=Paper=
{{Paper
|id=Vol-2025/paper_ddds_2
|storemode=property
|title=How to Build a Successful Business Model with Big Data Platforms?
|pdfUrl=https://ceur-ws.org/Vol-2025/paper_ddds_2.pdf
|volume=Vol-2025
|authors=Jos A.A.M. Verstegen,Bart Doorneweert
}}
==How to Build a Successful Business Model with Big Data Platforms?==
https://ceur-ws.org/Vol-2025/paper_ddds_2.pdf
How to build a successful business model with big data platforms?
A product lifecycle perspective
Jos A.A.M. Verstegen Bart Doorneweert
Wageningen University and Research Source Institute
jos.verstegen@wur.nl bart@source.institute
ABSTRACT more valuable when more people use it [1]. The detailed
A product lifecycle approach is used to describe the origin, information about user preferences itself offers a resource
history and development of current big data platforms, using for new business opportunities. It is for that reason that data
literature sources, business case descriptions, interviews is something referred to as the new oil [2].
held with founding team members of platform businesses,
and experiences in action research projects on big data Ignited by the promising market opportunities, the number
platform development in Dutch agriculture. The paper of big data platform initiatives are numerous. Many
concludes with an outlook on future developments and companies are looking for ways to ensure long-term access
business models. to big data. For this reason Monsanto, a large crop protection
company, acquired The Climate Corporation, a digital
agriculture company that examines weather, soil and field
CCS CONCEPTS
data for $930 million to “unlock new value for the farm
Human-centered computing → Collaborative and social
through data science” [3]. Many other companies, either
computing → Collaborative and social computing theory,
seeing great opportunities or fearing to be disrupted, want to
concepts and paradigms → Social content sharing
follow suit and aim to develop their own platform. Yet,
developing a big data platform is no easy ride, and there is
KEYWORDS no clearly set path to build a successful platform.
business models, big data, platform development
The objective of this paper is to describe the patterns and
ACM Reference format: stages that can be distinguished studying the origin, history
J.A.A.M. Verstegen and R.B. Doorneweert. 2017. How to and development of current big data platforms, in order to
build a successful business model with big data platforms? provide a context and inspiration to (clusters of) companies
A product lifecycle perspective. Proceedings Paper in Pdf and other institutions that consider or are in the process of
Format. In Proceeding of The International Conference on developing a big data platform.
Knowledge Technologies and Data-driven Business, Graz,
Austria, October 2017 (i-KNOW '17), 9 pages.
2 METHODOLOGY
1 INTRODUCTION In this study we combine industry & academic (grey)
Thanks to great developments in sensor-, information-, and literature resources, including business case descriptions,
communication technology large quantities of data are with interviews held with founding team members of
becoming available at real-time and at low costs. This opens platform businesses, and our experiences in action research
the door for businesses to receive information on supply- projects on big data platform development in Dutch
chain variables such as delivery status, processing failures, agriculture [4-6]. In these public-private partnership research
quality control, etcetera. On top of that, the granular usage projects Wageningen University and Research acts as a
data, coupled with direct communication with end-users knowledge broker providing both technical support on data
allows to evaluate user satisfaction and to provide them with exchange protocols and support on business model
more personalized products and services. development and related governance issues.
Platform opportunities emerge when the accumulated data We will use the product lifecycle perspective as an outline to
on a specific customer or user group becomes so insightful, describe the patterns and stages that can be distinguished
that it is possible to develop related services for a second studying the origin, history and development of current big
complementary customer or user group who wants to gain data platforms, building on the business model lifecycle
access to the prior. For instance, search engines or social perspective on two-sided internet platforms of Muzellec et
media users generate profile data, which can service a group al. [7] and the preparation, spread, evolution (PSE)
of advertisers who seek to target those specific users. framework of Han & Cho [8].
