1. 1 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur

2. 2 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
Table of Contents
Introduction ........................................................................................................................... 3
Definitions ............................................................................................................................. 4
IoT Market Drivers and Challenges in 2016 ............................................................................. 5
IoT Value Proposition Per Market Segments ........................................................................... 9
IoT Revenue Models .............................................................................................................. 12
Categories ...................................................................................................................................... 12
Examples ........................................................................................................................................ 15
The Value of Data .................................................................................................................. 22
Additional References ........................................................................................................... 25
About the Author .................................................................................................................. 27

3. 3 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
Introduction
In this report, we will review some of the key market drivers behind the Internet of Things (IoT),
the value proposition for each market segment, the common revenue models with some
examples, and finally the value of data as it relates to the IoT.
This report does not cover any introduction on the IoT or its market size because there are
plenty of excellent resources available online. Although additional resources used for this report
are listed at the end of this document, I particularly recommend the ones below to further
explore the subject.
● Roundup of Internet of Things Forecasts and Market Estimates, 2015
● IoT: Business Opportunities 2015–2025
● Enterprise IoT: A Definitive Handbook
● Collaborative Internet of Things (C-IoT)
● IBM: The Business of Things
● IBM: The Economy of Things

4. 4 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
Definitions
For the purpose of this report, we will define the “IoT” and “wearables” as subcategories of
“connected devices.” A connected device or smart device is a physical object in which
electronics, software, sensors, and network connectivity are embedded to enable these objects
to collect and exchange data. Both the “IoT” and “wearables” belong to the “connected devices”
paradigm, whereas the “IoT” usually refers to connected devices that are not carried on the
human body, a function that is fulfilled by the term “wearables.”
Although this report focuses primarily on the IoT, it also makes reference to “wearables.”

5. 5 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
IoT Market Drivers and Challenges in 2016
For many, 2015 was a year of exponential innovation in all areas. The CES 2016 conference
was a living example, with drones, virtual reality (VR), 3D printers, and many more innovations
that are further described in my previous report (Post-CES 2016: The Internet of Things and
Wearables).
As Dr. Michio Kaku remarked in “Visions of the Future,” a three-part BBC miniseries,
“We are making the historic transition from the age of
scientific discovery to the age of scientific mastery
in which we will be able to manipulate and model nature almost to our wishes”
~ Dr. Michio Kaku
In other words, we are evolving from passive observers of nature into its active choreographers.
Below are several areas of exponential innovations that are rapidly bringing the IoT paradigm to
reality, laying the path for a brand new connected world.
● As consumers are continuously connected to information in real time, primarily through their
mobile devices, they will expect not only real-time connectivity but also insightful real-time
data with which they can make valuable, actionable decisions.
● Machine learning, a subset of artificial intelligence (AI), is a critical component of the IoT,
because a massive number of data points (big data) must be converted into valuable and
actionable insights. Existing methods and systems are not fit for the job, and it is impossible
for humans to review and process all this data. Machine learning systems are built to find
patterns, correlations, and anomalies and boil them down to what is really meaningful (see
deep learning, ANN). The long-term R&D investments of Google, Microsoft, and IBM in
machine learning, cloud, and geolocation technologies are examples of how large
corporations are leading the way. Most recently, Google has launched an open source
machine learning project, TensorFlow, which gives developers the tools to build large,
intelligent IoT networks using “If This Then That” (ITTT) rule engines to control and integrate
IoT devices.
● Sensors have become commodities: As both size and manufacturing cost have decreased,
sensors have increased in both function and presence in connected devices. The sensors
listed below are common in IoT environments:
○ Accelerometers
○ Gyroscopes
○ Magnetometers
○ Humidity Sensors
○ Pressure Sensors

