M2M Communications Improve Customer Experience

CAN
MACHINE-‐TO-‐MACHINE
COMMUNICATIONS
BE
USED
TO

IMPROVE
CUSTOMER
EXPERIENCE
IN
A
SERVICE
ENVIRONMENT?

Shaun West, Dominik Kujawski and Paolo Gaiardelli

ABSTRACT

Purpose:

The
purpose
of
this
paper
is
to
identify
ways
in
which
Machine-‐to-‐Machine
(M2M)
communication

can
be
used
by
product-‐based
manufacturing
firms
to
deepen
and
broaden
the
service
aspects
of

their
customer
value
proposition.
The
expectation
is
that
an
improved
customer
value
proposition

leads
to
improved
customer
experience,
and
through
this
to
improved
customer
retention.

Design/methodology/approach:

The
approach
taken
has
been
two-‐fold:

1. a
literature
review
to
understand
what
is
available
in
a
B2B
environment;

2. obtaining
initial
feedback
from
surveys
and
interview
with
equipment
owners
and
operators,

suppliers
of
condition
monitoring
systems
and
other
stakeholders
to
understand
the

different
value
propositions.

It
was
considered
important
to
widen
the
horizon
of
‘condition
monitoring’
to
provide
as
many

different
ways
to
improve
the
customer
experience
as
possible.
The
literature
review
was

undertaken
based
on
the
broader
definition
of
condition
monitoring.
The
review
was
not
limited
to

the
academic
press
but
expanded
to
include
trade
journals
and
websites.
The
M2M
impact
on

human-‐to-‐human
interactions
was
also
considered.

Over
15
interviews
with
stakeholders
were
undertaken
so
that
their
perception
of
the
value

proposition
could
be
understood.
All
were
from
the
B2B
environment
and
with
interests,
of
some

form,
in
high-‐value
equipment.
This
required
detailed
segmentation
based
on
how
data
was

consumed
–
each
segment
had
different
outcomes
that
concerned
them.

Findings:

M2M
can
be
used
within
the
internet
of
things
to
improve
the
customer
experience.
However
there

are
many
risks
and
negative
aspects
that
limit
the
possible
gains:

• the
‘customer’
may
not
understand
what
they
actually
need;

• loss
of
personal
interactions
can
lead
to
a
perception
of
a
lower
level
of
value;

• clear
customer/use
segmentation
must
be
undertaken;

• each
customer
persona
must
have
a
clear
value
proposition;

• there
must
be
transparency
in
the
data
collection;

• the
data
collected
must
be
used
openly
for
root-‐cause-‐analysis
rather
than
defensively
to

protect
warranty
positions;

• the
data
can
be
used
to
support
new
product
and
service
development.

Originality/value:

This
remains
a
new
area
for
development
for
many
manufacturing
firms
in
the
B2B
space.
The

technology
is
proven
yet
there
are
numerous
firms
that
are
unable
to
monetise
the
monitoring
they

undertake
for
their
customers.
The
value
of
this
paper
is
that
it
develops
a
process
to
support
the

application
of
M2M
monitoring
by
identifying
key
tasks
to
help
firms
develop
an
effective
customer

value
proposition.

Keywords:
Servitization,
internet
of
things,
value
proposition,
customer
experience,
technology

communication.

West, Kujawski and Gaiardelli
4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
Rey
Juan
Carlos,
Madrid,
Spain
2

1 INTRODUCTION

For
many
years,
machine-‐to-‐machine
communication
has
been
growing
in
the
industrial
product

market.
Today
the
terms
“Industry
4.0”
and
“Internet
of
Things”
are
terms
that
are
often
used.
The

promise
of
the
technology
is
that
with
data
collected
from
the
equipment
and
machines

communicating
directly
with
each
other
manufacturing
processes
will
become
more
efficient.
This

has
already
been
seen
in
the
case
of
CAT’s
fleet
monitoring
system
(CAT,
2015);
a
fleet
monitoring

solution
for
lorries
(Aston,
2015)
and
has
also
been
used
in
many
process
industries
successfully

(OSISoft,
2015).

The
data
collected
has
in
some
of
these
cases
been
used
to
deepen
and
broaden
the
service
aspects

of
the
customer
value
proposition
delivered
by
these
firms.
The
firms
can
design
their
service

delivery
systems
to
meet
the
outcomes
desired
by
their
customers
and
in
some
cases
then
to

integrate
their
processes
into
the
processes
of
their
customers.
This,
according
to
Neely
(2008),

increases
the
degree
of
customer
integration
and
leads
to
increased
customer
retention.

To
deliver
advanced
services
(Bains
et
al,
2011)
it
is
often
necessary
to
have
operational
and

technical
data
from
the
equipment.
GE
Energy
Services
has
been
very
successful
with
this
with
its

contractual
services
for
both
industrial
and
aero
gas
turbines;
Rolls
Royce
similarly.
In
both
cases,
the

firms
can
move
to
an
hourly
fee
structure
as
they
have
operational
and
technical
data
on
the

machines
for
which
they
are
providing
services.
Understanding
the
equipment
operation
and

condition
means
that
they
can
drive
productivity
in
the
equipment,
typically
through
moving
to

condition-‐based
maintenance.
This
increases
their
customer's
equipment
availability
by
reducing
the

need
for
equipment
inspections.

To
provide
a
move
to
risk-‐based
maintenance
on
large
equipment
requires
significant
data
but
also

requires
close
co-‐operation
between
the
key
parties.
The
hypothesis
is
that
for
M2M
to
be
successful

it
must
be
predicated
on
improved
customer
engagement,
which
is
based
on
effective

communication.
This
means
that
the
data
collected
must
be
converted
to
information
that
generates

discussion
and
action.
This
paper
will
examine
this
topic
through
a
literature
review,
survey
and

interviews
and
make
recommendations
on
how
customer
integrations
can
be
improved
based
on

M2M
communications.

2 METHODOLOGY

This
section
describes
the
methodology
applied
in
the
study;
it
is
broken
up
into
the
literature
review,

the
survey
and
the
interviews.

2.1 Literature
review

An
in
depth
literature
review
was
undertaken
to
assess
the
current
state-‐of-‐the-‐art,
this
included
a

review
of
both
academic
literature
and
published
examples
in
the
industrial
press.
To
keep
the

relevance
of
literature,
the
research
and
analysis
was
continuously
carried
out
throughout
the

research.
The
scope
of
the
literature
review
was:

• the
value
in
ecosystems;

• supply
chain
collaboration
creating
open
innovation;

• customer
value;

• sustainability
through
customer
engagement;

• decision
making
by
converting
data
into
information.