Positive network externalities (also referred to as the
network effect) arise meaning that a good or service becomes
I-KNOW '17, October 2017, Graz, Austria J.A.A.M. Verstegen and R.B. Doorneweert
The paper will be structured according to the original entry software). Once Glooko’s launching business model
product lifecycle categories of Raymond Vernon [9]: “new gained traction with this early group of diabetics, it opened
product”, “maturing product” and “standardized product”. the gateway for platform opportunities, where Glooko went
We argue that the ultimate form of a big data platform is not to look for ways for diabetics to share their data with their
a simple question of choice, but the result of the intent of the physicians. Ultimately, it was aiming to tap into the multi-
owners of the platform on the one hand, and the experience billion dollar opportunity of the insurance market. However,
that participants to the platform allow to be expanded on the none of these opportunities would be of any real value if
core value of the platform on the other hand. Both factors Glooko wasn’t able to onboard a substantial user base of
shape the extent to which a platform can feasibly grow to in diabetic patients with a self-standing service that helped
size, and scope. In the final section we will discuss the them with the basics of managing their disease.
implications of historical development patterns and stages Consequently, Glooko’s next challenge was to have these
for current platform initiatives and elaborate on alternative diabetic patients migrate to connect with other users on the
roles and business models for companies and other platform using the logbook functionality. The company had
institutions that want to engage in big data developments. no way of saying that their customers would be willing to do
that for certain, until they arrived at that point when they
could test it.
3 NEW PRODUCT – THE ORIGING OF BIG
DATA PLATFORMS 3.2 Intentional Platforms
Looking at the earliest phase of the lifecycles of today’s big There are always two or more participant groups to a
data platforms, two types of origins can be distinguished, platform. But one of those participant groups is typically
namely 1) emerging platforms where a platform opportunity more essential, and also decidedly more difficult to attract to
revealed, only after a product or service has gained traction the platform than the other. Fishingbooker is an example of
with a single participant group, and 2) intentional platforms, an intentional platform, which can only work when two
where the outset was to involve two or more participants parties are involved from the beginning. Our interview with
groups from the beginning. co-founder of Fishingbooker.com, Nemanja Cerovac, for
instance revealed how that platform had to deal with the
3.1 Emerging Platforms challenge of connecting people who wanted to book fishing
Many of today’s platforms did not start-off as a platform but trips, and boat captains, who offer those trips.
evolved to it after realizing that the user base, e.g.
accumulated through a popular app, has potential for a There’s no rule to either supplying, or demanding platform
platform function. When the platform’s origin is a participants being the most critical to attract to the platform.
conventional pipeline business model with one user group or This varies according to context and platforms. Also, the
customer group, it means that another group should be new roles that participants assume can be either accretive or
‘seduced’ to use the platform as well. Usually there is no depletive. For example, consumers and producers can swap
imminent need for the first members of this peer group to roles in ways that generate value for the platform. Users can
join the platform; they can be contacted with the same ease ride with Uber today and drive for it tomorrow; travelers can
through other channels. Yet, with a growing number of peer stay with Airbnb one night and serve as hosts for other , e.g.
group members joining the platform it will evolve into a customers the next [10]. But spotting the most difficult party
more important channel increasing the urge for other peer (side) to the platform can be done from the drawing board,
group members to join as well. Think how LinkedIn used its Cerovac said. You can imagine being able to attract people
website as a professional profile formatting service, before it who want to book fishing trips. But then to engage them with
was useful as a professional networking service. (choosing the platform, there would need to be a credible offering of
focus on one vertical). boat captains on site who offer trips.
