Top Global Thinker Applies Lessons from Airbnb and Uber to Open Government as a Platform

Interview with Sangeet Choudary: Lessons from Airbnb and Uber business models enable open government as a platform for entrepreneurs
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Recently, I interviewed Sangeet Paul Choudary, a C-level executive advisor and an international best-selling author. He is the co-author of Platform Revolution and the author of Platform Scale. He has been selected as a Young Global Leader by the World Economic Forum and is ranked among the top 30 emerging thinkers globally in 2016 by Thinkers50 Radar, a global ranking of top business thinkers. His work on platforms has been selected by Harvard Business Review as one of the top 10 management ideas globally for the year 2016-17. Sangeet is also the co-chair of the MIT Platform Strategy Summit at the MIT Media Labs, an Entrepreneur-in-residence at INSEAD Business School, and an executive educator with Harvard Business School Publishing. He is also the youngest person to be ranked by Thinkers50 India among the top 50 thinkers globally of Indian origin. He is a working group chair at the WEF’s Global Future Council on Platforms and Systems and an expert on the advisory council for the WEF’s initiative on the Digital Transformation of Industries. Sangeet’s work has been featured as the Spotlight article on Harvard Business Review (April 2016 edition) and the themed Business Report of the MIT Technology Review (September 2015). He is frequently quoted and published in leading journals and media including the MIT Sloan Management Review, The Economist, The Wall Street Journal, WIRED Magazine, Forbes, Fortune, and others. He is a frequent keynote speaker and has been invited to speak at leading global forums including the G20 Summit 2014 events, the World50 Summit, the Mobile World Congress, and the World Economic Forum global and regional events. Here’s our interview:

What is a platform? How does it relate to a networked market?

A platform is an Open Infrastructure, coupled with a governance model, that orchestrates and intermediates the interactions of multiple stakeholders. So a platform is fundamentally a plug-and-play infrastructure, into which multiple stakeholders can connect and start interacting with each other. Producers and consumers of value can participate on top of the open infrastructure. And once a market is created, the platform sets the rules of governance that determine what gets encouraged and what gets discouraged.

The platform is the central organizing mechanism that enables a networked market. It is possible to have a network market without a platform, as well, where you have market participants working entirely through peer interactions without a central organizing platform. But in most cases today, we see a central organizing platform whenever we see an instance of a networked market. I see the platform as an infrastructure, along with the governance model, that is required to orchestrate and enable a networked market.

Per reading your book, Platform Revolution, I noticed that your co-authors have published many articles on two-sided markets. But what is it that makes the platform new, differentiated from a traditional two-sided market?

A lot of the economic research on platforms was done over the last 15 years, but much has changed over the last five to six years because of a few different forces coming together. First, the proliferation of smartphones and subsequently the rise of the internet of things has made the world much more connected and has given rise to many more forms of networked markets that can be possibly created. Second, the rise of the social web has digitized identity and has led to the creation of trust and reputation in different forms because of which we are now able to digitize real-world interactions much more effectively. Third, we’ve seen an explosion of data because of an explosion in connectivity and new self-governance mechanisms. So these fundamental drivers have accelerated over the last five to six years and that is why what’s happening today is different from what has happened in the past.

To understand what's different this time around, it's also helpful to look back on my journey over the last 5-7 years and how I've seen incumbents move towards platforms. I got fascinated by platforms around 2008-09, just as we were seeing the early signs of these forces coming together. Back then, few people understood the insights from my research and its applicability across the economy. My journey ever since has mirrored the rise of the platform revolution. I first started writing a popular blog in 2012 which gained a lot of traction among startups. Around 2014, I started seeing interest in platforms spilling over to large enterprises. Accenture and Gartner declared platforms as key themes around 2014-15. It was around this time that platform strategy gained mainstream acceptance across industries and has been growing ever since. What's different this time is the the widespread applicability of digitized and networked markets to all industries.

