Multi-sided platform for the internet of things. /Connected devices

1. HEC Professional
dissertation
Multi-sided platform for the
Internet of Things
1WATRIGANT Thibaut

2. What is the Internet of Things?
• The overall network behind connected devices that enables them to
communicate with their environment
2
@

3. Why do we talk about a platform: the interoperability issue
Nowadays, connected devices cannot talk to each other, as a result services are
device-centric instead of being user-centric.
3
Retail HealthQuantified SelfSmart Home
Multi-sided platform for the
Internet of Things

4. Which future for an internet of things multi-sided platform?
4
• WHAT: How will the platform be structured? How will network
externalities drive the platform structure?
• WHY: To what extent is there a market need for interoperability
based on data exchange on the market?
• HOW: Will the platform be profitable? How can the platform be
implemented to maximize success rate?
• WHO: Which resources and capabilities best help companies to
launch their platform?
?

5. Which future for a multi-sided platform for the Internet of Things?
5
WHAT: The IoT platform will be structured in 6 sides, linked by
strong network externalities
WHY: There is a need for interoperability based on data exchange
on the market
HOW: Considering advertisers as the profit-making side and
service providers as well as connected device manufacturers as
the subsidized side is optimal to grow thanks to network effects
while being profitable
WHO: Key success factors to build its platform are reputation and
financial resources

6. What would be such a platform?
IoT
platform
Platform characteristics:
• Multi-sided
• Cloud and data-based
Platform Offerings
• Data storage
• API library
• Data analytics
• IP indexation

7. The platform will be structured in 6 sides, linked by strong network
externalities: qualitative approach
7
End-users:
want a high-quality
service associated with
connected devices
Device manufacturers:
want to sell their offers
with a higher profit.
Network providers:
Want to improve their
revenues by finding new
customers or more data to
transfer.
Advertisers:
Want to charge higher
prices for ads using
targeting data
Service providers:
want to sell their services
with a higher profit.
Software providers:
want to maximize their
profit by selling their
offer
IoT
platform

8. The platform will be structured in 6 sides, linked by strong network
externalities: quantitative perceived added profit method
8
Resulting
externality matrix:

9. The platform will be structured in 6 sides, linked by strong network
externalities: taking competition into account
9

10. There is a need for interoperability based on data exchange on the
market
10
The platform will make increase customer willingness to pay for connected
devices, making grow the internet of things penetration
Impacted by the platform

11. There is a need for interoperability based on data exchange on the
market
11
Services (+6,2%):
Quality of service
improved & new
services by data
mixing.
Price reduction
(+1,6 to 5,6%):
End price reduction
due to new sources
of revenue created
Security of information
(+0,3 to 3%):
Method aggregated
implying better security
solutions
Ad absence(-7,7%):
Introduction in ads
related with
connected devices
services

12. Considering advertisers as the profit-making side and service providers as well as
connected device manufacturers as the subsidized side is optimal to grow thanks to
network effects while being profitable
12
ResultStrategy
1- Focus on growth by
relying on service
providers and device
manufacturers
2- Focus on profitability
by attracting advertisers

13. Key success factors to build its platform are reputation and financial
resources
13Note : some other platforms may also be included on this market map that has been built in January 2015

14. Key success factors to build its platform are reputation and financial
resources
14
Key resources &
capabilities
Firstmoveradvantage
Publicknowledgeof
thebrand
Financialresources
Platformoffering
versusexpectations
Professionalbeliefin
platformsuccess
Internationalpresence
Commercialsaleforce
Sizeofpartners
ecosystem
Platformdevelopment
planinaccordance
withnetworkeffects
Influence rate 5% 12% 9% 18% 18% 3% 5% 15% 15%

15. To summarize: what’s the future for our Internet of Things platform?
15
…will understand that
there is a market need
for interoperability
based on data
exchange between
connected devices
…and will reach
profitability by
attracting
advertisers
… will launch a 6-
sides platform
and will focus on
service providers
and device
manufacturers to
make it grow…
One actor with a
lot of reputation
and financial
resources…

16. Thanks
Questions
16

17. Appendices
0.1 General state of the art: the gap between platform researches and internet of things market news
0.2 General state of the art: literature review
1.1 Qualitative interview guide
1.2 Qualitative interviews: people interviewed
2.1 Quantitative survey: from data need to tangible results
2.2 Quantitative survey: data need understanding
2.3 Quantitative survey: survey marketing
3.1 Perceived added profit methodology: presentation
3.2 Perceived added profit methodology: results
4.1 Mathematical and iterative model: inputs
4.2 Mathematical and iterative model: method
4.3 Mathematical and iterative model: assumptions tested
4.4 Mathematical and iterative model: results
5.1 Actors resources and capabilities evaluation
5.2 Key success factors to build its platform are reputation and financial resources
5.3 Actors resources and capabilities evaluation
6. Bibliography
17