2.2 Survey

A
set
of
standard
questions
was
created
in
a
survey
tool
(SurveyMonkey)
and
distributed
to

stakeholders
with
an
interest
in
industrial
equipment.
The
range
of
stakeholders
targeted
ranged

across
asset
owners,
system
suppliers,
Original
Equipment
Manufacturers
(OEMs),
consultants
and

4th
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2015)

November
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2015,
Universidad
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Carlos,
Madrid,
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3

technology
investors.
The
survey
was
designed
to
be
completed
within
10-‐15
minutes
to
help
with

completion
rates.
The
survey
was
broken
up
into
the
following
sections:

• stakeholder
analysis
(eg,
type
of
business,
position
in
supply
chain);

• systems
today
(eg,
Do
they
help
you
achieve
the
outcomes
that
are
important
for
you?
What

outcomes
are
you
expecting
from
the
equipment
monitoring
in
terms
of
operations,

maintenance?);

• issues
associated
with
monitoring,
warranty,
and
equipment
operation;

• issues
associated
with
data
ownership
and
information
sharing;

• issues
associated
with
unplanned
downtime;

• an
understanding
of
the
gaps
between
what
stakeholders
expect
and
what
is
delivered

today.

Each
of
the
sections
included
an
open
question
allowing
direct
feedback.
The
questions
themselves

were
quantitative
to
enable
analysis.

The
survey
was
distributed
to
the
target
stakeholders
using
direct
methods
(email)
and
indirectly
(via

LinkedIn
topic
area
groups).
The
stakeholders
questioned
were
expected
to
have
a
general
interest

or
specific
interest
in
communication
issues.

2.3 Interviews

Based
on
the
initial
analysis
of
the
survey
results,
an
agenda
for
the
follow
up
interviews
was

created.
15
follow
up
interviews
were
undertaken
to
gain
a
more
detailed
insight
into
the
survey

results.
Each
interview
was
scheduled
for
45
minutes
and
consisted
of
the
following
questions:

• What
are
the
best
customer
value
propositions
you
have
seen?

• What
are
the
negative
aspects
of
monitoring?

• Who
should
own
the
data?

• How
should
data
be
accessed
and
shared?

• Have
you
experience
of
spying
vs
transparency?

• How
does
smart
(remote)
monitoring
improve
customer/supplier
interactions?

• Does
it
improve
OEM/customer
contact?

• How
could
the
contact
be
improved
with
the
data
flows?

• Does
the
OEM
get
the
data
they
need
at
the
right
time?
How
do
2nd
tier
OMEs
get
data?

• How
does
the
OEM
use
the
data
to
improve
their
product?
(eg,
product
development
or

existing
operations
or
maintenance?)

• What
do
you
learn
from
the
data,
what
is
the
most
surprising
aspect?

• Does
the
value
outweigh
the
cost?

The
interview
data
was
then
grouped
into
common
themes
to
allow
for
analysis.
Key
lessons
were

distilled
from
the
interviews
and
are
presented
in
this
paper.

3 RESULTS
AND
DISCUSSION

This
section
lays
out
arguments
from
the
literature
and
then
moves
into
the
finding
based
on
the

data
collected
and
closes
with
a
discussion.

3.1 Literature
review

In
their
shift
to
service
business,
manufacturers
firstly
focus
on
introducing
technologies
to
increase

the
efficiency
of
their
service
operations
(Agnihothri
et
al,
2002;
Kowalkowski
and
Brehmer,
2008).

This
requires
the
redesign
and
standardization
of
service
activities
(Kindström
and
Kowalkowski,
2009;

Brax
and
Jonsson,
2009).
Then,
as
service
orientation
becomes
more
intense,
digital
technologies
are

incrementally
leveraged
to
differentiate,
extend
and
complement
the
company’s
offer
(Kindström
and

4th
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2015)

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Carlos,
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Spain
4

Kowalkowski,
2009,
Belvedere
et
al,
2013).
This
can
be
the
case
of
remote
monitoring
systems,

diagnostics
&
prognostics,
reporting
&
analytics
services
that
are
bundled
with
the
product
to
raise
the

quality
of
customer
support
and
get
competitive
advantage.
However,
as
suggested
by
Harmon
et
al

(2011)
firms
can
also
exploit
technologies
to
design
radically
new
solutions
and
create
discontinuous-‐
breakthrough
innovation.

In
use
oriented
service
offerings,
smart
services
are
focused
to
provide
any-‐time-‐anywhere
access
to

the
specialised
resources
(products,
skills,
applied
knowledge),
in
either
individual
or
shared

consumptions,
in
order
to
enable
the
value
creation
process
(eg,
customers
create
value-‐in-‐context).

The
role
of
technology
as
an
enabler
of
servitization
is
recognised
by
many
authors
as
essential

(Neely,
2008;
Storbacka,
2011).
In
particular,
both
Neely
(2008)
and
Bains
et
al
(2011)
confirm
that
it

is
a
requirement
equipment
for
advanced
services
where
“pay-‐per-‐unit”
is
applied.

The
convergence
of
data
availability
and
information
processing
technology
boosts
value
creation,

because
technology
adoption
requires
a
redesign
and
a
standardization
of
operating
processes.

Thanks
to
the
enabling
technology,
a
better
visibility
of
the
asset
in
use
(in
terms
of
operating

conditions,
time
in
use,
and
location)
is
available.
This
allows
to
speed
up
service
activities,
improve

equipment
design
and
operation
behaviour
and
reduce,
at
the
same
time,
service
delivery
costs

(Lightfoot
et
al,
2011).

The
shift
from
“you
are
what
you
own”
to
“you
are
what
you
can
access”,
the
emergence
of

collaborative
consumptions
(Botsman
and
Rogers,
2010),
internet
facilitated
sharing
(Agrain,
2012)

and
access
based
economy
(Bardhi
and
Eckhardt,
2012),
as
well
as
a
market
getting
more
fluid,

facilitating
connection
and
share
resources
(Chandler
and
Vargo,
2011),
supported
by
the

improvement
of
product
reliability
and
availability,
enabled
by
mobile
devices
and
appliances
for

employees
and
customers
of
service
division
(Fano
and
Gershman,
2002),
information
systems
that

enable
field
operations
(Kowalkowski
et
al,
2014)
rather
than
condition
monitoring
systems
(Turunen

and
Finne,
2004),
gives
the
opportunity
to
introduce
new
business
models.
These
are
characterised

by
a
changed
notion
of
asset
ownership
and
management.
In
addition,
the
easy
access
to
real-‐time

information
provides
also
the
opportunity
to
develop
a
better
understanding
of
customer

behaviours,
easing
the
development
of
smart
solutions,
that
are
“fundamentally
pre-‐emptive
rather

than
reactive”
(Allmendinger
and
Lombreglia,
2005,
p.2).