In general, a platform is a multi-sided market if you will, and the two-sided market is the simplest configuration of any multi-sided market. Any multi-sided market can be broken into a set of different two-sided markets, which all interact with each other to enable the multi-sided market. But I would focus less on differentiating between what is happening with platforms today versus multi-sided markets in the past, except on one particular count, which is that the factors that move markets are not just the price. If you look at examples of markets in the past - stock markets, commodity exchanges - all of which were driven almost entirely by price. But if you look at real world interactions, market interactions are quite complex and only recently have we started to digitize and make efficient many of these market interactions, which is why the platform model is becoming much more important now.

What are the key ingredients of a successful platform?

There are three key ingredients of a successful platform. I refer to these three in my first book Platform Scale, where I talk about the platform stack. These three ingredients are: 1. the infrastructure that the platform provides, along with the governance model; 2. the data that the platform collects; and 3. and the network of participants and the interactions that get created around the platform. These are the three ingredients of a successful platform. The infrastructure and governance model is provided by the platform itself. Following this, the network of interacting parties starts coalescing around the platform, which collects data and uses this data to make the interactions more efficient. This works in a self-reinforcing model where more participation leads to more data, which in turn leads to a stronger governance mechanism, leading to further participation.

What are the benefits of a successful platform?

There are many benefits of a successful platform.

First, a successful platform makes the market much more efficient. In fragmented and opaque markets, it is difficult to search for different options. The platform, by aggregating all options, makes the market much more efficient.

Second, platforms drive transparency by creating a reputation layer for the market. Yelp and TripAdvisor are platforms that created transparency around the quality of restaurants and hotels in their respective markets and simplified consumer decision making.

Third, in a market with an inefficient gatekeeper , a platform comes in and re-intermediates that market more efficiently. A great example of this is the publishing industry, where Amazon came in and made the publishing industry more favorable to authors.

A fourth way in which a successful platform creates new benefits is by enabling users to produce for the first time; it converts non-producers to producers by virtue of the fact that it provides them with special tools for production and it also gives them access to a market. Uber allows people to become drivers for the first time. Airbnb allows people to host a B&B for the first time because now they have access to a market for their service.

The final benefit of a successful platform is that it can potentially create an entirely new production paradigm. Wikipedia created a new model of production, where the writing, the editing and the approval all happens on top of a platform versus the traditional linear model of publishing. With the rise of new coordination technologies and distributed governance models, like blockchain, we may see many more examples of production models shifting from traditional linear models to new platform enabled models.

Over the last few years, I’ve worked with clients across industries to design platforms that unlock these benefits. I’ve designed platforms that make upstream supply chains much more transparent because of the sheer volume of data captured and assign reputations for participants in the supply chain. I’ve looked at building patient-centric ecosystems that shift power away from gatekeepers in the healthcare industry and move it towards patients. I’ve also architected many alternate labor and resource markets in different industries that create the efficiencies that I mention above and often allow small emerging companies in these industries to scale rapidly without reliance on traditional gatekeepers. Of late, I’ve been focusing a lot on building B2B platforms, not your typical Ubers and Airbnbs, but platforms that require alliances among large businesses, require the creation of industry standards and involve a whole range of complex coordination that one doesn’t find in B2C markets. All the efficiencies mentioned above are now coming into B2B markets as well.

It seems that there is platform thinking and platform implementation. Can you distill the two for me?

Platform thinking is about taking the right decisions about ecosystem architecture, incentives, governance, and ensuring that the whole system is properly architected and governed. Platform implementation then involves applying these various elements into actual implementation. It is the creation of the ecosystem architecture — the laying out of the governance mechanisms - understanding how network effects work, and how to lay out the factors that will increase network effects. These are the critical elements that are very different in the case of platforms.

