12/02/16
Servitization of the Home: IoT
Development of Use-Visibility
Measures
Dr Glenn Parry
Associate Professor of Strategy and Operations Management
University of the West of England
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Outline
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•
•
•
•
Background
Theoretical frameworks
Method
Results
Discussion
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Aim
•  Focus on the understanding of the nature
of value creation in the home
•  To use this understanding to drive the
development of a novel platform [HAT] and
associated business models
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Improving business models to
create sustainable supply chains
•  Each person in the UK
–  uses 150 litres of water1
–  produces 416Kg of domestic waste2
•  Only 24% of the 2.5 million tonnes
of plastic wrapping used was
recycled3
•  Opportunity to develop smarter
business models to support
longer life products
–  Electrical goods along could be worth
£800m p.a.
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Source: 1. WaterWise 2012. 2. 2013 figures from Defra 2015. 3. WRAP 2014
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Businesses are responsible for
their products through life
•  Firms must consider supply, use, recovery, re-use,
repair, recondition, recycle and disposal
–  but they don’t have data on product use
•  We focus upon consumer use processes as the
focus of value creation
–  Also the beginning of the reverse supply chain
•  The Internet of Things can provide useful context
specific data
–  enables the understanding of what? When? and why?
of household consumption
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References: Ashby et al., 2012
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Information asymmetry in the
home
•  Consumer has knowledge of functional
activities
–  Little information is passed back to the supplier
•  Suppliers lack post sale visibility of their
products in use
•  Contexts of use are where value is created
–  Where products are used in combination with
other resource in value creating activity
–  This is the start point of the reverse supply chain
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Research Question
How can Internet of Things be opera4onalised in the home to capture data on a consumers use of products and what are the implica4ons for supply? of 47
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Outline
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•
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•
•
Background
Theoretical frameworks
Method
Results
Discussion
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Defining the firms Business
Model
•  The design of the value creation, delivery and capture mechanism
employed by an enterprise to entice customers to pay for value and
convert those payments to profit
Teece, 2010
•  The rationale of how an organisation creates, delivers and captures
value
Osterwalder and Pigneur, 2009
•  A set of generic level descriptors that captures how a firm organises
to create and distribute value
Fuller & Morgan 2010
•  A system of interdependent activities that applies to the focal firm
and can also apply to the customer, supplier and third parties
involved in the delivery of the service
Zott & Amit 2010
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References to value or service
delivery, but no definition
•  The design of the value creation, delivery and capture
mechanism employed by an enterprise to entice customers to pay
for value and convert those payments to profit
Teece, 2010
•  The rationale of how an organisation creates, delivers and
captures value
Osterwalder and Pigneur, 2009
•  A set of generic level descriptors that captures how a firm organises
to create and distribute value
Fuller & Morgan 2010
•  A system of interdependent activities that applies to the focal firm
and can also apply to the customer, supplier and third parties
involved in the delivery of the service
Zott & Amit 2010
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What does value mean?
Conceptually we take it to be some measure of ‘goodness’ of 47
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Source: Ng, I. C. L. (2014), Creating new markets in the digital economy: Value & Worth,
Cambridge
University
Press:
Cambridge
Value perception; shift from
exchange to use
•  Defining value is challenging
–  Traditionally value is
understood as “in exchange”
–  value is frequently seemingly
‘objective’, externally defined,
and ‘given’
–  measures of value are often
firm-centric
•  An effective way to strategize
and innovate is to shift the
conceptual focus of value to
use
–  Use value describes how good
something is when you use it
Sources: Penrose, E., (1959, p25), The Theory of the Growth of the Firm, Blackwell: Oxford; Vargo, S. L. and Lusch, R.F. (2008), "Service-dominant
logic: continuing the evolution", Journal of the Academy of Marketing Science, Vol.36, No. 1, pp. 1-10; Ravald,A., Grönroos, C. (1996) "The value concept
and relationship marketing", European Journal of Marketing, Vol. 30 Iss: 2, pp.19 - 30 ©Dr Glenn Parry 2016
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Use value is difficult to capture and
it is perceptual, which is annoying
•  Capturing how ‘good’
something is in use is difficult
•  Value is perceptually
determined
–  by the user in their context
•  Perceptions change with
context and new information
•  We need a constant stream of
new use information
Businesses need to understand changing pa@erns of use In their day these were all considered to
be ‘good’
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Lets consider value; which is most
valuable?