Finally,
technology
enables
comprehensive
vertical
and
horizontal
information
sharing
and

coordination
in
all
directions
between
department,
divisions
and
network
partners
supporting
the

implementation
of
the
product-‐service
strategy
(Martinez
et
al,
2011;
Auramo
and
Ala-‐Risku,
2005).

A
large
amount
of
research
dealing
with
technology-‐driven
service
innovation
in
service
business
has

been
undertaken
to
understand
how
smart
service
initiatives
reframe
competitive
landscapes.
The

literature
review
of
the
literature
on
this
topic
reveals
the
existence
of
different
perspectives
taken

into
consideration
and
briefly
described
in
the
following.

The
key
themes
of:

• value
is
in
the
ecosystem;

• supply
chain
collaboration
creating
open
innovation;

• customer
value;

• sustainability
through
customer
engagement;

• systems
must
help
the
owner/operator
to
make
the
right
decisions,
technical
info
then

supports
business
decision
making.

will
now
be
developed
further
in
the
following
sections.

4th
International
Conference
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Business
Servitization
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2015)

November
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2015,
Universidad
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Carlos,
Madrid,
Spain
5

3.1.1 Value
is
in
the
ecosystem

According
to
Iansity
and
Levin
(2004)
the
metaphors
of
keystones
and
ecology
are
helpful
to
think

about
the
business
environment
of
a
company.
Iansity
and
Levin
concluded
that
the
loose
networks

of
suppliers,
distributors,
technology
providers
and
other
“components”
of
the
ecosystem
affect
and

are
affected
by
the
creation
and
delivery
of
a
company’s
own
offerings.
Each
member
of
an

ecosystem
shares
the
fate
of
the
whole
network
regardless
of
its
strength.
As
Clarysse,
et
al
(2014)

affirmed
(as
cited
in
Zahra
and
Nambisian,
2012)
ecosystems
are
organized
as
complex
networks
of

firms
whose
integrated
efforts
are
addressing
the
needs
of
the
end
customer
and
there
is
a
growing

consensus
that
provide
companies
with
resources
and
information
to
navigate
in
constantly
changing

compititive
environment.
Jacobides
and
MacDuffie
(2013)
said
that
the
hardest
companies
to
replace

in
the
value
chain
are
the
integrators
of
system.

Iansity
and
Levin
(2004)
present
two
ingredients
that
are
part
of
success
within
the
business

ecosystems.
First,
business
ecosystems
consist
of
a
large
number
of
loosely
interconnected

participants
who
are
dependent
on
each
other
for
their
own
mutual
performance.
Every
of
the

participants
has
its
core
competence
which
together
with
others
allow
to
constitute
value
while

individual
efforts
have
no
value
outside
the
collective
effort.
The
second
vital
element
is
the
need
for

a
“keystone”
company
that
ensures
each
member
of
the
ecosystem
remains
in
good
health.
Indeed,

such
a
firm
must
develop
new
capabilities
as
partners
orchestration
and
management
of
network

dynamics
(Kindström
and
Kowalkowski,
2014).

As
Galateanu
and
Avasilcai
(2014)
concluded
that
the
value
co-‐creation
in
business
ecosystems
can

be
realized
by
establishing
different
types
of
relations
where
the
technological
changes
have
a
major

impact
on
value
creation.
Indeed,
servitization
forces
changes
to
traditional
buyer
supplier

relationships
(Bastl
et
al,
2012;
Saccani
et
al,
2014)

The
new
trend
that
is
Industry
4.0
might
be
the
key
influencer
of
the
value
drivers
in
the
business

ecosystem.
(Bechtold
et
al,
2014)
state
the
smart
services
and
smart
products
will
increase
the
scope

of
manufacturers
value
creation
activities.
Especially
manufacturing
companies
based
in
high-‐cost

countries
need
to
leverage
this
opportunity
to
sustain
competetive
edge
and
drive
growth.

In
such
a
context,
as
stated
in
(Bechtold
et
al,
2014)
vertical
and
horizontal
integration
based
on

digital
technologies
allows
companies
to
drive
value
through
transparency
and
process
automation.

Connected
supply
chains
allow
identification
all
along
the
production
process,
which
enable

manufacturers
to
be
more
responsive
to
change
requests.
Thus,
the
maximum
level
of
transparency

can
be
established
over
the
whole
supply
chain.
This
will
form
a
centerpiece
for
operation
excellence

in
any
Industry
4.0
strategy.
The
"Ecosystem:
people,
machines
and
software,”
(2015)
website
states

that
the
Industry
4.0
ecosystem
consists
not
only
of
smart
factories
and
intelligent
products,
it
also

includes
people.
It
is
a
question
of
allowing
people
to
perform
high
quality
and
creative
work
and

provide
them
with
opportunity
to
achieve
a
work/life
balance
with
just
as
much
flexibility
as
the

production
systems
of
the
future
that
people
will
control.

3.1.2 Supply
chain
collaboration
creating
open
innovation

According
to
Mathuramaytha
(2011)
today
almost
all
organization
are
in
the
process
of
adopting
the

supply
chain
activities
and
make
them
competitive.
Collaboration
is
the
driving
force
behind
effective

supply
chain
management
and
improves
performance.
It
may
share
large
investments,
pool
risks
and

share
resources,
reasoning
growth
and
return
on
investment.
Both
intra-‐firm
and
inter-‐firm

collaboration
is
crucial
for
servitization
(Neu
and
Brown
2005)
and
is
part
of
the
open
innovation

paradigm
defined
by
Chesbrough
et
al
(2007).

4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
Rey
Juan
Carlos,
Madrid,
Spain
6

As
stated
by
DeAngelis
(2014)
using
sensors
to
monitor
manufacturing
equipment
and
the

environment
is
nothing
new,
but
using
those
sensors
to
communicate
with
other
equipment
and

automatically
feed
data
is
one
of
the
newest
frontiers.
In
Figure
1,
there
is
presented
a
business

scenario
that
shows
intelligent
communication
system
between
different
parts
of
the
value
chain

within
Industry
4.0.