When I advise on platform implementations, I start by creating an overall governing architecture for the ecosystem. Once this architecture is created, the key pressure points in the architecture can be identified to determine strengths and weaknesses of different ecosystem players. This, in turn, helps us determine where value is created and where it can be captured. Executing without such an architecture can lead to a lack of coordination in execution efforts, which in turn, can kill the platform.

What are some prominent examples of platform revolution?

There are many examples of the platform revolution that we see today. I would clump them broadly into three categories.

The first is industries, which are highly information intensive that have been impacted by platform revolution. Media, for example, has gone from traditional pipeline models to platform models. Telecom has moved from linear models of traditional handset manufacturers to platform models of Apple and Android. Professional services recruitment is moving from linear models of traditional recruitment agencies, and the agency model of service provisioning, to new kinds of marketplaces.

The second group of industries are the more regulated industries of banking, healthcare and education, where platform models are only now coming into play. Insurance is moving into platform enabled models. Banking is being challenged by peer-to-peer marketplaces, as well. And with new forms of markets being created in banking, we are seeing new kinds of data being gathered to determine who should get a loan, who should be funded, and what kind of a premium should be offered to a certain person. These are all being made possible because of platforms. Healthcare is a prime example where the platform revolution is beginning to take hold. Patient-centric ecosystems are being created, where entire platforms are centered around solving for the patient and creating a whole ecosystem of service providers to provide solutions to the patient. Forther upstream in B2B health care, platform-centered models are creating transparency across the whole healthcare industry.

We are also seeing a third group of industries, where the platform revolution is beginning to take hold. This is in heavy industry where platforms are gradually taking shape and because these industries are becoming digitized (largely because of sensors). GE, Siemens, Bosch, Caterpillar are some examples of companies that are building platforms in these industries.

In your book, you write: “Incumbent companies can fight back against platform-driven disruption by studying their own industries through a platform lens and beginning to build their own value-creating ecosystems, as Nike and GE are doing.” What do you mean by this? Is there a recommended strategy on how to recognize new upstarts when crafting a platform strategy? For example, Siemens and Honeywell know how to compete against each other but must now compete with Google’s Nest. How does a Siemens and Honeywell recognize potential new segment entrants using platform revolution thinking? Or, even new opportunities to develop an ecosystem? I ask because I am sure executives in the hotel industry never thought people would feel comfortable renting out rooms in their houses to random strangers.

1. How Can Incumbent Companies Fight Back

First of all, incumbent industries can fight back by studying their own industry through a platform lens. Platforms enter an industry when the critical elements of decision making or the elements of supply and demand get digitized. Transportation moved to platform based models when the location of a car became digitized because of a smartphone. A platform like Airbnb came up when identity and trust became digitized. These are examples of critical elements which once digitized, lead to the creation of a platform model. Incumbent companies can look to understand what kinds of factors are being impacted by the forces of digitization and accordingly determine what kinds of platform opportunities are possible in a particular industry.

In banking, a new platform for real estate loans would digitize a user’s journey in purchasing a house and then determine the point in the journey and the level of creditworthiness that user has to connect that user with a loan.

In heavy industry and manufacturing, a lot of elements are getting digitised thanks to sensors. GE is trying to digitize the working of a machine, so that decisions can be taken and the interactions between machines-and-machines with machines-and-humans can be coordinated through a platform. That’s another example of looking for digitization in your industry and then finding a platform opportunity over there.

In my work with incumbents, I primarily focus on mapping out the ecosystem flows and understanding points at which digitization could restructure these flows and the ensuing decisions that various actors take. Understanding the impact of data on shaping the flow of goods, services, and money, and the decisions related to these flows is the first step towards digital business model transformation for any incumbent.

2. How to Identify New Platform Entrants

One way to look for potential new entrants is to look at the lower end of your industry, which you would not think of as your competition, where quality is not a key criterion. Look at new models emerging over there. If a model gains hold in that segment, and if it can develop a strong curation system over time, then it can move upstream.