Gold
Polystyrene
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By framing value as a measure of how good
something is it must be situated in use and context
The value of an offer to a consumer is only known when they integrate it into their lives of 47
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Where do suppliers get customer
data?
•  Traditional supplier-centric approaches focus on the ‘providerconsumer interface’
–  This is usually the point of exchange
–  Data is PoS, or may be satisfaction surveys, market studies etc.
•  After sale suppliers may have no contact with the consumer
–  unless a repeat purchase is made
–  or there is a problem and the consumer returns the offering
•  Providers have limited opportunity to collect use data
–  there is no data readily available for value creation processes
and use contexts
–  i.e. the private consumer value creation processes
Most firms do not ‘see’ value crea4on processes Source: Ng, I. C. L. (2014), Creating new markets in the digital
economy: Value & Worth, Cambridge University Press: Cambridge
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PoS data is available and measured
Capture Worth
£ sustainable
Point of sale data es gn
nc desi
e
u n Infl si-o
o
op
pr
Production of
Value
Survey data a value proposition
Realised
in use and context
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We can get consumer use data direct
from IoT devices and sensors
Capture Worth
£ sustainable
Value
Production of
IoT Use Data Realised
in use and context
a value proposition
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This is already done in complex
engineering service
•  Helicopters and aircraft are now
often sold as a service
–  E.g 1000 flying hours
•  The provider needs to monitor
condition and use
–  Health Usage Monitoring
Systems [HUMS]
–  Intelligence Vehicle Health
Management [IVHM]
•  This changes the nature of the
business model
–  often shifts responsibility and risk
–  Reliant on technology so requires
complex expensive infrastructure
IoT extends this concept into the home at low cost Source: Neely, A. (2010) “The Servitization of Manufacturing: Innovation in
Business Models”, Service Grand Challenge Summit Meeting, Cambridge Sept
22nd. ; Image from Withus, http://www.withus.re.kr/withus/e/product/
product_hums.htm
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Data can inform supplier and the
‘closed loop’ supply chain
Raw materials Manufacturing Distribu-on Returns
stream
Returns
Sales
Consumer up
Landfill lin
g
po
Returns Returns Returns Returns evalua-on evalua-on evalua-on evalua-on Centres Centres Centres Centres Wholesale / retail co
Remanufactured Product (Secondary markets) New Returns
int
Spares
recovery
The Loop is not really closed! De
Spare Components of 47
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Source: adapted from Blackburn et al., 2004
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What is supply chain visibility? there are three main perspectives
Visibility is Focus place on Sources •
Access and use of
information across a
supply chain
•
information exchange or
sharing
•
Lamming et al., 2001; Bradley,
2002; Swaminathan and Tayur,
2003; Schoenthaler, 2003;
Simatupang and Sridharan 2005;
Vitasak, 2013
•
The properties of
exchanged information
•
determined by the extent
to which the shared
information is accurate,
trusted, timely, useful and
in a readily usable format
•
Bailey and Pearson, 1983; Mohr &
Spekman, 1994; Gustin et al.,
1995; Mohr and Sohi, 1995; Closs
et al., 1997; McFarlane and Sheffi,
2003; Chan, 2003; Barratt and
Oke, 2007; Caridi et al., 2010,
2013; Francis, 2008; Dittmann,
2006; Goh et al. 2009;Zhang et al,
2011; Klueber and O’Keefe 2013
•
A capability that brings
attention to exceptions in
supply-chain execution
(sense), and facilitates
action (respond)
•
capability to use
information to initiate and
inform action
•
Eisenhardt & Martin, 2000; McCrea
2005; Kaipia and Hartiala, 2006;
Barratt and Oke 2007; Caridi et al.,
2010; Wei et al 2010; Holmström et
al. 2010; Klueber and O’Keefe
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Visibility has been developed within
performance management
•  Supply Chain information availability is usually not seen as a
problem1 by managers
–  But communication and sharing seems to be ineffective
•  Measures are often monetary resource equivalents2
–  Using financial measures can give misleading signals
•  Measurements are typically one of three types3
–  Static measures are lagging indicators, impossible to take any
corrective actions