Figure
1
Typical
business
scenario
in
the
Internet
of
Things
(Schönthaler,
2015)

Figure
1,
presents
communication
between
supplier,
carrier,
shipper,
producer
and
his
customer.
As

stated
in
(Schönthaler,
2015)
this
digital
transformation
of
the
value
chain
provides
the
supplier
with

insight
to
the
inventory
directly
on
the
shelf,
so
proactive
actions
are
possible.
From
this
new
way
of

collaboration
arises.
According
to
Siebenmorgen
(2015)
a
fundamental
step
in
the
direction
of

Industry
4.0
is
the
digital
modelling
of
the
value
chain,
where
a
large
number
of
users
networked

through
cooperation
platform
benefit.
Siebenmorgen
underlines
that
the
trust
of
all
companies

involved
must
be
gained,
otherwise
no
Industry
4.0
business
model
will
be
successful.

Even
smart
services
initiatives
favour
new
forms
of
collaboration
and
cooperation,
in
certain
cases,

rivals
are
asked
to
collaborate
(coopetition).
Indeed,
Smart
services
initiatives
are
likely
to
reshape

the
competitive
landscape
and
change
the
traditional
industry
boundaries.

3.1.3 Customer
value

Anderson
et
al
(2006)
explains
the
importance
of
customer
value
that
they
value
forces
suppliers
to

focus
on
what
their
offerings
are
really
worth
to
their
customers.
The
paper
described
a
systematic

method
to
help
with
the
development
of
value
propositions
to
that
are
meaningful
to
their
target

customers.
With
M2M
services
customer
value
must
continue
to
be
developed,
in
fact,
“smart

services”
encapsulates
more
than
just
mere
technology.
This
concept
also
refers
to
a
more

customercentric
view
and
strategy,
that
transform
that
technology
into
a
value
added
services
from

the
customer’s
point
of
view
according
to
Reinartz
and
Ulaga
(2014).
According
to
(Osterwalder
and

Pigneur,
2002)
value
is
created
through
use,
a
reduction
of
the
customer’s
risk
or
by
making
his
life

easier
through
reduction
of
his
efforts.
Capturing
the
value
can
be
during
value
creation,
purchase,

consumption,
its
renewal
ot
its
transfer.
The
value
and
price
level
can
be
compared
to
one
of
the

companies
competitor’s.
To
deliver
the
right
value
the
target
customer
needs
to
be
defined,
the

means
to
reach
and
communicate
with
him,
as
well
as
the
relational
strategy
to
establish
with

customer.
Campbell
et
al
(2011)
state
that
“advances
in
technology,
especially
information

technology,
and
widespread
use
of
the
Internet,
can
be
viewed
as
a
catalyst
that
facilitates
the
shift

4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
Rey
Juan
Carlos,
Madrid,
Spain
7

in
the
traditional
service
boundary
between
provider
and
customer
towards
either
self-‐service
or

super
service”.

However,
while
services
supporting
the
products
(SSP)
can
be
easily
standardized
to
offer
a
“digital

version”,
services
supporting
the
customers
(SSC)
always
show
a
big
deal
of
variety
due
to
people

interactions
and
customer-‐specific
situations.
Thereby,
it
is
said
that
“technology
may
not
be

appropriate
in
the
context
of
an
SSC
business
orientation
given
that
these
services
are
directed
at
the

client
and
customized
rather
than
to
the
product
and
standardized”
(Antioco
et
al,
2008,
p.
351).

3.1.4 Sustainability
through
customer
engagement

As
well
as
Park
et
al
(2012)
suggest,
digital
technologies
integrate
and
combine
product
and
services

in
different
ways,
to
deliver
a
product-‐service
systems
that
brings
also
social
and
environmental

benefits
Tukker
(2004
and
2013).

Most
marketers
think
that
interacting
as
much
as
possible
with
customer
will
allow
them
to
build

strong
relationships
with
the
customer
(Freeman
et
al,
2012).
Not
all
of
the
customers
want
to
have

relationship
with
the
brand;
it
is
essential
to
determine
different
expectations
in
different
target

groups.
Also,
interaction
do
not
build
relationships
-‐
shared
values
build
them.
The
shared
value
is
a

belief
that
both
brand
and
consumer
have
about
a
brand’s
higher
purpose
and
philosophy.
The
more

interaction
is
not
always
better,
instead
of
continuous
demanding
of
customer
attention
try
to

reduce
the
cognitive
overload
consumers
feel
for
the
brand
(Freeman
et
al,
2012).

As
stated
in
Bloem
(2014)
the
best
example
of
engagement
are
applications
that
are
directly
related

to
interaction
with
blue-‐collar
members
of
staff
or
end
users,
through
measuring
and
regulating,

maintenance
and
software
upgrades.
For
example,
Philips
allow
consumers
to
operate
lamps
as
they

wish
and
in
this
way
get
data
to
implement
their
tasks
much
more
efficiently.
This
allows
Philips
to

be
connected
with
the
customer
24/7,
expand
user
experience
through
improved
human-‐machine

interaction
and
products
are
a
part
of
the
end-‐to-‐end
ecosystem.
Figure
2
presents
sustainable

customer
engagement
model
that
can
be
achieved
when
company
makes
the
relationship
with
the

customer
visible,
tangible,
empowering
and
emotional
through
all
phases
of
product
and
service

consumption.

Deloitte
(2014)
report
presents
sustainability
as
both
a
valuable
risk-‐management
tool
and
long-‐term

contribution
to
the
bottom
line.
Sustainability
as
a
value
proposition
is
still
waiting
to
be

implemented
in
many
corporate
strategies
and
that
is
for
potential
leveraging
customer

engagement.
It
allows
to
increase
customer
loyalty,
advocacy
and
repeat
conversions.
A
potentially

engaged
customer
generates
significant
premiums
in
terms
of
money,
profitability,
and
revenue
and

relationship
growth,
for
the
following
reasons:

• transparency
engagement
framework
refers
to
efforts
where
business
effectively
informs
the

consumers
of
the
sustainability
performance
of
a
specific
product.

• the
partnership
engagement
refers
to
improving
sustainability
by
inviting
customers
to

participate
actively
in
partnership
with
the
third-‐party
organization.

