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HEC Professional dissertation

Multi-sided platform for the Internet of Things

WATRIGANT Thibaut

What is the Internet of Things?

• The overall network behind connected devices that enables them to communicate with their environment

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@

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.

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Retail HealthQuantified SelfSmart Home

Multi-sided platform for the Internet of Things

Which future for an internet of things multi-sided platform?

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• 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?

?

Which future for a multi-sided platform for the Internet of Things?

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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

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

The platform will be structured in 6 sides, linked by strong network externalities: qualitative approach

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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 offerIoT

platform

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

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Resulting externality matrix:

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

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There is a need for interoperability based on data exchange on the market

The platform will make increase customer willingness to pay for connected devices, making grow the internet of things penetration

Impacted by the platform

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There is a need for interoperability based on data exchange on the market

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

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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

ResultStrategy

1- Focus on growth by relying on service providers and device manufacturers

2- Focus on profitability by attracting advertisers

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Key success factors to build its platform are reputation and financial resources

Note : some other platforms may also be included on this market map that has been built in January 2015

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Key success factors to build its platform are reputation and financial resources

Key resources & capabilities

First mover advant

age

Public knowledge of the brand

Financial

resources

Platform

offering versus

expectations

Professional belief

in platfor

m success

International

presence

Commercial

saleforce

Size of partne

rs ecosyst

em

Platform developmen

t plan in accordance

with network effects

Influence rate 5% 12% 9% 18% 18% 3% 5% 15% 15%

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To summarize: what’s the future for our Internet of Things platform?

…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…

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Thanks

Questions

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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

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

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Platform markets

Internet of Things

Theoretical Empirical

Network

externalitiesChicken & egg issue

Best

Ressources &

capabilities

Market

definition

Platform profitability

Platform ch. driven

Surveys on

people

perception

Market day to day news

Surveys on people

perception

Some cases: videogames, payment, ecommerce…

Research gap

General state of the art: literature review

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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)

1.1 Qualitative interview guide

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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

1.2- Qualitative interviews: people interviewed

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Confidential

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2.1 Quantitative survey: from data need to tangible results

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

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2.2 Quantitative survey: data need understanding

Data need Understanding• From hypotheses to

data need• From data need to

data gathering methodology

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2.2 Quantitative survey: data need understanding

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?YesNo

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 functionalitiesIts designIts priceServices offered with the deviceSecurity of my personal dataAdvertising absence

Page break…

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2.2 Quantitative survey: data need understanding

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

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2.2 Quantitative survey: data need understanding

Data result interpretation• Graphical and

analytical analysis of data

• Mix between data from quantitative survey and data from qualitative interviews

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2.3 Quantitative survey: survey marketing

Survey marketing• Article on Aruco

website• Facebook

advertising• Social media

advertising• Slideshare

presenting the project

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3.1 Perceived added profit methodology: presentation

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

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3.2 Perceived added profit methodology: results

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+1𝜎+1 −𝜎

− 1 𝜆+1−𝛿 −1

− 𝜆 −1− 1 −1

−𝜅 𝜒 −𝜅𝛼+𝜔 𝛼+𝜔

−𝜃 − 0−𝜀 𝛼− 1

−0 − 0−𝛼 − 0

𝜑+𝛽 𝜑+𝛽− 0 −𝜏

0 − 𝛽0 − 0

𝛽− 1 0− 0 − 1

)

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4.1 Mathematical and iterative model: inputs

Kp2+Kn

2=1, Kp=0.50, Kn=0.75.Cn

2+Ca2=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.

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4.2 Mathematical and iterative model: method

Input data: key variables and initial

conditions

𝑛𝑖+1 , 𝑗=𝑛𝑖 , 𝑗+𝑛𝑖 , 𝑗𝐶𝑛∑𝑘

𝐸𝑖𝑘

𝑛𝑖𝑘

𝑛𝑘𝑡𝑜𝑡

+𝑛𝑖 , 𝑗𝐶𝑎 𝐴𝑖𝑗 (𝐾 𝑛∑𝑘

𝐸𝑖𝑘

𝑛𝑖𝑘

𝑛𝑘𝑡𝑜𝑡

+𝑃 𝑖)

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

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4.3 Mathematical and iterative model: assumptions tested

Price expectation strategy -Δpi125% 110% 50% 111% 102% 102%

                                 

Investment matrix Aij1,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,2 1,2 0 4,3 1,9 1,41,5 1 2 4 0,8 0,61,5 1 2 4 0,8 0,61,5 1 2 4 0,8 0,61,5 1 2 4 0,8 0,61,5 1 2 4 0,8 0,61,5 1 2 4 0,8 0,6

∑𝑘=1

6∆ 𝑃𝑖

6≤ 1

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4.4 Mathematical and iterative model: results

nij End-users Device manufacturers

Advertisers & data users

Service provider

Software provider

Network provider

n1 1000 5 10 5 5 1n2 1420 6 10 7 6 1n3 2018 8 10 10 7 1n4 2869 10 10 14 8 1n5 4079 13 10 19 9 1n6 5803 16 10 27 11 2n7 8263 20 10 38 12 2n8 11775 26 10 54 14 2n9 16802 33 10 76 17 2

n10 24014 42 10 107 20 2n11 34397 53 10 152 23 3n12 49417 68 10 215 27 3n13 71286 87 10 306 32 3n14 103405 113 10 436 37 3n15 162341 142 11 613 41 3n16 257288 180 13 866 44 4n17 413186 231 15 1233 49 4n18 676059 304 17 1776 54 4

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4.4 Mathematical and iterative model: results

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5.1 Actors resources and capabilities evaluation

1- Market study of actors having launched their platform end-2014

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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

• 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%,

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5.3 Actors resources and capabilities evaluation