6. 6 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
○ Temperature Sensors
○ Acoustic Sensors
○ Digital Light Sensors
● New energy harvesting technologies are making these sensors either energy independent
or extremely efficient in both wearable and IoT devices.
“The common feature with all of them [i.e. wearables] is the prominence of
sensor options as the key enabler for their most useful functions.
Sensors collect data about the physical and chemical properties of the body
and local environment and use it to feed algorithms which output insightful information. With
coverage of all of the prominent incumbent sensors and the most promising emerging options,
the report concludes that there will be 3 billion wearable sensors by 2025, with over 30% of
them being new types of sensors that are just beginning to emerge.”
~ IDTechEX, “Wearable Sensors 2015–2025: Market Forecasts, Technologies, Players”
“IHS predicts that from 2013 to 2019 the worldwide market for sensors in wearables will expand
by 67 million units . . . . Its market growth is driven by the increasing number of sensors in each
product sold. This basically means that with wearables getting more complex and measuring
more parameters, more sensors will be needed to be installed in them. They predict shipment of
sensors will rise faster than the market of wearables themselves. The average wearable device
shipped in 2019 will incorporate 4.1 sensor elements, up from 1.4 in 2013.”
~ IHS, “MEMS & Sensors for Wearables Report”
● Network connectivity for IoT devices requires a better range of standard connections as well
as the ability to overcome obstacles (walls, floors, etc.). For this reason, the Wi-Fi Alliance®
has introduced the low-power, long-range Wi-Fi HaLow™ designation for products
incorporating IEEE 802.11ah technology.
● New sources of funding such as Kickstarter and Indiegogo allow for new and disruptive
products, however, more serious initiatives from large corporations such as Google,
Microsoft, Intel, IBM, and Cisco are the main drivers

7. 7 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
●
Corporate Investors Participate in a Record Number of IoT Startup Deals In 2015
The challenges below will have an impact on the overall value of the IoT and its rate and length
of adoption.
● Interoperability – The value of the IoT is “the sum of it all”: the more sensors, apps,
platforms, and data are interoperable, the more we humans will benefit from IoT.
“Right now people mostly buy single products for a single purpose . . . .
As a shelf item in an Apple Store or BestBuy, it works.
But if you want to make those things sing and dance together, forget it.”
~ Frank Gillett, a vice president and analyst at research firm Forrester. The Internet of Things Is
Everywhere, But It Doesn’t Rule Yet - WIRED (Dec 2015)
● Consortiums – The majority of key players have not yet joined any consortium or alliance
(e.g., Zigbee, AllSeen).
● Security – Unfortunately, 2015 has been an exceptional year for data breaches, exposing
consumers’ personal records and financial and health information. Although consumers will
be more cautious in 2016, the IoT market offers great opportunities for increased security for
objects and communications.
“Security is a potential barrier to customers adopting the new technology.”
~ John Curran, managing director of communications, media and tech practice for consulting
firm Accenture.

8. 8 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
“IoT is an especially promising market for the digital identification ecosystem . . . . With IoT
rapidly touching all spheres of communication, the digital identification industry has found
considerable merit in entering the machine-to-machine (M2M) market by providing specific
SIMs or modules that determine whether or not to allow a machine access to the network.”
~ Frost & Sullivan Digital Transformation Global Program Director Jean-Noël Georges.
● Privacy has been and continues to be an important subject in 2016, particularly in the
health sector.
● Big data has several challenging characteristics:
Volume: The quantity of generated and
stored data. The size of the data
determines the value and potential
insight and whether it can actually be
considered “big data” or not.
Variety: The type and nature of the data:
text, images, audio, or video.
Complexity: managing data coming from
multiple sources can be very
challenging. Data must be linked,
connected, and correlated so users can
query and process it effectively.
High velocity: real-time, performance
and volume challenges (real-time
analytics).
“A full 90 percent of all the data in the
world has been generated over the last
two years.”
SINTEF - Big Data for better or worse

9. 9 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
IoT Value Proposition Per Market Segments
The two tag clouds below are a visual depiction of tags generated using 2,066 company
descriptions by firms that conduct business in the areas of connected devices (IoT, M2M) using
DataFox data services, a deal-sourcing and research platform covering private technology
companies. DataFox Intelligence organizes information about more than one million companies
using machine learning and natural language processing algorithms.
The color and font size represent the prominence or frequency of the tags’ use and how
representative they are of market trends in the IoT. The first tag cloud provides a high-level
overview of company trends. The following words were excluded from the list: “and, Internet,
IoT, of, technology, things, wearable.”
Tag Cloud 1 - General