• the
life
cycle
engagement
is
when
business
strives
to
engage
customers
in
parts
of
the
entire

life
cycle
of
a
specific
product.

• the
collaborative
engagement
platform
refers
to
business
applying
modern
network

technology
to
create
with
customers
shared
value.

4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
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Juan
Carlos,
Madrid,
Spain
8

• Figure
2
Sustainable
Customer
Engagement
by
(Deloitte,
2014)

3.1.5 Systems
must
help
the
owner/operator
to
make
the
right
decisions,
technical
data
then

supports
business
decision
making

McAfee
and
Brynjolfsson
(2012)
state
that
managerial
decisions
are
greater
than
technical
challenges

starting
with
the
role
of
the
senior
executive
team.
The
most
critical
aspect
of
big
data
is
the
impact

on
how
decisions
are
made
and
by
whom.
A
successful
and
effective
company
puts
information
and

the
relevant
decision
right
in
the
same
location.
Expertise
is
not
often
where
it
used
to
be
due
to

create
and
transferred
information.
Maximization
of
a
cross-‐functional
cooperation
allows
the
right

usage
of
data.
The
idea
of
the
right
decision-‐making
process
lies
in
delivery
the
right
data
to
people

who
understand
the
problems
and
who
have
problem-‐solving
techniques
to
effectively
use
them.

Rowley
(2007),
uses
the
DIKW-‐hierarchy
(Figure
3)
as
a
model
to
allow
data
to
be
translated
into

information,
knowledge
and
eventually
wisdom.
Only
with
information
can
management
actions
be

taken.

Figure
3
Translation
of
data
into
information
to
support
business
decision
making

3.2 Survey
and
interview
results

The
survey
population
was
32,
from
which
interviews
were
conducted
with
15
stakeholders

representing
a
range
of
industry
players:

• 20%
were
OEMs
with
24%
being
engaged
in
OEM
services;

• 20%
were
equipment
operators
with
41%
being
involved
in
equipment
maintenance

services;

• 20%
of
those
who
responded
were
asset
owners,
a
further
7%
were
pure
financial
investors;

• 30%
provided
consulting
services.

4th
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2015)

November
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2015,
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Carlos,
Madrid,
Spain
9

The
total
numbers
add
up
to
more
than
100%
as
many
of
the
firms
were
engaged
in
more
than
one

activity.
This
confirms
that
the
population
that
responded
provided
a
wide
view
of
the
stakeholders

in
the
equipment
value
chain.

The
supply
chain
analysis
confirmed
that
both
equipment
and
service
sales
were
made
directly
to
the

end
user
and
indirectly
via
a
contractor.
This
is
common
in
many
industrial
equipment
markets

(Rosenbloom,2007)
where
new
equipment
sales
follow
a
different
channel
to
service
sales
and
the

channel
develops
on
the
phase
of
the
project.

When
asked
about
the
types
of
systems
respondents
were
using
and
how
successful
these
were
in

supporting
their
achievements,
the
two
least
reliable
systems
were
acoustic
(11%
response
rate)
and

video/photo
analysis
(11%
response
rate).
Interestingly
there
was
a
contradiction
in
that
photo/video

analysis
was
one
of
the
most
valuable
fault
finding
tools,
reflecting
that
it
is
used
largely
in
an

interactive
way
during
planned
(62%)
and
unplanned
(42%)
inspections.
Acoustic
emission
analysis

was
found
not
to
support
outcomes
successfully
yet
was
often
(50%)
used
in
fault-‐finding.
The
most

positive
outcomes
were
found
to
be
from
the
operational
data
(28%)
and
vibration
analysis
(26%).

Vibration
analysis
was
often
(53%)
used
in
fault-‐finding,
whereas
operational
data
was
not
used
as

frequently
in
fault-‐finding
(33%).
Both
methods
scored
highly
in
remote
and
continual
measurement

(>42%
of
respondents).
Performance
data,
something
that
combines
many
data
feeds,
supported

outcomes
23%
of
the
time
and
was
used
to
support
fault-‐finding
with
an
expectation
for
the
data
to

be
collected
continually
(50%).

3.2.1 Operations
and
maintenance
considerations

Operations
and
maintenance
have
a
major
impact
on
the
outcome
of
any
operation.
For
this
reason,

there
were
a
group
of
questions
around
these
topics
and
how
monitoring
can
assist
the
asset
owner

to
achieve
their
desired
outcomes.

Warranty
fulfilment
is
closely
associated
with
the
new
installation
of
equipment.
This
can
be,
as
has

been
discussed,
a
direct
sale
to
the
asset
owner
or
indirect.
Nevertheless,
the
OEM
has
warranty
and

performance
obligations
and
there
are
also
operation
and
maintenance
requirements.
For
warranty

and
equipment
operation,
within
all
responses
equal
value
was
given
to
(80-‐75%):

• ensuring
the
equipment
is
operated
and
maintained
correctly;

• feedback
on
how
equipment
is
actually
used;

• detailed
understanding
of
equipment
life
consumption;

• improving
plant
performance.

There
are
outcomes
from
monitoring
the
normal
operation
of
the
equipment,
the
three
most

important
were:

• increased
use
of
proactive
maintenance
(89%
important/very
important);

• improved
equipment
efficiency
(88%);

• stable
operation
of
the
plant
(73%).

These
points
are
associated
with
getting
more
out
of
the
equipment
and
reducing
the
costs,
which

leads
to
a
lower
per
unit
cost
of
production.

When
asked
about
the
maintenance
outcomes
that
were
important
the
three
most
important
were:

• a
desire
to
move
to
condition
(or
risk)
based
maintenance
(78%);

• to
undertake
targeted/opportunity
maintenance
(75%);

• to
drive
down
the
cost
of
maintenance
(74%).

These
points
are
associated
with
the
desired
outcome
of
a
lower
total
cost
of
ownership.

4th
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10

What
outcomes
are
expected
in
terms
of
supporting
unplanned
downtimes?
The
most
important

aspects
here
were:

• to
support
opportunity-‐based
maintenance
(77%);

• to
improve
problem
solving
(74%);

• to
allow
safe
operation
when
equipment
is
damaged
(69%).

These
points
are
associated
with
minimising
lost
production
associated
with
unplanned
downtimes.