In Dutch agriculture we see that an intentional platform is
The case of Glooko: Initially Glooko was launched as a
formed by a farmer organization and agricultural
smartphone-based log of blood-sugar metrics for diabetics.
cooperatives to facilitate farm data exchange and retain data
Before, diabetics had to read out the glucose levels from their
ownership at the members of the cooperatives, i.e., the
blood testing meters by hand. With Glooko this process is
farmers [4]. Because most Dutch farmers already exchange
automated using a smart cable connecting the glucose meter
data with (one or multiple) of these cooperatives, there is
and the smartphone. Glooko’s first bet was that they could
already a solid user base to start with.
provide such a service via an app on the Apple App Store,
and generate revenues from app sales, as well as from sales
of the cable. Important part of this value proposition to 3.3 Development of the platform’s business
diabetics was that the cable was device agnostic, enabling model
users to read out glucose data from a variety of device brands In the earliest phase of a product lifecycle a business model,
(at the time, each glucose meter had its own cables, and data- describing the underlying economic logic of how a business
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How to build a successful business model with big data platforms? I-KNOW '17, October 2017, Graz, Austria
can deliver value to its customers, has to become clear. The find a sustainable basis for business growth, i.e., to
same is true for a platform, where a two-sided (or multi- accumulate critical resources by finding enough participants
sided) business model has to be defined. The biggest to expand the platform, and build its clout amongst internet
challenge of creating a platform, regardless of whether it is users. Bringing on a critical user group to the platform
an emerging or an intentional platform, is to have appealing increases the stickiness of the platform for others. Only after
value propositions for (at least) two groups of users. The so- stickiness is nearly instituted will most successful platform
called chicken-or-egg problem [11] is a critical balancing owners think of harvesting value from it [14].
act, where first a group of the most hard-to-retain group of
users’ needs to be convinced to use the platform. That group The case of Fishingbooker: “Growth is not an implicit
then needs to be suited with a matching engagement from consequence of a platform demonstrating its value, but of
their matching parties. Each increment in the prior, needs to careful, and thoughtful engineering of a growth engine”, as
be met with a proportional increment of the latter. This Nemanja Cerovac of Fishingbooker.com stated in his
balancing act is handwork at first, Cerovac said. interview. In the case of Fishingbooker the challenge after
Fishingbooker onboarded its first fishermen through direct successfully matching the first fishing boat captains with
contact, even going so far as travelling to the Florida Keys, fishing tourists was to find more captains to sign onto the
to have them sign up to the platform. Also Airbnb had initial platform. Previously this was handwork, with cold-calling,
problems to get a good matching because the pictures of and in-person visits. But in order to grow sustainably, this
accommodations of Airbnb listings were too bad to convince process needed to become more scalable. Naturally,
anyone to book these. Having professional photographers Fishingbooker turned to online advertising, targeting fishing
visit the hosts and make pictures turned out the solution. boat captains through Facebook. However they soon realized
Also, to develop the market in France Airbnb sent out teams that their targeting, and call to action in the marketing
of people to organize parties, info sessions and other “on the message were not optimized yet, resulting in a cost per sign-
ground” activities to convince people to list their on that was too high to sustainably grow the business. In
accommodations on Airbnb [12]. response to this dilemma, the Fishingbooker team changed
their focus to Mauritian fishing boat captains, as recreational
3.4 The transition from push to pull fishing is also a big activity there, yet Facebook advertising
Platforms generally come to life, putting a lot of effort in there only costed a fraction of advertising in the United
serving a specific small user group of early adopters, before States. This move allowed the team to experiment with their
they can grow out to become the default of the market. The advertising message, and optimize it for conversion to sales
first users are brought onto the platform by an active value online. Once the message had been tested, and showed
proposition push to on-boarding them. At a certain point, results, the team then opened the advertising to the United
data, and/or users will be accrue in the business model, and States again, but this time with result. It proved to be the
can be used as a new productive resource, which enables a basis for Fishingbooker’s exponential growth, making it the
new value proposition to be created [13]. Google for current go-to booking site for fishing trips in the United
instance, needed to collect enough users, and relevant data States.
before it could provide a targeting service to advertisers.
Typically the value proposition, e.g., the functionality of the Like Fishingbooker, many other platforms have faced the
platform, evolves over time, e.g. as new insights based on challenge of finding a cost-effective growth engine. Notably
user behavior become available. Airbnb used the classifieds website Craigslist, as a growth
channel, where Airbnb users could easily post their rental
homes on a platform with a huge audience [12].