10. 10 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
In the second tag cloud, the following words were excluded from the list: “and, consumer, data,
electronics, hardware, internet, iot, management, mobile, of, security services, software,
technology, things, wearable” and provided a more granular view by exposing the primary areas
of business interest.
Tag Cloud 2 - Granular

11. 11 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
IoT implementation and value proposition varies for each industry sector:
● Healthcare
● Home
● City
● Environmental
● Security and emergency
● Retail
● Logistic
● Industrial
● Agriculture
● Cars and transportation
● Energy
The interactive mind map below highlights common use cases for each industry sector as well
as common values propositions. Click on the banner below to fully explore the mind map.

12. 12 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
IoT Revenue Models
Categories
This section reviews the various categories of revenue models in the context of commerce
transaction types, and delves deeper into these models through specific examples.
First, we provide a brief semantic review, as people tend to confuse the terms “business model”
and “revenue model”.
A revenue model is a framework for generating revenues that identifies which revenue source
to pursue, what value to offer, how to price the value, and who pays for the value. It is a key
component of a company’s business model.
Categories of revenue models – As the lines that separate the digital and physical worlds blur,
so do the monetization models. Physical objects are becoming smarter and more connected
and seamlessly integrated with services, allowing for various sources of revenue. For the
purpose of this report we will focus on the following categories. Many companies, the B2B in
particular, rely on more than two revenue models.
● Product purchase (one-time) – This model is common in the consumer electronics market,
selling devices with (free) embedded services or mobile applications (apps) in Apple or
Android stores.

13. 13 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
● Product and services purchase (one-time) – In the B2B world, enterprise software is
licensed, hardware is sold, and consulting and training services are either bundled in the
price or sold separately. As the industry is migrating to software-as-a-service (SaaS) or
platform-as-a-service (PaaS) models, vendors adopt a subscription revenue model as a
primary source of income.
● Subscription (recurring) – This model is prevalent in the consumer market and, as
mentioned previously, is rapidly growing in the B2B market. Usually, in the subscription
model, the consumer can upgrade from a freemium model and buy more advanced
features, increased privacy, and ad removal. This model applies to online services accessed
through a web browser. Cloud services and storage vendors charge their customers a
monthly subscription fee for a certain amount of storage or analytics services.
● Freemium – This is the dominant model for apps and online services that provide free
services with limited features in exchange for commercial use of data (e.g., targeted ads).
Customers have the option to migrate to a subscription model as described above.
● Transactional – This is a pay per use model that is common with major IoT platforms. For
example, the Amazon AWS IoT platform charges per number of messages sent from/to
each connected device. This model is explored further below.
● Leasing – This model is uncommon but still relevant in the hardware equipment market.
The above revenue models can be attributed to two commerce transactions types (as well as
two sub-categories):
● B2C – Business-to-consumer, such as apps or consumer electronic devices hardware
products sold directly to consumers.
● B2B Vertical – Business-to-business vertical for specific industries, such as Apple’s
licensing of HomeKit to develop home automation and security apps and products.
● B2B Horizontal – Integration via web services or business partnerships between IoT
vendors (cloud services, analytics, business intelligence, etc.)
The diagram below presents both revenue models and commerce transaction types in the
context of the IoT marketplace.