When Airbnb started it was just a way for people to share their rooms and mattresses. Today, it can compete with large hotels because it had a strong curation system that helped it to keep moving upstream. We are seeing something similar happening in the finance world today, where risky transactions are happening on peer-to-peer platforms, but as they gain greater data these platforms will be in a place to make better decisions and on-board more mainstream transactions, as well. We are seeing some of this happening in healthcare, as well, where a lot of wellness platforms are still being used only by early adopters. But as these platforms gain a stronghold and as they learn more from data, they will start moving into more mainstream use cases in healthcare , including cure. Look for use cases that are not mainstream and are often associated with low quality. See if those use cases are gaining hold because with enough data and enough usage, these use cases can benefit from curation and move towards better quality and then start competing with the incumbents eventually. This is how one would look for new platform opportunities in any industry.

What learnings and lessons can governments learn from the leading (for-profit) platform innovators? Such as Airbnb and Uber?

First and foremost, platform innovators are organized to innovate very nimbly around their core. Platform companies have a very strong core built around data, machine learning, and a central infrastructure. But they rapidly innovate around it to try and test new things in the market and that helps them open themselves for further innovation in the ecosystem. Governments can learn to become more modular and more agile, the way platform companies are. Modularity in architecture is a very fundamental part of being a platform company; both in terms of your organizational architecture, as well as your business model architecture.

The second thing that governments can learn from a platform company is that successful platform companies are created with intent. They are not created by just opening out what you have available. If you look at the current approach of applying platform thinking in government, a common approach is just to take data and open it out to the world. However, successful platform companies first create a shaping strategy to shape-out and craft a direction of vision for the ecosystem in terms of what they can achieve by being on the platform. They then provision the right tools and services that serve the vision to enable success for the ecosystem[1] . And only then do they open up their infrastructure. It’s really important that you craft the right shaping strategy and use that to define the rights tools and services before you start pursuing a platform implementation.

In my work with governments, I regularly find myself stressing the importance of thinking as a market maker rather than as a service provider. Governments have always been market makers but when it comes to technology, they often take the service provider approach.

In your book, you used San Francisco City Government and as examples of infusing platform thinking in government. But what are some global examples of governments, countries infusing platform thinking around the world?

One of the best examples is from my home country Singapore, which has been at the forefront of converting the nation into a platform. It has now been pursuing platform strategy both overall as a nation by building a smart nation platform, and also within verticals. If you look particularly at mobility and transportation, it has worked to create a central core platform and then build greater autonomy around how mobility and transportation works in the country. Other good examples of governments applying this are Dubai, South Korea, Barcelona; they are all countries and cities that have applied the concept of platforms very well to create a smart nation platform. India is another example that is applying platform thinking with the creation of the India stack, though the implementation could benefit from better platform governance structures and a more open regulation around participation.

In your book you also said industries that are information-intensive are most prone to platform disruption; whereas, conversely, highly regulated industries are less likely to be transformed by platform thinking. Many global governments, however, are information-intensive and are also highly regulated. Is platform thinking best applied to developing countries? How can platform thinking help developing countries?

Developing countries have a unique opportunity to apply platform thinking for a variety of reasons. In many developing countries, the legacy systems have been so bad that it’s been very difficult to offer basic services, like financial inclusion using those legacy systems. Hence, there’s an opportunity for technology to create an alternate infrastructure independent of legacy systems. The India stack is a good example of creating an alternate infrastructure for becoming a platform. Similar examples exist in Africa. For instance an initiative like M-Pesa has created an alternative payments’ infrastructure, while piggybacking on the existing Hawala network of payments. These are all examples of applying platform thinking to developing countries.

But focusing only on technology compatibility issues misses the point. I’ve worked on designing smart city platforms for large cities in developing parts of the world. In many of these instances, rewiring legacy systems is a smaller issue than rewiring the mental models of key stakeholders.