–  Dynamic metrics are leading indicators, which predict
outcomes and can trigger corrective actions
–  Motivational metrics translate objectives
into motivating measures
Despite the defini4on sta4ng use, li@le is said about measuring how someone uses an offer Source: 1. Bilalis et al. 2002. 2. Melnyk et al. 2004, Kaplan and Norton, 1992; 3. Dimancescu, D. and Dwenger, K., World-Class New Product
©Dr Glenn Parry 2016
Development: Benchmarking Best Practices of Agile Manufacturers, 1996 (American Management Association: New York)
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Firms usually behave like someone
stood on a motorway bridge
•  We can observe the
process of A to B
•  We can measure speed
and volume
•  We know direction of
travel
•  We know where the road
goes
•  We may see individuals
repeat journeys
We don’t know the ‘why?’ The context and goal of 47
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Use value, visibility and IoT
•  Value is only being realised during the experience of
an offering (use) within a specific time, place and
setting (context)1
–  suppliers need information about how and when their
offerings are employed in various use processes
•  Value creation has been considered through a
relationship lens
–  customer to provider links are described as service
encounters2 or episodes3
•  Encounters and episodes are opportunities to collect
information on value creation in consumer processes
Using IoT supply chains can we propose we can get dynamic visibility data of consumer use processes Source: 1. Vargo et al., 2008; Payne, A. F., K. Storbacka and P. Frow (2008), "Managing the co-creation of value", Journal of the Academy of Marketing Science, Vol.36, No. 1,
pp. 83-96; 2. Payne, A. F., K. Storbacka and P. Frow (2008), "Managing the co-creation of value", Journal of the Academy of Marketing Science, Vol.36, No. 1, pp. 83-96; 3.
Ravald,A., Grönroos, C. (1996) "The value concept and relationship marketing", European Journal of Marketing, Vol. 30 Iss: 2, pp.19 - 30
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Outline
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•
•
•
•
Background
Theoretical frameworks
Method
Results
Discussion
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Explorative case study of 6 HAT
users
•  Quantitative data from sensors and systems in the
homes
–  Instrumentation of rooms to create data density
•  Qualitative data from interviews, user process
descriptions and home visits
•  Focus upon showering activity (difficult space)
–
–
–
–
Private function in the home
Video not acceptable
“Wet” environment
Mains power use limited
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Hub of All Things is the platform
repository used to collect data
•  HAT collects IoT data
–  And makes it accessible only to
you in one place
•  The platform is built
–  We had 6 people collecting a lot
of personal data
–  We are working now to scale up
•  HAT data is owned by the
individual
–  Individuals share data only with
those they select
–  DP0’s data given to study
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Process mapping using IDEF0
IDEF0
Constraints / Controls
(e.g. legislation, set limit)
Input
(e.g. requirements
and materials)
Func-on Output
(e.g. Product, Document)
Mechanisms/Resources
(e.g. Plant, People, Algorithm)
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Generic “Shower”
Towel
Megan
Hot Shower
water gel
Showering Clean Megan
Used towel
Waste water
Shower Light Extractor
fan
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Outline
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•
•
Background
Theoretical frameworks
Method
Results
Discussion
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Identification of many resources
in the shower room
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Generic “Shower” process and
resources used
Towel
Megan
Hot Shower
water gel
Showering Clean Megan
Used towel
Waste water
Shower Light Extractor
fan
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Analysis of the resources led to a
categorization of data types
•  Interaction Data
–  Data from a resource/mechanism which is not transformed, diminished
or depleted during single use E.g. taps, showers, doors, rooms
•  Experience data
–  Information from resource that is transformed, diminished, but not
depleted E.g. towel, flannel,
•  Depletion data
–  Data on a resource which is consumed at a rate higher than it is
replenished E.g. shower gel, shampoo
•  Consumption data
–  Data on resource which is replenished at the rate it is consumed E.g.