18. General state of the art: the gap between platform researches and
internet of things market news
This research bring empirical evidence to theoretical studies related with multi-
sided platform and give theoretical insights to the new internet of things
market
18
Platform
markets
Internet of
Things
Theoretical Empirical

19. General state of the art: literature review
19
Platform
markets
Internet of
Things
Theoretical Empirical
(Ropert, Bonneau, & Ramahandry, 2013)
(Institut Carnot, 2011)
(Haowei, Tianhai, Yuan, & Rencai, 2013)
(Vermesan & Friess, 2010)
(Gartner, 2014)
(Cisco Internet Business Solutions Group, 2011)
(Ericsson, 2010)
(Morgan Stanley, 2013)
(IDC, 2014)
(Miorandi, Sicari, De Pellegrini, & Chlamtac, 2012)
(Canalys, 2014)
(Evans, 2011)
(Sriram, et al., 2014)
(Rochet & Tirole, 2002)
(Hagiu & Wright, Multi-Sided Platforms, 2011)
(Balamuralidhar, Prateep, & Arpan, 2013)
(Sylvain, 2014)
(Parker & Van Alstyne, 2002)
(Cusumano & Gawer, 2002)
(Caillaud & Julien, 2001)
(Zhu & Iansiti, 2007)
(Liebowitz & Margolis, 1995)
(Rangan & Adner, 2001)

20. 1.1 Qualitative interview guide
20
Introduction and introduction of the interview: “Dear Mister / Madam, Thanks for having accepted giving your
opinion and knowledge. All the information you give me may contribute to the work I am currently undertaking and
may be included inside, under your name or anonymously depending on your preference. “
Q2.1-First question, simple to answer and very factual to make the interlocutor confident and talk more easily: “What
is your definition and understanding on the Internet of Things? Can you explain to me your day to day work and its
link with this market?”
Then, react on one sentence and begin asking questions to extract the following data needed:
General questions my interlocutor platform perception. Two goals: being sure we talk about the same thing
and get information or new ideas using actors’ perceptions on the platform (Q2.2). Among these questions,
clarifying and exploring the platform offerings to different actors. Then determining whether they think the
platform is more quality driven, installed base driven or expectation driven not by directly asking it to my
interlocutor but by asking him to order 3 platform offerings, each one accentuating one of the three previously
cited characteristics (Q2.3). Then I will ask which resources and core capabilities best help building such
platform in his opinion before asking him evaluate which actor has best success rate in implementing its
platform (Q2.4).
Questions about his data sharing experiences and issues: I am going to ask them about the awareness
concerning data they might be giving already away to try to get an understanding about their experience, and
know how related to this issue.
How sensitive my interlocutor is to other actors on the platform? To proceed, I will introduce a type of actor,
explain what could be its potential role in the platform, ask my interlocutors to comment on this role before
asking him to rate between 0 and 5 the importance he would give to this type of actor (Q2.5).
How sensitive he is to platform prices? I will introduce the subject by asking my interlocutor what benefits he
hope gaining from such a platform. Then I will introduce the cost-side of acceding to such benefits by asking
which payment structure would best suit my interlocutor before inquiring about how much would he be
willing to pay and how sensitive is its price elasticity (Q2.6).
Initial interview guide:
Guide
redesigned
and
adapted
after each
interview

21. 1.2- Qualitative interviews: people interviewed
21
Confidential

22. 2.1 Quantitative survey: from data need to tangible results
22
Data need
Understanding
• From hypotheses to
data need
• From data need to
data gathering
methodology
Survey design
• From data need to
survey design
• Questions review
• Questions design
on Google survey
Survey
marketing
• Article on Aruco
website
• Facebook
advertising
• Social media
advertising
• Slideshare
presenting the
project
Data analysis
• Data
standardization on
Excel
• Respondents pool
constitution
• Data analysis per
pool
• Data graphic
representation
Data result
interpretation
• Graphical and
analytical analysis
of data
• Mix between data
from quantitative
survey and data
from qualitative
interviews

23. 2.2 Quantitative survey: data need understanding
23
Data need
Understanding
• From hypotheses
to data need
• From data need to
data gathering
methodology