4 MATURING PRODUCT – THE GROWTH
AND MONETIZATION OF BIG DATA Emerging platforms may have the option to revert to their
pipeline business model but intentional platforms that start
PLATFORMS from scratch building a user base face the risk that they never
reach enough credibility for their offering. If they aren’t able
After the “new product” phase, the platform concept has to crack the challenge of onboarding of their hardest
become visible and has proven to respond to the needs of the customers up till a certain velocity, they will never be able
(two or more) participant groups. Now the challenge to attract enough people from the other side of the market to
becomes to find a cost-effective way to grow the user base, that platform.
and create revenue streams that are substantial enough to
generate a profit.
4.2 Sustainable revenue streams
Wessel et al. [14] argue that “digital companies should delay
4.1 Critical resource accumulation profitability for as long as they can”. Because of the network
In the maturing phase one can expect that competitors may effect “it will always be better to harvest value after further
want to copycat the concept. Therefore, the prerogative is to increasing the stickiness of the platform”. Yet, only a limited
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I-KNOW '17, October 2017, Graz, Austria J.A.A.M. Verstegen and R.B. Doorneweert
number of platforms receive sufficient funding from There’s no doubt that Instagram was a great hit to its users.
investors to actually fuel their growth, but under very With its launch in 2010, it grew to one million users in two
specific conditions. Notably the taxi ride hailing app Uber months’ time [21]. Yet the business model didn’t have a
has received a lot of funding to fuel its growth. The condition solid revenue stream yet. To mediate this, Instagram has
it met for this was that it had a great organic growth engine been working with different options for advertising
to attract drivers, and passengers, and service them with a revenues. A notorious move by the company to strengthen
profit [15], but that this model wouldn’t easily spread to itself as an advertising platform was the change in the terms
other geographies. Therefore it needed to be subsidized to of service in 2012, In this change Instagram provided for
achieve this, spending an estimated $1,55 on every $1 it some essential provisions to enable them take ownership of
makes [16]. Therefore Uber is applying a lot of investor content provided to the platform, and to show advertisements
money to settle in a region, and then get its regionally in conjunction with users’ content. This raised a big backlash
profitable business model implemented [17]. from users [22]. As a consequence Instagram tweaked its
policy, and didn’t start with advertising until 2013 [23].
Most companies can’t follow Uber’s path because they have Currently even, it is still experimenting with new advertising
investor bases demanding profit maximization today. As for products, like the most recent one for business accounts with
the cost-effective growth, this is a major hurdle for many which it is backtracking on some of the ways that leading
platforms. Most have to bootstrap fund their growth accounts use the platform for online marketing [24].
engineering, and will either remain a niche or lose the
business if they fail to attract enough funding. That’s why
companies look for ways to draw value from the platform 5 STANDARDIZED PRODUCT – ALL SET
thereby changing functionalities, introducing subscription
fees or including advertisements. However, these changes
FOR FURTHER EXPANSION BY
are not without risks because they are frequently met with FANNING OUT OVER MULTIPLE
scorn from user groups, who dislike the change in user INDUSTRY VERTICALS
experience. Popular platforms like Twitter and Quora also Once a company has tackled the complexity of offering a
face this delicate balancing act as they search for ways of platform at scale, effectively captured an interaction between
generating revenue through the core value that they provide. participants and firmly established stickiness to the platform,
The challenge (and danger) here is to not lose grip on the the quest then turns to applying the resources that are
core utility, and user base in the process. Changes are accruing to the business model (user bases, data,
constrained by where the users want or permit value creation infrastructure) to fan out over multiple industry verticals.