3.2.2 Data
sharing
and
ownership

The
consensus
view
was
that
the
data
should
be
owned
by
the
equipment
owner
but
shared
within

the
ecosystem.
The
interviews
highlighted
this
to
be
a
very
emotional
issue
for
the
equipment

owners
as
they
considered
that
the
data
(technical,
operational
and
commercial)
was
commercially

sensitive.
In
interviews,
they
were
also
concerned
that
the
data
should
be
shared
and
used
within

the
ecosystem,
provided
they
understood
the
purposes
for
which
it
was
being
used.
In
details
the

three
most
important
aspects
were:

• Information/output/reporting
from
the
system
needs
customizing
(80%).

• The
data
is
commercially
sensitive
(66%).

• The
equipment
owner
should
own
the
data
(60%).

Interview
responses
confirmed
the
ownership
of
data
was
an
important
issue.
Several
of
the

interviewees
stated
clearly
that
the
data
had
commercial
value
and
that
ownership
must
be
vested

with
the
equipment
owner
and
not
the
OEM.
Further
views
here
suggested
that
the
firm
doing
the

measuring
should
own
the
data
and
another
said
it
depends
on
who
takes
the
risk.

In
contrast
to
the
data
ownership
question,
there
was
general
agreement
from
the
interviewees
that

faster,
better
and
cheaper
solutions
could
be
generated
by
the
ecosystem
when
the
technical,

operation
and
commercial
data
were
shared.
The
use
of
data
and
the
anonymity
of
data
remained

key
concerns.

3.2.3 Descriptions
of
customer
value
propositions
and
value
for
money

The
utilities
and
OandG
firms
provided
some
of
the
most
attractive
examples
of
customer
value

propositions,
typical
themes
being:

• maintenance
–
maintenance
cost
out,
moves
to
risk-‐based
maintenance;

• advanced
services
–
underpinned
by
monitoring,
we
could
de-‐risk
our
service
contracts;

• operations
–
data
showed
that
the
OEM
damaged
the
equipment
during
commissioning;

operational
technical
data
helps
increase
speed
of
troubleshooting;
value
comes
from
a

holistic
view;
we
use
the
combined
data
for
our
business
reporting
and
optimization.

When
asked
in
the
survey
if
the
monitoring
system
that
was
used
supported
the
desired
outcomes:

only
in
33%
of
the
responses
did
the
system
provide
all
of
the
data
that
was
required.
This
clearly

shows
that
there
the
value
propositions
are
not
matching
the
expectations.
Yet
owner/operators

were
providing
examples
of
positive
value
propositions
and
had
a
desire
to
continue
using
and

developing
the
technology.

3.2.4 Negative
aspects
of
monitoring

There
were
a
number
of
negative
aspects
that
were
in
contradiction
to
each
other.
This
suggests
a

weak
fit
between
today's
problem
and
solution
and
that
therefore
a
clear
value
proposition
has
not

yet
been
identified.
This
was
typically
found
when
the
OEM
chose
a
marketing
“push”
to
sell
the

technology,
with
the
owner/operator
considering
that
the
technology
was
being
forced
upon
them.

4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
Rey
Juan
Carlos,
Madrid,
Spain
11

Data
overload
was
clearly
a
problem
for
some
and
related
to
the
integration
of
the
systems
and
the

relevance
of
the
data
presented.
Questioning
on
these
issues,
there
was
a
preference
for
one

management-‐level
system
that
could
present
the
data
in
a
more
relevant
way
for
those
consuming

the
data.

Base-‐level
concerns
about
fault
reporting,
data
security
and
a
reporting/controlling
vs
transparent

approach
were
described
and
discussed
separately.
Here
there
were
concerns
from
equipment

owners/operators
about
the
OEM
spying
on
them,
yet
there
was
also
an
expectation
of
pro-‐active

OEM
support.
The
OEMs
also
had
a
concern
that
owner/operators
did
not
want
to
“expose
their

stupidity”.
A
Liquefied
Natural
Gas
(LNG)
plant
Operations
and
Maintenance
(O&M)
team
member

said
they
“Need
to
know
what
is
needed
by
whom
and
why”.

3.2.5 Improving
customer/supplier
interactions
and
the
sharing
of
data

The
consensus
view
from
the
interviews
was
that
sharing
data
should
improve
customer/supplier

interactions.
How
to
do
this
is
part
of
the
value
proposition;
however,
the
findings
were
that:

• it
should
be
proactive
so
that
the
OEM
can
be
ready
to
help
with
trouble
shooting
or
spares;

• information
must
flow
in
both
directions,
allowing
one
set
of
data
to
be
used
to
help
improve

the
quality
of
trouble
shooting;

• joint
problem
solving
helps
to
mature
the
relationships
and
encourages
more
interactions
at

different
levels;

• sharing
of
resources
helps
to
drive
out
cost
yet
risks
deskilling
staff.

One
OEM
respondent
went
as
far
as
saying
that
“…you
should
work
'open
book'
with
the
data…”.

The
move
to
outcome-‐based
solutions
with
an
alignment
of
objectives
creates
value
in
some
cases.

Embedding/sharing
of
resources
was
viewed
positively
by
a
number
of
the
interviewees.
There
is
an

effort
required
by
all
parties
to
learn
to
work
closely
together,
and
focusing
on
high-‐level
goals
(e.g.

total
cost
of
ownership)
rather
than
transaction
cost
was
a
key
lesson.

Sitting
together
in
this
way
and
understanding
the
equipment
owner’s
business
objectives
was

considered
important
by
many
respondents.
Getting
people
to
do
this
requires
effort
and
maturity.

The
OEMs
working
in
joint
data
analysis
centres
with
the
owner/operator
considered
this
a
good

approach
as
it
could
assist
the
combining
of
technical
and
commercial
reporting,
helping
all
parties
to

focus
on
improving
operations
or
as
one
interviewee
said
“finding
ways
to
use
customer
waste
to

generate
value”.

The
consensus
view
was
that
second
tier
OEMs,
unless
suppliers
of
critical
plant
items,
had
a
tough

time
getting
access
to
the
data
they
need
when
they
need
it.
Here
the
system
integrator
was

considered
a
key
party
in
the
ecosystem
to
support
access;
however
a
number
of
respondents

mentioned
that
warranty
and
other
contractual
issues
may
create
barriers.