24. 2.2 Quantitative survey: data need understanding
24
Survey design
• From data need to
survey design
• Questions review
• Questions design
on Google survey
Survey design on Google SurveyFrom data need Questions review
Page title: Connected devices: tell us what you
think of their future!
Introduction: This poll has been created by
Thibaut Watrigant, writer at Aruco.com, while
writing a professional dissertation on the Internet
of Things market evolution, focusing on IoT data
exchange platform to improve quality of IoT-
related service. This poll contains 9 questions and
will take 5 minutes to handle. Thanks for your
answers, all of them being anonymous.
Q1.1: Have you already bought a connected
device?
Yes
No
Q1.2: While buying, which relative importance
you give to the following criteria (Scale: 0 to 5,
from “not important” to “the most important
thing”)
The object and its functionalities
Its design
Its price
Services offered with the device
Security of my personal data
Advertising absence
Page break
…

25. 2.2 Quantitative survey: data need understanding
25
Data analysis
• Data
standardization on
Excel
• Respondents pool
constitution
• Data analysis per
pool
• Data graphic
representation
Data exported from Google survey to Excel
resulting in anExcel Tab 16x113 to be standardized
Pool constitution:
three pools
Use of Excel « SUMIF » function to analyse every
result per respondent pool
Data graphic
representation per
question per pool.
Ex: what if we
pay you to obtain
your data

26. 2.2 Quantitative survey: data need understanding
26
Data result
interpretation
• Graphical and
analytical analysis
of data
• Mix between data
from quantitative
survey and data
from qualitative
interviews

27. 2.3 Quantitative survey: survey marketing
27
Survey
marketing
• Article on Aruco
website
• Facebook
advertising
• Social media
advertising
• Slideshare
presenting the
project

28. 3.1 Perceived added profit methodology: presentation
28
We have based network
externalities from actor A to actor
B quantification on how much
perceived added profit the
presence of actor B makes on
actor A’s income statement. As
the effect of an added profit of a
certain number of dollars is
market dependent (for instance a
network provider and an advertiser
do not have the same profit scale
and margins), all quantification
will have to be affected by a factor
characterizing profitability level in
the different industries in order to
be comparable.
Actor A
Perceived added profit of
joining the platform:
ΔPercProf = f(Actor A, Actor B, Actor C)
Other Actor A Actor B
Network externalities between actors A
and from actor B to actor A

29. 3.2 Perceived added profit methodology: results
29
e: number of end-users.
d: number of devices
compatible with the
platform, which is highly
correlated with the
number of connected
device manufacturers
having joined the
platform.
Ad: number of advertisers
paying to obtain data in
order to contextualize
their advertisings.
s: number of service
providers linked with the
platform.
So: number of software
providers linked with the
platform.
n: number of network
providers linked with the
platform.
𝐸 =
𝜆 + 𝜂 𝜆 + 1
𝜎 + 1 −𝜎
−1 𝜆 + 1
−𝛿 −1
−𝜆 −1
−1 −1
−𝜅 𝜒 − 𝜅
𝛼 + 𝜔 𝛼 + 𝜔
−𝜃 −0
−𝜀 𝛼 − 1
−0 −0
−𝛼 −0
𝜑 + 𝛽 𝜑 + 𝛽
− 0 −𝜏
0 −𝛽
0 −0
𝛽 − 1 0
−0 −1

30. 4.1 Mathematical and iterative model: inputs
30
Kp
2+Kn
2=1, Kp=0.50, Kn=0.75.
Cn
2+Ca
2=1, Cn=0.84, Ca=0.40.
n1tot=50 million, n2tot=4,000, n3tot=1,000, n4tot=10,000, n5tot=1,000, , n6tot=20.
P1=10, P2=7, P3=5, P4=3, P5=3, P6=3.
n1,1=1,000, n1,2=5, n1,3=10, n1,4=5, n1,5=5, n1,6=1.
𝑛𝑖+1,𝑗 = 𝑛𝑖,𝑗 + 𝑛𝑖,𝑗 𝐶 𝑛
𝑘
𝐸𝑖𝑘
𝑛𝑖𝑘
𝑛 𝑘𝑡𝑜𝑡
+ 𝑛𝑖,𝑗 𝐶 𝑎 𝐴𝑖𝑗 𝐾 𝑛
𝑘
𝐸𝑖𝑘
𝑛𝑖𝑘
𝑛 𝑘𝑡𝑜𝑡
+ 𝑃𝑖
𝐸 =
−1.5 −1.7
−1.5 −0.5
−1.0 −1.7
−0.3 −1.0
−0.7 −1.0
−1.0 −1.0
−0.7 −0.1
−3.8 −3.8
−0.6 −0.0
−0.5 −0.9
−0.0 −0.0
−1.9 −0.0
−1.2 −1.2
−0.0 −0.2
−0.0 −1.1
−0.0 −0.0
−0.1 −0.0
−0.0 −1.0