to travel. Finding the right balance requires experimentation, This may take the form of expanding to new markets, or
e.g., agile development using minimum viable products [18], fulfilling a new role in the market. Even at this late stage, the
to find out what mix of participants, and platform services right step to expansion is still found through business
can be combined together to create or maintain an optimal experimentation [25]. Eisenmann et al. [26] refer to the
platform experience. At the same time, frequently upgrading “fanning out” phenomenon as platform envelopment:
the platform’s value proposition is essential as well. entering another platform market combining its own
Otherwise users may defect to another platform e.g., with a functionality with that of the target market in a multi-
more international scope, superior functionality or other platform bundle. For instance, Microsoft used its dominant
appealing features. In the case of social networks, it may be position with Windows operating system to promote
wise for companies to have alternative platforms and Windows Media player in the same bundle thus attacking the
communities because typically young people tend to defect till then dominant streaming media platform of
a certain social network after a while, e.g., when their parents RealNetworks (Real) and Google used its dominant position
have joined the social network [19-20]. as a search portal to launch Google Shopping thereby
attacking the price comparison and market outlet services by
The case of Instagram: Instagram was initially a platform platforms such as Ebay and Amazon.
where users could share their photo’s online with their
followers. The attraction to users was the ability to apply At a subsequent stage you can typically observe that the
various kinds of filters on photographs to give them extra earnings from offering web services (e.g. infrastructure and
effect. During the several years Instagram’s user base has access to user bases) to affiliated companies and developers
grown, it is increasingly being used for lifestyle marketing, are becoming a more vital element of the big data platform
to promote personal brands. This evolution towards business model than the revenues from actually selling own
marketing happened autonomously, driven by users commodities on the platform. Industry experts are
themselves. This despite the fact that Instagram is not fully hypothesizing that this is the final status in development of
equipped as a marketing service. For instance, the use of the company, where it focusses on being the fertile landscape
URL’s in comments, and in photo captions is prohibited, on which other ventures can grow. Thompson [27] expresses
making it hard to convert traffic to other destinations. the evolution that is taking place at Amazon as follows:
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How to build a successful business model with big data platforms? I-KNOW '17, October 2017, Graz, Austria
“Amazon may have started as The Everything Store but its as a platform has enabled Amazon to take a different look at
future is to be a tax collector for a whole host of industries its technology resources. Amazon has the data and the
that benefit from the economies of scale, and AWS (Amazon infrastructure to develop new offerings for a wide variety of
Web Services) is the model.” different markets. This technology infrastructure comes at a
very high fixed cost, and is only economically feasible at
Uber is progressing along the same line of development as scale, which keeps competitors from duplicating this model.
Amazon. The algorithm used to connect drives, and But the technology infrastructure has become so extensive
passengers can potentially be used for a whole range of other that it can support other business to run on it as well. Amazon
services. Starting with a specialized offering of offering taxi discovered this ability when it was working with larger 3rd
rides, the company is experimenting [28] with other logistics party vendors like Target, and Marks & Spencer’s online
applications like food delivery (UberEATS), and local parcel efforts. It even contributed to a more optimal utilization of
delivery (UberRUSH), which potentially hold more revenue resources [31]. This realization gave birth to Amazon Web
for the company. Services, which is an operating system to the internet for
other developers.
The case of Amazon: News of Amazon’s acquisition of
food retailer Whole Foods made headlines for 2017 [29]. For
many in the food industry this came as a revelation. But 6 DISCUSSION AND OUTLOOK
when one looks at Amazon’s track-record with spreading Above we have described the patterns and stages of
over different industry verticals, the acquisition is part of development of big data platforms. The product lifecycle
how the business intends to develop over the coming time. categories of Vernon (1966) offered an adequate structure to
Amazon’s approach to industry has been systematic, and discuss the development paths of the big data platforms we
backed by solid business experimentation rigor. Starting off have today. But what does this mean for organizations that
as an online bookstore in 1995, Amazon built a company are now looking for opportunities to start building a big data
model that is able to continuously try-out new propositions, platform? Is this still feasible or has the world market been
and test new business models, whilst executing on existing divided by the large corporations such as Amazon, Google
successes. Upon founding the company, Amazon and Facebook who are very keen not to lose their dominant
immediately took off on the market. It provided its users an positions and make sure to take over the companies that may
experience of huge selection of book title to choose from. become a threat to them such as WhatsApp, Instagram,
Through loopholes in the procurement system of large book YouTube, etc. And what if you do not want or cannot
wholesalers, which would still ship small volumes of books generate the resources to build your own platform but still
if they were part of large orders of books that were out of want to benefit from the large market opportunities of big
stock, Amazon was able to keep inventory costs low, and data. What alternative business models are available?