The trend in government is to build an ecosystem of development in which citizen developers help their governments. For example, West Sacramento Mayor announced how he was working with local innovators to develop a Tinder-like app for citizens to express their like or dislike of city services. But some states are creating internal platforms that are language agnostic. For example, California developed an innovation portal for internal employees to have a sandbox to develop new ideas. Evidently, there’s an internal platform and external platform revolution taking place in government. How does government as a platform (GaaP) fit into the platform revolution? And, what advice would you give to large IT vendors looking to capitalize on this new platform revolution in government?

Thinking about government-as-a-platform, I think of three different models:

The first model involves creating an innovation sandbox where governments look at existing data and open it to enable external innovation. This form of approach has historically been more opportunistic than strategic. Look at what data you have and open it out to an ecosystem.

A second model that is slightly more market-centric but still doesn’t leverage platform thinking. In this model, governments transform specific verticals. Mobility is a common vertical that governments want to transform because there is significant user pain around mobility and transportation. Healthcare and Energy are examples of other such verticals. We have many examples of governments doing platform initiatives in silos within these verticals. Even though this involves bringing together a vast range of stakeholders to solve that problem, you’re still operating in silos. Eventually, you create these many different platforms that don’t talk to each other.

The third way of doing it is a platform-centric model: Where you create a central platform and then start launching these initiatives off the central platform. You may create a central platform for the whole nation (government or city) and then start a mobility initiative on top of that. As you get data from the mobility initiative, say, data about traffic - you can connect it with data about real estate to understand what parking optimization should be done. Once you have data about real estate and about how buildings are using energy, you can connect that to data about the grid to see how buildings can interact with the grid to optimize the use of energy. The right way to apply platform thinking is to ensure that the various initiatives that you are “platformizing” are all interacting with each other and not operating in silos.

It seems there’s always a chicken-before-egg problem in government, especially due to the funding mechanisms, even though CMS and the White House Office of Social Innovation fund some innovation projects that are seemingly scalable. Out of the eight proven chicken-before-egg platform strategies talked about in your book, which one best applies to governments?

With governments, solving the chicken-and-egg problem is best achieved by ensuring that the ecosystem believes that the government is fully committed to the platform. This in turn is achieved though a few mechanisms. First, you can start with a marquee player coming on board and kickstarting the platform. Alternately, the government assigns a very deliberate source of funds for the success of the ecosystem so that the ecosystem can participate. External innovators can participate on the platform with the guarantee that they will get outcomes from participating on the platform. And finally, ensure that there is a very compelling use case that is created by the government and by its initial partners before you start opening it up to the larger ecosystem because nothing is more discouraging than being on a platform that is not being consumed. And so creating that initial use case is critical.

Again, thinking back on my work building smart city platforms for governments, I’ve always seen creation of the initial use case as being critical to the long-term success of the platform. In Chicago, the initial use case was the smart grid. In Singapore, it was transportation. In the Middle East, it may well be irrigation. A successful use case early on is critical for solving the chicken and egg problem.

As a tech entrepreneur, I remember reading about the varying types of startup business models. I attended numerous lectures on the Uber business models. What new business models will emerge in the platform revolution? And, why does the construction of that business model require a new canvas design? [Note: I saw your business model construction on platforms.]

When we think of business models - in a world of pipelines, business models are very product-centric. In a world of platforms, business models and market-centric. Let me explain that a bit.

Linear pipeline business models typically vary two or three things. They vary the quality of the product that is created; the process through which the product is created, and the experience the customer gets on using the product. That’s been the dominant way of thinking about business models in the case of pipelines.

When we move to platforms, we start thinking of business models along different variables. We now start thinking in terms of how the market is organized because platforms organize markets. We now start thinking about what makes a particular market more efficient. What are the factors that make that market more efficient. Business models emerge around those efficiencies.