14. 14 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur

15. 15 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
Examples
The three juggernauts – Apple, Alphabet, and Windows are the “platform” leaders that
encompass both B2C and to some extent the B2B markets with the greatest offering, greatest
brand exposure, and strongest market cap and strategic acquisitions. Each table provides an
overview of the market caps for these platforms, the various categories of acquisition trends in
order of importance, their involvement in the IoT marketplace, and their various revenue
models.
1 Company Name Market Cap Number of Employees
$541.53B 93,657
Corporate Strategy: Acquisition trends by sector in order of importance
music, security,
computing, data, analytics, marketing,
sensors, learning, facial
IoT Relevance
● IoT platform: Apple HomeKit home automation
● Strategic partners: Philips, Eve, Ecobee
● Wearable platform: iHealth/Apple watch
● Connected devices (smartphone, watch, tablet)
● Apple iOs and App store platform
● Apple car (codename: “Titan”)
Revenue Models
Multiple: products, subscription, freemium

16. 16 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
2 Company Name Market Cap Number of Employees
$477.59B 61,377
Corporate Strategy: Acquisition trends by sector in order of importance
web, advertising, satellite, AI, cloud
IoT Relevance
● SaaS / PaaS / Cloud-based services and storage
● Home automation: Nest
● Google Glass
● Brillo: embedded OS, core services, developer kit, and developer console for IoT
● TensorFlow: open-source AI engine
Revenue Models
Multiple: products, subscription, freemium
3 Company Name Market Cap Number of Employees
$407.3b 120,612
Corporate Strategy: Acquisition trends by sector in order of importance
customer, enterprise,
pen, touch,
data, analytics,
home
IoT Relevance
● Strategic partnership with Samsung announced at CES - “IoTivity”
● OS platform, cloud services (Storage, PaaS, and SaaS)
● Microsoft Windows IoT core for small devices (and Samsung in the future)
Revenue Models
Multiple: Products and services, subscription, freemium

17. 17 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
3 Company Name Market Cap Number of Employees
$132.55B 95,764
Corporate Strategy: Acquisition trends by sector in order of importance
Mobile,
medical, payment, storage, services
IoT Relevance
● Strategic partnership with Microsoft announced at CES - “IoTivity”
● Connected devices (smartphone, watch, tablet)
Revenue Models
Multiple: Products
The remaining examples represent a variety of IoT leaders through their innovation, revenue
models, and/or market positioning. I had the opportunity to meet with some of their
representatives during the CES 2016 convention. These companies appear in alphabetical
order.
Amazon Web Services (AWS) is a collection of cloud
computing services that includes the well-known
Amazon Elastic Compute Cloud (EC2), offering virtual
machines, and Amazon Simple Storage Service (S3),
an online file storage web service. The AWS IoT
service, recently added to this list, allows connected devices to interact securely with cloud
applications and other devices. Using the various existing Amazon services (e.g., Amazon
Machine Learning, DynamoDb), IoT applications can be built to gather, process, analyze, and
act on data generated by connected devices without having to manage any infrastructure.
Amazon is well known for providing reliable, secure, and scalable cloud-based services at an
extremely competitive cost. The AWS IoT service revenue model is as follows:
● Customers pay per messages published and messages delivered to devices or applications
(transactional model). Unlike IBM or Bosch, the price doesn’t vary by device type but by
region (cost is higher for messages published or sent to Asia Pacific).

18. 18 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
Bosch is a multinational
engineering and electronics
company based in Germany.
Bosch’s IoT market focus is on
manufacturing of hardware
products with embedded software that can be mass produced. Bosch’s approach is similar to
that of IBM: rapid prototyping, implementation, and valuation of an IoT platform for business
customers using the XDK Cross Domain Development Kit.
The XDK Cross Domain Development Kit, which sells for $185 MSRP, includes eight embedded
sensors. By combining this development kit with Bosch’s professional services, business
customers have access to rapid prototyping, testing, requirements, specifications, mass series
production of hardware embedded software, certification, and compliance support.
● Bosch’s primary revenue model in this market is a product and services approach (no cloud
services or apps).
La Poste is a postal service
company in France and an
interesting case study for the
IoT.
It has remained a public
company for many years. However, because of EU directives requiring member states to
introduce competition in their postal service, in 2005 the French government allowed private