still offer a wide variety of choice to its customers. The
company was such a hit, that after launch, it only took
6.1 Does the winner take all?
Amazon 2 months to make sales from all states of the United
Today we see big data platforms highly dominating certain
States, as well as 45 other countries. Early growth was
markets: Alibaba accounts for over 75% of Chinese e‑
realized by listings on search engines like Yahoo, and
commerce transactions, Google accounts for 82% of mobile
Netscape, citing Amazon as a great resource on the tips these
operating systems and 94% of mobile search, and Facebook
sites used to suggest to its user on their landing pages. Also
is the world’s dominant social platform [10]. It is obvious
Amazon built affiliate programs as early as 1996, where
that those companies have a strong position but there will
people who shared their reviews of books online, could offer
always be room for new entrants, especially when those new
an Amazon link to their readership, where they could buy the
entrants manage to develop a distinctive value proposition
book. Affiliates were then offered a commission on those
and generate or collect enough funds to build market share.
sales. These measures, along with a host of other features
Back in 2007 the five major mobile-phone manufacturers—
that boosted customer conversion to sales, and retention to
Nokia, Samsung, Motorola, Sony Ericsson, and LG—
the platform, generated Amazon’s sticky growth engine. The
collectively controlled 90% of the industry’s global profits.
platform grew to a million served customers in 27 months,
Nokia and the others had classic strategic advantages that
and became the United States’ 3rd largest book seller by
should have protected them: strong product differentiation,
1998 [30]. From 1998 onward, Amazon went into sales of a
trusted brands, leading operating systems, excellent
broader range of products, starting with music, but also
logistics, protective regulation, huge R&D budgets, and
adding categories like toys, garden furniture, and apparel
massive scale. For the most part, those firms looked stable,
over the subsequent years. With every step in expanding
profitable, and well entrenched. Yet, in 2015 Apple’s iPhone
their product range, they also were attracting a broader range
singlehandedly generated 92% of global profits, while all but
of participants to the platform (even opening the platform to
one of the former incumbents made no profit at all (Van
3rd party resellers in 2000), and deepening the development
Alstyne et al., 2016). Airbnb also started as a small company
of its technology, and data infrastructure. This progression
at a time that Craigslist was the dominant website for
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I-KNOW '17, October 2017, Graz, Austria J.A.A.M. Verstegen and R.B. Doorneweert
offering private accommodations for rent. However, Airbnb ways of working are so novel that the legal implications of
managed to become the dominant platform for booking the platforms business mode are not clear yet during the
accommodations via the development of a stronger value earlier stages of the platform. But eventually as platform
proposition by avoiding the scam on Craigslist and arranging growth pushes on, and as it starts fanning out to different
high-quality pictures, and by ‘wickedly’ piggy-backing [11] verticals, legal frictions start to become apparent. An
Craigslist’s user base [12]. By doing this Airbnb unbundled increasing amount of lawsuits of competition authorities
the multi-purpose portal of Craigslist. A similar unbundling result in high penalties for platforms allegedly abusing their
happened with AOL that offered clients a large bundle of dominant position.