As an example, Craigslist allowed buyers and sellers to interact with each other, but Airbnb created the trust and insurance components, internalized the payments and created the reputation system, which together created a new business model. The business model centers around factors that make market interactions more efficient. The kinds of business models that we end up looking at will depend on the kinds of interactions we’re looking at. For commercial interactions, business models monetize the transaction cut. When curating one-side of the market and guaranteeing high-quality supply, the business model may requires paymen to access that supply. When we look at a market where there is no commercial transaction but where the two-sides value access to each other, — for example, one side might want to influence the other side — the business model may involve charging for access to the market. Depending on how markets are organized, new kinds of business models will emerge and that is the fundamental difference when we move from a pipeline model to a platform-based model.

In the private sector, consumers are often the buyers. The relationship between producers and consumers is not always a 1-to-1 relationship, especially in the advertising and government sectors. For example, the buyer is not always the consumer (and /or user) of the service or product. In my opinion, what is most hard is for vendors, creators, and GovTech entrepreneurs to design an interaction in which the consumer is not the buyer, especially when you don’t have access to the consumer (i.e. someone in prison). So any recommendations on how government platform creators should construct a producer-to-consumer platform interaction when the consumer is not a buyer?

I’ve experienced this first hand while designing new business models, especially in highly regulated industries that are resistant to such innovation. While designing a new data-driven business model in energy, healthcare or financial services, you impact an entire system of stakeholders and policy makers. Ecosystem architecture is, again, a very handy tool to resolve issues of systemic impact. When you draw out the relationships and flows between different ecosystem actors, you can run simulations to illustrate the design of the ecosystem in the old business model and the impact on various actors and flows after the new business model comes in. Ecosystem architecture and modeling is the single most important powerful tool here. Just using business model canvases is not going to help. Canvases are static whereas ecosystems are dynamic so mapping out the actors and flows and running simulations of their behavior is critical to forecasting platform impact and designing new business models.

Entrepreneurs often hear: “Go build a product in a blue ocean market, not a saturate (red ocean) market.” But we’re seeing the design of new business models that are disrupting traditional businesses. Will a platform strategy (and business model) enable the disruption of any of industry, even if it is nascent or mature?

When we think of this in terms of platforms, what we often see is that platforms do not necessarily deviate from the idea of blue oceans and red oceans. They actually reinforce that idea. Even if an industry is mature, there might be underserved markets within that industry. By penetrating those blue ocean markets and then strengthening the feedback loop, the platform is able to move into an eventual red ocean market. Let’s take a few examples.

Youtube started in amateur video and created a feedback loop that allowed the community to vote on the quality of the video. It was able to move up the chain into more professional video and started disrupting media houses and traditional television to some extent.

Take Airbnb as an example. The hotel and accommodation industry already existed, but there was an underserved portion of the market, both from a supply side and even from a demand side. When Airbnb created the right reputation and insurance models that fostered trust and quality control, they were able to move up the chain.

Platforms that disrupt traditional businesses do not compete headlong with the traditional business. They start with a blue ocean market within that industry, which is usually an underserved lower end of the market. Once they have successfully penetrated that, they train their feedback loop and curation model, which then allows them to move upstream into the red ocean market and disrupt the traditional incumbents.

Blockchain is an emerging technology that everyone is talking about, even the federal government and cosmetics industries. It seems that blockchain furthers the platform revolution. Everyone keeps talking about the difficulties of monetizing the blockchain, but it seems a platform (and ecosystem) model might be a great way for monetization moving forward. How does blockchain fit into the new platform revolution?

Blockchain is a peek into the next version of where business design might move. Every business has a production function and a governance function. In the world of pipelines and traditional hierarchical business organizations, both the production and the governance were centralized. You produced in a factory and operated a hierarchical organization. With platforms, the production became decentralized but the governance is still centralized. All platforms today are still governed by a central organization; whether it’s Facebook, Google, Airbnb, Uber, all of them have a central company governing the platform. What will change with blockchain is that not only will the production become decentralized, but we will also have governance becoming decentralized. Today's platforms used a decentralized production model to disrupt a centralized production model. The next generation of platforms will use a decentralized governance model to challenge the centralized governance model.