water, electricity
These are nested func4ons and categorisa4on is set by the chronology of a selected event of 47
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Example of interaction data
capture: the shower room
Z-wave humidity sensor
Also gives count data of Interac4on with shower of 47
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Example of consumption data
capture: shower water use
Time / mins 35 Z-wave flood sensor
Average 21 mins
250 Volume / Litres 30 200 25 150 20 Time 15 100 Volume 10 50 5 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Showering event occurrence
Also gives count data of Interac4on with shower Shower dura4on and volume of water was much longer than individual thought! of 47
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Note: av. duration 19 mins; av. water vol. 149 litres (a bath is 80 litres)©Dr
Glenn Parry 2016
Example of experience data
capture: Towel
Z-wave motion sensor
Time
00:05:46 Use Time 00:04:19 00:02:53 00:01:26 00:00:00 Occurrence
It appeared that the towel was used more oRen than the ‘owner’ expected Others were using their towel to dry their hands! of 47
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Example of depletion data
capture: shampoo
AMBB; Developed by Cambridge
y = -­‐2.3173x + 176.4 R² = 0.90627 Weight /g 300 y = -­‐2.2503x + 400.53 R² = 0.90626 250 (B) 200 150 (A) 100 50 0 0 20 40 60 80 100 120 140 Days Shampoo consump4on rate was rela4vely linear of 47
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Example depletion data capture:
Shower gel
Weight
AMBB; Developed by Cambridge
Shower gel consump4on rate was erra4c of 47
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Linking data we can start to see the
effects of context on shower gel use
Running increases both shower 4me, and shower gel consump4on by 100% of 47
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Outline
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•
•
•
•
Background
Theoretical frameworks
Method
Results
Discussion and Conclusions
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Findings
•  Explorative case shows IoT implementation and
operationalisation in the home
–  Tracks consumption, use and resource combination
•  Numerous implications for supply
–  Consumers perceptions of use differs to actual
•  Time in shower is longer
•  Use of towel is more ‘shared’ than thought
=> Survey data would be misleading
–  Some activities are moderators for others
•  Running leads to longer shower length and double the
consumption of shower gel
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A useful categorization of data types to
use when examining process
•  Interaction Data
–  Data from a resource/mechanism which is not transformed,
diminished or depleted during single use E.g. taps, showers, doors,
rooms
•  Experience data
–  Information from resource that is transformed, diminished, but not
depleted E.g. towel, flannel,
•  Depletion data
–  Data on a resource which is consumed at a rate higher than it is
replenished E.g. shower gel, shampoo
•  Consumption data
–  Data on resource which is replenished at the rate it is consumed
E.g. water, electricity
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Benefits of IoT for supply chain
•  Design touchpoints for product acquisition
–  The right product, in sufficient quantities at the right price
•  Improve timings and planning of reverse supply
–  Data improves predictability of returns and service
requests
•  Utilize customer data for effectiveness
–  Train customer to use the product ‘correctly’
–  Extends the concept of “customer as employee” where
they may be selected, trained or dismissed1
•  Improve process for efficiency by understanding
patterns of use
–  Data may allow for automated or customer led product
inspection
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Source: Johnston, 1989
HAT enables, with consumer consent, a
truly ‘closed loop’ supply chain
Remanufactured Product (Secondary markets) po
g
co
New Returns
Sales
De
Spare Components Wholesale / retail lin
Distribu-on up
Manufacturing int
Data on consumer use in context Raw materials Returns
stream
Returns
Automated Removes
the decoupling point
evalua-on HAT data Consumer Landfill of 47
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Going forwards, we need firms to innovate
apps to link personal data in our lives
We can chose apps to remind us of things we need and where to buy it when we are in our cars Firms can compete to get you to go and buy from them We can also trade use data so firms can fill the knowledge gap of 47
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Going forwards, academic work
will examine blurring boundaries
•  Physical
–  Changing sense of place
–  Where is home, work,
neighbours?