services from dialup to all the information services that you
use, all in one thing. Yahoo came along and unbundled all The European Union recently has fined Google a record-
the content from the access. And then one of the features of breaking €2.42 billion for antitrust violations pertaining to
Yahoo was search, Google came along and unbundled its Google’s Shopping search comparison service [35]. In
search. The fanning out on industry verticals and above The Netherlands, law suits were held by real estate brokers
examples show that bundling and unbundling of products to get access to and a proper listing on the dominant portal
and services is a continuous process, often facilitated by Funda.nl [36]. Uber’s business model thrives on independent
underlying technology change but always directed towards drivers as customers to its platform, not as employees. But
increasing customer value [32]. recent labor lawsuits indicate that Uber has a significant
employer responsibility towards their drivers, which would
Incumbents from more traditional industries are also waking make its business model significantly less scalable than it
to the need for business model innovation, and currently is. Other legal liabilities, like Uber’s infringement
experimenting with new ways to better service their of local taxi transport regulations, would jointly have such a
customers. Recently Disney announced that it will be large exposure, that it exceeds Uber’s valuation, and cash at
starting its own, dedicated movie streaming service, and is hand [37]. The same goes for Amazon as it will face scrutiny
going to pull distribution licenses to other services, like from competition authorities following acquisitions like
Amazon, and Netflix by 2019 [33]. This business model Whole Foods. Airbnb is another platform that has faced legal
innovation implies significant changes to competitive challenges, notably regarding city taxes. As the platform
balances, as Disney movies, including big titles like Star grew, it was able to do so without being noticed much by the
Wars, and Toy Story, tend to draw large numbers of viewers. city authorities. But as the platform grew, and existing
In the same way, the recent Whole Foods acquisition by hospitality services started pointing to the unfair advantage,
Amazon, is also likely to provoke changes with incumbents, Airbnb was faced with tax compliancy, and a significant
suggesting that the battle for supermarket retail has stepped administrative burden, and friction to the platform’s growth.
up pace, and is not decided as of yet. This uncertainty to growth comes at time, that Airbnb is also
looking for new directions in which to expand the platform
Another reason to believe that there will remain room for into the travel industry [38].
new entrants is the fact that ancient transaction costs theories
[34] will also remain valid in this ‘new economy’ (although 6.2 Other business models
equilibria may shift considerably). Sure, positive network What other business models exist if you do not want or
externalities exist meaning that a good or service becomes cannot generate the resources to build your own platform but
more valuable when more people use it [1]. This will fuel the still want to benefit from the large market opportunities of
emergence of large, international corporations with gigantic big data? Chen et al. [39] describe a chain of big data
user bases and various industry verticals in different parts of applications that can form the starting point to develop
society. Yet, these conglomerates will also face diminishing alternative business models besides offering a platform.
returns to management and thus increased costs of Kempenaar et al. [40] have summarized their chain in six
organizing a large firm, particularly in large firms with many chain stages. Business models can be developed around
different plants and differing internal transactions (such as a products and services on data capturing, data storage, data
conglomerate). This is especially true when frequent transfer, data transformation, data analytics and data
innovations are essential to prevent users (producers, marketing. It would take another paper to elaborate on all
consumers, developers) from defecting to other platforms, these models individually but it is clear that the market
making the conglomerates vulnerable to disruption. opportunities from big data platforms will also boost new
market opportunities in other parts of the data chain, ranging
Moreover competition authorities and societal resistance from more requests for sensor companies to capture data to
will limit the growth of conglomerates. Stickiness of a more trusted advisors who can filter, combine, analyze, and
platform can also become too extreme when denying proper interpret big data flows to come up with relevant information
access to or listing of third parties prevents those parties to support specific customers. Such a trusted personal
from having fair competition. Platforms thrive on new ways advisor would then no longer be exclusively for the very
of connecting participants, enabling them to share
information, and organize business exchanges. Often these
6
How to build a successful business model with big data platforms? I-KNOW '17, October 2017, Graz, Austria
wealthy people on our planet but thanks to big data could [9] Vernon, Raymond (1966). “International
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This work was partially supported by the Data Fair NL TKI- [10] Van Alstyne, Marshall W.; Parker, Geoffrey G. &
AF-16101 Project and the Personalised Nutrition and Health Choudary, Sangeet Paul (2016). Pipelines,
TKI-AF-15262 Project. Platforms, and the New Rules of Strategy – Scale
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