19. 19 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
postal service companies to begin operating and transformed La Poste into a public-owned
company limited by shares in 2010.
Because Internet development has reduced its postal activities, La Poste diversified its business
and leveraged its brand as a trustworthy, secure company that delivers goods, mail, and
services to consumers and businesses.
La Poste is the second largest employer in France and offers web-based email to approximately
1.6 million active accounts. More recently, the group has created a document exchange and
archiving platform called Docapost that has recently expanded its IoT activities by offering a
business intelligence (BI) platform to enable businesses to connect and securely exchange data
between connected devices and applications. Docapost has several revenue models:
● Subscription for SaaS, PaaS, and cloud storage
● Products and services for consulting and system integration offerings
● Cost is per device and not per message (transactional), unlike Amazon or IBM
Exosite provides a proprietary
platform and consulting services
to enable customers to deploy
their IoT infrastructure. Because
many hardware vendors realize
that unintelligent hardware are commodities, Exosite helps these vendors create “added value”
services within their existing infrastructure. Exosite has several revenue models:
● Products and services through their professional services organization (Time and materials)
● Transactional costs messaging per device
● Subscription model for cloud storage
IBM is one of the biggest investors in the IoT with a focus in
the B2B enterprise market that leverages its strength in
analytics, business intelligence (BI), artificial intelligence (AI),
and integration of these services into its “Cognitive IoT,” the
“Watson internet of things.” Like Bosch, IBM leverages Texas
Instrument’s sensor tag for rapid prototyping of IoT solutions to help build customers’ ROI in a
cost-effective manner. In a recent study, “The Business of Things,” IBM states that 65 percent of
respondents were unsure about IoT ROI.

20. 20 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
IBM IoT platform revenue models include
● Subscription for their BlueMix SaaS, PaaS, and IBM cloud storage
● Products and services for consulting and system integration offerings
● Transactional cost model for messaging between devices and apps, which varies based on
device category
Oracle recently launched its
cloud-based platform, the Oracle
Integration Cloud Service (ICS),
by converting some of its key
customers and working toward
converting its remaining
customers over time while gaining new ones. Oracle therefore is migrating from an on-premise
business (product and service model) to an as-a-service strategy (subscription and transactional
models). We can also envision a transition from traditional professional services to integration
and implementation support.
Oracle’s Integration Cloud Service (ICS) objective is to help customers streamline the rapid
development and deployment of cloud-based services with pre-built integrations.

21. 21 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
Oracle Internet of Things (IoT) is a cloud-based offering platform within the ICS that allows
companies to connect their devices to the cloud, analyze data from those devices in real time,
and integrate their data with enterprise applications, web services, or other Oracle cloud
services such as Oracle Business Intelligence Cloud Service.
Oracle revenue models have the following features:
● Like Amazon, Docapost, and IBM, Oracle IoT Cloud Service offers a subscription model.
● Oracle charges customers a monthly fee per a certain number of devices with a range of
messaging per device per month (transactional model). Neither IBM nor Oracle charge all
devices in the same manner, whereas Amazon has a single price for all.
The interactive mind map below highlights additional examples of vendors’ revenue models
within each IoT market segment.

22. 22 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
The Value of Data
The core business objective of both the IoT and wearables markets is to capitalize on the value
of data to drive innovative services with a quantifiable return on investment (ROI).
The value of data depends on a company's core business. For example, companies that sell
consumer electronic products rely on data as a means to improve their customer service and
support, whereas those who offer free mobile apps or free online services rely on data mainly as
a primary source of revenue through advertising.
The diagram below represents the value of data in the “knowledge economy.”

23. 23 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur

24. 24 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
In the “Knowledge Economy,” data is vital for all business units, allowing for greater competitive
edge, customer acquisition, retention, and targeting, as well as helping to define and refine
pricing of products and services. For example, a product manager will use data to
● Assess how a product is used
● Identify success factors
● Identify future product requirements
● Allow for self/remote diagnostics
● Streamline and automate technical support
● Improve CRM (improve customer relation quality and strength)
Data interoperability between various services and business partners provides great
“functional value” that allows for better user experience (e.g., log into your Airbnb account via
your Facebook account or apply for a job on the career page of a company using your LinkedIn
account) as well as financial ones.
In the consumer world, the “IoT product” becomes a “data-driven platform”; once activated, it
provides customers with content and a digital experience. For marketers, the IoT product offers
the ability to provide “on-demand personalized services and experiences.”
“Marketers default to delivering advertising messages in a regular sequence of campaigns,
instead of ‘on-demand’ personalized services and experiences.”
~ Andy Hobsbawm, the CMO of EVERYTHNG
For shareholders of services businesses, data embodies financial potential or company value
which is calculated through various formulas using the user base and data types (generic and
personal data) owned by a company. Not all data points have equal value.