3.2.6 Product
improvement

The
use
of
the
data
collected
to
improve
the
product
was
considered
important
in
the
interviews.
An

investor
said
that
it
was
a
“must”,
the
owner/operators
said
that
the
OEMs
were
too
slow
to

integrate
what
they
learned
into
new
product
development
or
service
upgrades.
GE
was
considered

as
an
OEM
that
took
what
they
learned
from
monitoring
and
integrated
it
into
both
service
upgrades

and
new
products.
The
data
should
also
be
used
to
support
changes
to
operations
and
maintenance

(e.g.
longer
intervals
between
maintenance)
based
on
both
the
technical
and
operational
data.
The

only
way
this
can
be
done
is
through
closer
working
with
the
stakeholders
within
the
ecosystem.

4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
Rey
Juan
Carlos,
Madrid,
Spain
12

3.2.7 Lessons
from
the
interviews
from
the
use
of
monitoring
technologies

In
balance,
the
interviewees
said
that
there
was
value
from
using
monitoring
systems
and
that
the

ecosystem
created
more
value
than
individual
parties
were
able
to
do.
This
means
that
there
must

be
significant
integrations
at
a
personal
level
within
the
ecosystem
to
allow
this
co-‐creation
to
take

place.
On
an
interpersonal
level,
a
number
of
the
interviewees
stated,
“once
the
parties
start

working
together
you
start
to
get
more
trust”.

A
number
also
commented
that
the
monitoring
solution
“ran
the
risk
of
being
taken
for
granted”,
in

which
case
may
lose
it
importance
in
the
view
of
the
owner/operator.
This
was
because
the
system

tended
to
focus
on
risk
mitigation
meaning
that
a
failure
was
prevented.
Other
findings
from
the

interviews
were:

• Low
cost
sensors
(video)
have
enough
on-‐board
computing
power
(investor);

• Our
flash
dryer
was
having
problems:
it
was
found
before
it
caused
problems
(utility);

• Once
you
start
working
together
you
start
to
get
more
trust
(LNG);

• GE
medial
have
a
super
value
proposition
for
their
equipment
in
hospitals
(OEM);

• Must
work
around
the
business
solution
and
then
the
technical
solution
can
be
found

(system
integrator);

• Solution
comes
best
from
co-‐creation
around
the
ecosystem
(consultant);

• The
customer
can
pull
you
out
of
the
problem
(consultant);

• A
modern
train
can
have
10M
data
points
per
trip
–
must
be
provided
in
an
understandable

form
(consultant).

3.2.8 Overview
of
the
survey
and
interview
results

In
summary,
the
main
findings
of
the
survey
and
the
interviews
were
segmented
into
two
themes,

customer
relationships
and
underlying
considerations,
listed
in
Table
1.

Interview
results
suggest
that
the
best
solutions
provided
information
to
allow
people
to
make
the

decisions,
rather
than
the
machines
taking
their
own
decisions
based
on
pure
technical
data.
A

process
in
Section
3.3
below
provides
one
possible
framework
to
help
OEMs
to
help
integrate

customer
experience
into
the
development
and
operation
of
systems.

Table
1
Main
issues
that
can
drive
customer
relationships
and
underlying
considerations,

identified
from
the
interviews

Customer
relationships
Underlying
considerations

• The
‘customer’
may
not
be
able
to
describe

clearly
what
they
need,
yet
many
are
able
to

describe
the
outcomes
they
are
trying
to

achieve;

• Clear
customer/use
segmentation
must
be

undertaken
based
on
position
in
supply

chain/ecosystem
and
the
outcomes
they
are

seeking;

• Each
customer
persona
must
have
a
clear

value
proposition,
it
is
no
long
sufficient
to

have
one
value
proposition
for
‘customers’;

• Loss
of
personal
interactions
can
lead
to
a

perception
of
a
lower
level
of
value
as

customers
take
the
service
as
the
new
norm.

• There
must
be
transparency
in
the
data

collection
and
as
GE
say,
a
‘single
point
of

truth’,
this
means
that
every
party
in
the

ecosystem
should
use
the
same
data
source;

• The
data
collected
must
be
used
openly
for

rather
than
defensively

to
protect
warranty
positions,
this
requires

trust
between
the
players
in
the
ecosystem;

• There
are
internal
consumers
of
the
data

collected
and
this
can
support
new
product

and
service
development,
so
the
data

(technical
and
operational)
must
flow
down

to
them.

4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
Rey
Juan
Carlos,
Madrid,
Spain
13

3.3 Process
description

Using
the
results
of
the
survey
and
the
interviews
and
integrating
these
with
the
best
practices

identified
in
the
literature,
the
authors
have
designed
a
process
to
assist
industrial
firms
to

understand
better
the
complexities
of
how
to
integrate
these
new
technologies
into
their
existing

offerings
to
provide
the
customer
with
the
value
that
they
are
expecting.
This
is
not
a
simple
task
as

every
OEM
exists
in
a
different
position
in
their
particular
ecosystem
and
this
makes
it
more
critical

that
the
OEM
comprehends
the
ecosystem,
so
that
they
can
understand
how
and
where
the
know-‐
how
exists.
A
proposed
process
is
shown
in
Figure
4;
this
is
developed
further
below.

Figure
4
Proposed
process
description
to
assist
OEMS
to
develop
a
customer
value
proposition

for
M2M
communications

3.3.1 Where
do
you
sit
in
the
ecosystem
and
who
bring
what
value?

The
purpose
of
this
element
is
to
provide
context
for
the
OEM
so
that
they
understand
where
they

sit
within
the
ecosystem.
They
can
then
understand
who
and
what
they
can
influence.
More

importantly
when
it
comes
to
joint
problem
solving,
they
can
then
identify
the
parties
who
may
be

able
to
support
them
to
create
a
solution
for
the
owner/operator
of
the
equipment.
This
is
an
open

innovation
paradigm
(Chesbrough
et
al,
2007)
in
that
the
solution
is
developed
with
the
help
of

external
partners.

3.3.2 Do
you
understand
your
customer's
gains
and
pains?

Within
Service
Design
(Tripp,
et
al,
2013)
empathy
mapping
is
an
important
activity
to
gain
a
fuller

understanding
of
your
customer.
Here
it
has
been
seen
that
many
OEMs
have
complex
supply
chains

and
ecosystems
and
therefore
understanding
key
stakeholders
becomes
increasingly
important.

Users
outside
the
key
target
group
of
the
system
may
have
an
interest
in
the
information
that
the

data
from
such
systems
represents.
Consumption
of
the
information
must
(Rowley,
2007)
be
in
a

form
that
creates
action;
this
means
that
the
data
must
be
transformed
into
information
relevant
to

the
person
consuming
it.