In the tech world, we’re starting to see Everything-as-a-Service. This started with Software-as-a-service (SaaS) but now has expanded to include: marketing-as-a-service, healthcare-as-a-service, infrastructure-as-a-service, disaster record-as-a-service, and now platform-as-a-service. How will this trend everything-as-a-service, in your opinion, influence platform revolution?

The reason we see everything-as-a-service is because of the cloud. You don’t need to set up the entire infrastructure, you can access it all with the cloud. The cloud in itself is the central infrastructure that allows platforms to work.

The platform revolution is offering everything-as-a-service to both sides, not just to consumers but also to producers. Think of a driver on Uber, he is able to log into the central infrastructure and gain access to business opportunities. In the past, he would have had to work within a certain organization in order to get access to business.

The most successful platforms will always appear to their ecosystem as a service whether its the producer side or the consumer side. There are certain platforms that require the ecosystem to build on top of themselves and they do not appear as a service. If you think of Android, where an app developer has to build specifically for Android, it’s a very hosted kind of experience. But in most platforms today, which gain rapid adoption, both the producer side and the consumer side interact with the platform on a service based model and that will increasingly become more important because the idea of converting something to a service changes not just the pricing model and hence the friction of coming on-board, but also changes the way the central infrastructure interacts with the user, where the experience constantly gets shaped because of the data that is coming in and the way the service is personalizing itself for the user.

What is the dark side of the online platform revolution? Essentially, what are strategy trade-offs? Beyond someone ransacking a house on Airbnb or kidnapping someone in an Uber. For example, I noticed in your HBR article, Pipelines, Platforms, and the New Rules of Strategy, you used the retail industry as an early example of platforms. We’re starting to see traditional brick-and-mortar stores close. Now, property owners are going to have to renegotiate with their stores (producers) due to the lack of (consumer) foot traffic that will result from the closure of big box stores (i.e. Macy’s). It seems as if they are dependencies that are naturally created as a result of building a platform. Are those dependencies the dark side?

There are many dark sides to the platform revolution, all of which stem from the fact that today’s platforms have the unenviable tension of having decentralized production but centralized governance. Whenever you have this conflict of decentralized production and centralized governance, you will have a conflict of interest because the actor governing the platform may take decisions which may not work in the favor of the producers of the ecosystem producing on the platform. In general, the governance and the production need to go hand-in-hand because the governance needs to be structured in a way that the production is encouraged.

Airbnb, for example, creates good policies for hosts so that they are encouraged to come on-board. But there are some cases where the governance goes at odds with the production. Amazon is a producer on its platform and also sets the rules of governance for its marketplace, and so there’s a conflict of interest. Whenever a merchant on Amazon starts competing with Amazon as a producer and that merchant is selling something that is valuable, there’s a conflict of interest there. Amazon has been known to acquire and organically push out merchants to get into certain profitable categories.

Meerkat, the live video platform, gained a lot of traction on Twitter before Twitter cut it’s life out and acquired its cheaper competitor Periscope instead. There was a conflict of interest again. The dark side of the platform revolution is very often about this conflict of interest, where the governance of the platform is at odds with the incentives that the producers need on the platform.

I am moving the future direction of my work to explore the dark side of the platform economy better. I’ve been working with foundations and non-profits, as well as with the WEF to explore and lay out how platforms can be architected for large scale social good. At the same time, I’ve been working with labor unions to help them understand the future of work in a platform world and the problems of over-dependence. I’ve also been advising policy makers on how to rethink policies around property (who owns what), liability (who is liable for what), and value capture (who monetizes what) in a world of platforms. The distribution of risks and rewards are difficult to trace in complex ecosystems. There is much that needs to be done to understand the dark side of platforms and regulate them better

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