•  Virtual
Virtual
–  Traditional boundaries blocked
information flow, but no more
–  Decisions will be made on data,
not manager expertise
•  Epistemological
–  Blurring employee, vendor and
customer
–  Can we measure and
understand everything?
ys
h
P
l
ica
Ep
ist
e
mo
log
ica
l
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Questions
www.hubofallthings.com
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Visibility challenges
•  Fit of visibility information to informational structure
–  How can data be captured and formatted?
–  What data from the combination of sub-processes
would be useful?
–  How can data be integrated into the supply chain?
•  Fit to operational purpose
–  Different data requirements of different suppliers
•  Fit for delivery of offer
–  Greater visibility leads to modification or
postponement impacting the production of the offering
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Closing the loop allows
servitization of the home
•  New availability business models can be offered to
the home
–  We are happy to buy water, power and telephony as a
service – but what about soap, toothpaste etc?
–  Failure rate can be more accurately predicted if use
context is known
•  With known history we can offer better warranties
•  If an object has a known history it is easier to find
ways to reuse/resell it
•  We can deliver more appropriate recycling and
waste management services
–  volumes are known before the service is enacted
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Contributions to theory
•  Visibility is an enabler of servitization
•  A focus on value in exchange can be
changed to a focus on value in use
–  Enabled through the combination of IoT
enabled UVMs that provide visibility of use in
context
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Dimensions of value creation
Source of value crea4on Academic lens User of value Crea4on Process Value capture process Society • Sociologists • Economists Ecologists • Individuals • Organiza-ons • Governments • Innova-on and new firm crea-on • Compe--on • Capital investment • Incen-ves • Laws and regula-ons • Factor Condi-ons • Demand Condi-ons • Suppor-ng industry infrastructure • Firm strategy and rivalry Organisa-on • Strategic Management • Organiza-onal Theory • Strategic HRM • Consumer • Society • Inven-on • Rare, inimitable, • Innova-on non-­‐subs-tutable • R&D resource • Knowledge crea-on • Intangible resource • Structure and social condi-ons • Incen-ves, selec-on and training Individual • Psychology • Organisa-onal Behaviour • HRM • Consumers • Client • Organisa-on • Knowledge crea-on • Search • Ability • Mo-va-on • Training • Network posi-on • Unique experience • Tacit knowledge of 47
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Lepak, D., Smith, K.G., Taylor, M.S. (2007) “Value creation and value capture: a multilevel
perspective”,
Management Review, 32(1)180-194
Ideas draw upon the paper
Parry, G., Brax, S.A., Maull, R., Ng., I. (2016)
“Visibility of consumer context: improving reverse
supply with internet of things data”, Supply Chain
Management: An International Journal
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The basic business model framework
shows value creation and capture
Capture Worth
£ sustainable
Value
Realised
Production of
in use and context
a value proposition
Source: Teece, 2010; Parry and Tasker, 2014
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Your data is in ‘verticals’ and
taken by firms you use
•  This misses the
horizontals
–  the links
between the
data
•  Context of use
is in the
horizontals
–  What you do,
when and with
who
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