are
relevant
to
understand
how
PCA
impacts
firm
performance
for
industrial
equipment
manufacturers.
2.1.
Product
configuration
in
industrial
equipment
manufacturing
Industrial
equipment
manufacturers
offer
durable
goods
that
are
highly
customized
to
fit
customers’
production
processes.
Cus-
tomization
in
these
firms
entails
a
trade-off
with
responsiveness
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