31. 4.2 Mathematical and iterative model: method
31
Input data: key
variables and initial
conditions
𝑛𝑖+1,𝑗
= 𝑛𝑖,𝑗 + 𝑛𝑖,𝑗 𝐶 𝑛
𝑘
𝐸𝑖𝑘
𝑛𝑖𝑘
𝑛 𝑘𝑡𝑜𝑡
+ 𝑛𝑖,𝑗 𝐶 𝑎 𝐴𝑖𝑗(𝐾 𝑛
𝑘
𝐸𝑖𝑘
𝑛𝑖𝑘
𝑛 𝑘𝑡𝑜𝑡
+ 𝑃𝑖)
Hypotheses tested
on business model
and on
implementation
Iterative model Results on platform
growth and profitability
Test with different hypotheses to maximize
results on growth and profitability

32. 4.3 Mathematical and iterative model: assumptions tested
32
Price expectation strategy -Δpi
125% 110% 50% 111% 102% 102%
Investment matrix Aij
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,2 1,2 0 4,3 1,9 1,4
1,5 1 2 4 0,8 0,6
1,5 1 2 4 0,8 0,6
1,5 1 2 4 0,8 0,6
1,5 1 2 4 0,8 0,6
1,5 1 2 4 0,8 0,6
1,5 1 2 4 0,8 0,6
𝑘=1
6
∆𝑃𝑖
6
≤ 1

33. 4.4 Mathematical and iterative model: results
33
nij End-users
Device
manufacturers
Advertisers &
data users
Service
provider
Software
provider
Network
provider
n1 1000 5 10 5 5 1
n2 1420 6 10 7 6 1
n3 2018 8 10 10 7 1
n4 2869 10 10 14 8 1
n5 4079 13 10 19 9 1
n6 5803 16 10 27 11 2
n7 8263 20 10 38 12 2
n8 11775 26 10 54 14 2
n9 16802 33 10 76 17 2
n10 24014 42 10 107 20 2
n11 34397 53 10 152 23 3
n12 49417 68 10 215 27 3
n13 71286 87 10 306 32 3
n14 103405 113 10 436 37 3
n15 162341 142 11 613 41 3
n16 257288 180 13 866 44 4
n17 413186 231 15 1233 49 4
n18 676059 304 17 1776 54 4

34. 4.4 Mathematical and iterative model: results
34

35. 5.1 Actors resources and capabilities evaluation
35
1- Market study of actors having launched their platform end-2014

36. 5.2 Key success factors to build its platform are reputation and
financial resources
• Determination of best resources and capabilities to launch its internet of
things platform
36
• Building a good product: having financial means to invest in R&D and to be
able to manage and secure data (9%), offering services which match different
sides’ expectations (18%) and rely on network effects (15%), and building an
ecosystem with a lot of actors to raise the number of platform offerings (15%).
• Being already known and having a good brand reputation: being known by the
public (12%), having professionals believing on platform success (18%), having
a big commercial salesforce (5%) and an international presence (3%).
• Being the first to launch its platform: 5%,

37. 5.3 Actors resources and capabilities evaluation
37
2- Determination of key success factors for platform launching
Key resources &
capabilities
Firstmover
advantage
Publicknowledgeof
thebrand
Financialresources
Platformoffering
versusexpectations
Professionalbelief
inplatformsuccess
International
presence
Commercial
saleforce
Sizeofpartners
ecosystem
Platform
developmentplanin
accordancewith
networkeffects
Influence rate 5% 12% 9% 18% 18% 3% 5% 15% 15%

38. 5.3 Actors resources and capabilities evaluation
38
3- Application of these criteria to platform launchers
Confidential

39. 6. Bibliography
39
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Balamuralidhar, P., Prateep, M., & Arpan, P. (2013). Software Platforms for Internet of Things and M2M. Journal of the Indian Institute of Science VOL 93:3, 487-498.
Caillaud, B., & Julien, B. (2001). Chicken and Egg: Competing Matchmakers. London: CEPR Discussion Paper.
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