3.3.3 Do
you
understand
the
customer’s
outcomes
and
their
influencers?

How
easy
is
it
for
the
OEM
to
understand
the
outcomes
that
the
customer
is
expecting?
This
may

explain
why
so
many
of
the
respondents
were
only
partially
happy
with
remote
monitoring.
The

outcomes
or
goals
that
the
owner
is
seeking
must
be
translated
into
a
form
that
is
relevant
and

controllable
within
the
environment
of
the
monitoring
(Bostsman
and
Rogers,
2010).
The

relationship
between
the
technical
issues
and
the
commercial
implications
are
a
key
demand
from

the
owner/operators
of
the
equipment.

3.3.4 Can
you
clearly
describe
the
customer
value
proposition?

The
owner/operators
that
were
interviewed
were
better
able
to
describe
the
customer
value

propositions
they
were
expecting
than
were
OEMs.
Marketing
theory
says
that
the
seller
must
be

able
to
describe
the
value
proposition
and
Osterwald
(2002)
has
provided
a
format
to
assist
OEMs
to

Where
do
you

sit
in
the

ecosystem
and

who
brings

what
value?
Do
you

understand

your
customer's

gains
and

pains?
Do
you

understand
the

customer's

outcomes
and

their

influencers?
Can
you
clearly

describe
the

customer
value

proposition?
Can
you

describe
clearly

where
the

customer’s

value
accrues?

4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
Rey
Juan
Carlos,
Madrid,
Spain
14

do
so.
Nevertheless,
the
clearest
descriptions
of
customer
value
propositions
were
from
the

owner/operators.
This
suggests
that
customer
pull
will
bring
the
technology
to
the
market.

3.3.5 Can
you
describe
clearly
where
the
customer’s
value
accrues?

As
with
the
point
on
describing
customer
value
propositions,
this
is
very
important.
It
is
specific
to

the
different
stakeholders
and
was
again
best
described
by
the
owner/operators.

4 CONCLUSIONS

The
survey
and
interview
data
were
generally
in
agreement
with
the
literature:
the
owner/operators

were
looking
for
support
with
new
M2M
solutions
that
would
increase
the
interactions
between
the

key
stakeholders.
The
expectation
was
that
joint
problem
solving
would
increase
the
speed
of

problem
resolution,
reduce
costs
and
create
better
solutions.
This
is
in
agreement
with
the
open

innovation
concept
of
Chasebrough
et
al
(2007)
and
Doblin
(2015)
who
recommend
increased

customer
engagement
in
innovation.
This
is
also
supported
by
Freeman
et
al,
2012
and
Deliotte

(2014)
where
the
customer
experience
and
shared
values
were
considered
as
a
key
sustainability

aspect.

The
degree
of
customer
engagement
must
increase
in
order
for
M2M
systems
to
deliver
the

customer
value
propositions
they
offer.
Loss
of
personal
interactions
can
lead
to
a
perceived
lower

level
of
value.
Engagement
should
be
on
a
more
individual
basis,
where
each
customer
persona
must

have
a
clear
value
proposition.
Customers
of
data
include
all
of
the
active
players
in
the
ecosystem,

so
an
understanding
of
what
each
customer
requires
needs
to
be
actively
made.
This
is
particularly

true
in
an
environment
where
the
customer
may
not
understand
what
they
actually
need.

Consumers
of
the
data
could
be
in
OEM
product
development
as
well
as
other
suppliers
in
the

ecosystem.

Data
itself
has
a
value,
and
many
stakeholders
should
be
able
to
access
the
data.
There
should
be

transparency
in
the
collection
and
future
uses
of
the
data.
The
best
relationships
were
developed

from
data
that
was
transformed
into
information
and
used
collaboratively
for
root-‐cause-‐analysis,

rather
than
defensively
to
protect
warranty
positions.
The
data
should
include
the
operational
data

as
well
as
the
technical
data
from
the
machines.

5 RECOMMENDATIONS

To
address
the
conclusions,
the
authors
have
some
recommendations
that
any
firm
that
is
creating

an
M2M
solution
for
its
customers
should
consider
during
the
development
of
the
customer
value

proposition:

• identify
who
are
your
customers
in
the
ecosystem
and
understand
the
outcomes
they
value;

• segment
your
customers
in
terms
of
the
outcomes
they
are
seeking
and
create
for
each
a

persona
with
a
clear
value
proposition
with
clear
identification
of
where
value
is
created;

• find
ways
to
engage
with
the
customer,
as
experience
is
important
in
creating
sustainability

and
the
loss
of
personal
interactions
can
lead
to
a
perception
of
a
lower
level
of
value;

• wherever
possible,
the
data
collected
must
be
used
openly
for
rather

than
defensively
to
protect
warranty
positions;

• remain
open
and
transparent
with
data
collection
and
the
use
of
the
data;

• there
are
internal
consumers
of
the
data
that
is
collected
and
this
can
support
new
product

and
service
development.

4th
International
Conference
on
Business
Servitization
(ICBS
2015)

November
19-‐20,
2015,
Universidad
Rey
Juan
Carlos,
Madrid,
Spain
15

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N.,
&
Simmons,
D.
(2002).
Leveraging
technology
to
improve
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service.
International
Journal
of
Service
Industry
Management,
13(1),
47-‐68.

Aigrain,
P.
(2012).
Sharing:
culture
and
the
economy
in
the
internet
age.
Amsterdam
University
Press.

Allmendinger,
G.,
&
Lombreglia,
R.
(2005).
Four
strategies
for
the
age
of
smart
services.
Harvard

Business
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83(10),
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ACKNOWLEDGMENTS

The
authors
would
like
to
thank
the
Lucerne
University
of
Applied
Sciences
and
Arts
and
the

university
of
Bergamo.

AUTHOR
CONTACT
DETAILS

Dr
Shaun
West

Lectuere
for
Product
and
Service
Innovation

Wirtschaftsingenieurwesen
|
innovation,

Lucerne
University
of
Applied
Sciences
and

Arts,
Switzerland

Email:
shaun.west@hslu.ch

Phone:
+41
79
770
5986

Paolo
Gaiardelli

Assistant
Professor

Department
of
Engineering

University
of
Bergamo

Email:
paolo.gaiardelli@unibg.it

Phone:
+39
035
2052385

Dominik
Kujawski

Student,
Masters
in
Science
and
Engineering

Luzern
University
of
Applied
Science
and
Art

Email:
shaun.west@hslu.ch

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