25. 25 IoT Market Trends & Revenue Model Anatomy (January 2016)
by Guillaume Tourneur
Additional References
Wearable Sensors 2015–2025: Market Forecasts, Technologies, Players (IDTechEx)
http://www.idtechex.com/research/reports/wearable-sensors-2015-2025-market-forecasts-
technologies-players-000431.asp
MEMS and Sensors for Wearables Report – 2014 (IHS Technology)
https://technology.ihs.com/496122/mems-sensors-for-wearables-2014
Market Forecast: Wearables (CCSInsight)
http://www.ccsinsight.com/our-services/1711
Unlocking the Potential of the Internet of Things (McKinsey)
http://www.mckinsey.com/insights/business_technology/the_internet_of_things_the_value_of_di
gitizing_the_physical_world
Who's Who on the Adoption Curve (MediaPost)
http://www.mediapost.com/publications/article/257488/whos-who-on-the-adoption-
curve.html?utm_source=newsletter&utm_medium=email&utm_content=bottom&utm_campaign
=85737
Marketing and the Internet of Things, Closer than You Think
http://chiefmartec.com/2015/06/marketing-internet-things-closer-think/
What’s The Value of Your Data?
http://techcrunch.com/2015/10/13/whats-the-value-of-your-
data/?ncid=rss&utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+Techc
runch+%28TechCrunch%29&utm_content=FaceBook&sr_share=facebook
Apple and Google Know What You Want Before You Do
http://www.wsj.com/articles/apple-and-google-know-what-you-want-before-you-do-
1438625660?mod=e2li
Wearable Technology Is Not Going Anywhere!
http://www.wearable-technologies.com/2015/07/wearable-technology-is-not-going-anywhere/
WPC - The Wearable Future
http://www.pwc.com/us/en/technology/publications/wearable-technology.jhtml
Use Data Visualisations to Tell Stories and Gain Influence
https://www.linkedin.com/pulse/use-data-visualisations-tell-stories-gain-influence-jay-
zaidi?trk=hp-feed-article-title-share
The Invasion of Wearables in the Workforce

26. 26 IoT Market Trends & Revenue Model Anatomy (January 2016)
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http://techcrunch.com/2014/12/14/the-invasion-of-wearables-in-the-workforce/
Wearables Will Be Routine in the Workplace by 2020
http://www.baselinemag.com/innovation/wearables-will-be-routine-in-the-workplace-by-
2020.html
The Inception of Wearables in the Workforce
https://wtvox.com/2015/04/the-inception-of-wearables/
The Internet of Things (IoT) Has Arrived - What You Should Know (LinkedIn Pulse)
https://www.linkedin.com/pulse/internet-things-iot-has-arrived-what-you-should-know-chuck-
brooks

27. 27 IoT Market Trends & Revenue Model Anatomy (January 2016)
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About the Author
Guillaume Tourneur is a technology product manager and business development professional.
His expertise is bringing new technology products to life in organizations ranging from
bootstrapped startups to global Fortune 500 firms. He has led teams through the product
development cycle, evaluated markets and potential ROI, and developed and implemented go-
to-market strategies that have generated $20+ million in revenue.
His industry background includes connected devices and the Internet of Things (IoT), with an
emphasis on wearables for the sports and fitness industries, and entertainment/Internet
technology such as video on demand (VOD), recommendation engines, and digital asset
management systems (DAM). He has extensive experience in collaborating with agile
development teams.
Other interests include IRONMAN triathlon training.
Email: GTourneur@gmail.com