2- Determination of key success factors for platform launching

Key resources & capabilities

First mover advant

age

Public knowledge of the

brand

Financial

resources

Platform

offering

versus expecta

tions

Professional belief

in platfor

m succes

s

International

presence

Commercial

saleforce

Size of partner

s ecosys

tem

Platform developmen

t plan in accordance

with network effects

Influence rate 5% 12% 9% 18% 18% 3% 5% 15% 15%

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5.3 Actors resources and capabilities evaluation

3- Application of these criteria to platform launchers

Confidential

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6. Bibliography

Amdocs. (2011). Making the most of connected devices. Chesterfield, MO: Amdocs.Atzori, L., Iera, A., Morabito, G., & Nitti, M. (2012). The Social Internet of Things (SIoT) – When social networks meet the Internet of Things: Concept, architecture and network characterization. Cagliari: Elsevier.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.Canalys. (2014). Defining the Internet of Things. Pao Alto, CA: Channels Pulse (PCHA), Enterprise Pulse (PENT), Mobile Pulse (PMOB).Cisco. (2014). Future of Innovation: Building IoT platform. Internet of Things World conference (pp. 1-30). Chicago, Illinois: Cisco Research.Cisco Internet Business Solutions Group. (2011, 07 29). The Internet of Things - How the Next Evolution of the Internet is Changing Everything. San Francisco: Cisco Whitepaper.Colistra, G., Pilloni, V., & Atzori, L. (2014). The problem of task allocation in the Internet of Things and the consensus-based approach. Cagliarni: Elsevier.Cusumano, M. A., & Gawer, A. (2002). The Elements of Platform Leadership. Cambridge, MA: MIT Sloan Management Review .Ericsson. (2010, 04 13). thecompany/press/releases/2010/04/1403231. Retrieved 11 23, 2014, from ericsson.com: http://www.ericsson.com/thecompany/press/releases/2010/04/1403231Evans, D. S. (2011). Platforms Economics: Essays on Multi-Sided Businesses. New York: Competition Policy International (CPI).Filistrucchi, L., Geradin, D., & Van Damme, E. (2012). Identifying two-sided markets. Tilburg: TILEC.Gartner. (2014, 11 11). Press release. Retrieved 11 23, 2014, from gartner.com: http://www.gartner.com/newsroom/id/2905717Goldman Sachs. (2014). The Internet of Things: Making sense of the next mega-trend. New York: Global Investment Research.Gubbia, J., Buyyab, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Melbourne: Elsevier.Hagiu, A., & Wright, J. (2011). Multi-Sided Platforms. Cambridge, US: Harvard Working Paper.Hagiu, A., & Wright, J. (2013). Do you really want to be an ebay? Harvard Business Review, 103-108.Haowei, W., Tianhai, Z., Yuan, Q., & Rencai, D. (2013). Research on the framework of the Environmental. Xiamen: Institute of Urban Environment, Chinese.ICT, E. C. (2014, 07 23). Internet of Things and Platforms for Connected Smart Objects. Retrieved 11 22, 2014, from ec.europa: http://ec.europa.eu/research/participants/portal/desktop/en/opportunities/h2020/topics/9091-ict-30-2015.html#tab1IDC. (2014). Worldwide and Regional Internet of Things (IoT) 2014–2020 Forecast: A Virtuous Circle of Proven Value and Demand. Framingham, MA: IDC whitepaper.Institut Carnot. (2011). Livre blanc: objets communicants et internet des objets. Paris: Institut Carnot.Miorandi, D., Sicari, S., De Pellegrini, F., & Chlamtac, I. (2012). Internet of things: Vision, applications and research challenges. Varese: Elsevier.Morgan Stanley. (2013, 10 02). businessinsider.com. Retrieved 11 23, 2014, from 75-billion-devices-will-be-connected-to-the-internet-by-2020: http://www.businessinsider.com/75-billion-devices-will-be-connected-to-the-internet-by-2020-2013-10Parker, G., & Van Alstyne, M. (2002). Two-sided network effects: a theory of information product design. Management Science, 1494-1504.Perera, C., Zaslavsky, A., & Christen, P. (2013). Context Aware Computing for The Internet of Things: A Survey. Piscataway, New Jersey: IEEE COMMUNICATIONS.Pérez, J. L., Villalba, Á., Carrera, D., Larizgoitia, I., & Trifa, V. (2014). The COMPOSE API for the Internet of Things. World Wide Web commitee (p. 6). Séoul: WWW'14 companion.Rochet, J.-C., & Tirole, J. (2002). Platform Competition in Two-Sided Markets. Toulouse: Journal of the European Economic Association.Ropert, S., Bonneau, V., & Ramahandry, T. (2013). Internet of Things: Outlook for the top 8 vertical markets. Montpellier: Idate research.Sivabalan, A., Raja, M. A., & Balamuralidhar, P. (2013). Towards a LightWeight Internet of Things. Bangalore: Journal of ICT Standardization.Sriram, S., Manchanda, P., Esteban Bravo, M., Chu, J., Ma, L., Song, M., et al. (2014). Platforms: A Multiplicity of Research Opportunities. 9th Invitational Choice Symposium at Erasmus University (pp. 1-19). Rotterdam: Erasmus University.Sylvain, G. (2014, 11 24). Which actors may benefit from an IoT multi-sided platform? (T. Watrigant, Interviewer)Vermesan, O., & Friess, P. (2010). Internet of Things Strategic Research Roadmap. Europe: European Research Cluster.Vottero, F., & Boulègue, A. (2014). Le marché des objets connectés. Paris: Xerfi research.Witchalls, C. (2013). The Internet of Things business index: A quiet revolution gathers pace. London: The Economist Intelligence Unit.