Picture this scene in “The Social Network” film by David Fincher. After getting back from the Bill Gates lecture at Harvard, Mark Zuckerberg and Eduardo Saverin engaged in this conversation:
EDUARDO “I said it’s time to monetize the site.”
MARK “What does that mean?”
EDUARDO “It means it’s time for the website to generate revenue.”
MARK “I know what the word means. I’m asking how do you want to do it?”
EDUARDO “Advertising. We’ve got 4000 members.”
MARK “Cause theFacebook is cool. If we start installing pop-ups for Mountain Dew it’s not gonna be cool.”
EDUARDO “I’m talking as the business end of the company…the site…”
MARK “We don’t even know what it is yet. We don’t know what it is, we don’t know what it can be, we don’t know what it will be. We know that it’s cool, that is a priceless asset I’m not giving it up.”
EDUARDO “When will it be finished?”
MARK “It won’t be finished, that’s the point. The way fashion’s never finished.”
EDUARDO “You’re talking about fashion? Really? You?”
MARK “I’m talking about the idea of it and I’m saying it’s never finished.”
This dialogue expresses opposing views on some of the most fundamental questions related to platforms. While wanted to explore the possibilities offered by an emergent social network growing at an exponential pace, Eduardo preferred to pursue the most visible alternatives to monetization, even if, at some point, those choices might put Facebook coolness perception at risk. More than 15 years after the original dialogue and Facebook success in many forms beyond the pure social network scope, these questions still challenge entrepreneurs, investors, and managers.
Platforms are the engines of a significant economic transformation. They hold the keys to extend the benefits of large-scale innovation to an increasing number of people. But we still need to learn to harness their development to deliver the considerable impact they promise. By embracing an experimentation mindset, individuals and companies can explore the many exciting possibilities offered in this context of increasing innovation and technological complexity.
Platforms are the business archetype from the digital age. Seven of the world’s ten most valuable companies are platform businesses. Via creating virtual communities over a shared technological infrastructure, platforms can explore and combine interests from different participants in unexpected ways. As a consequence, platforms impact our society in many other areas beyond the business or technology realms. By helping scientists develop vaccines for the current and future pandemics, reshaping the media landscape (with the emergence of independent producers), or matching people into new relationships, platforms will continue to produce many innovations for the years to come. However, as successful as platforms continue to be, we can also observe many unanswered questions about their potential. These are emergent challenges with no clear answer in sight. With this perspective in mind, I intend to share some of the learnings I collected along with my career managing platform-based businesses in different markets and stages of development.
Part of the challenge is that much of our conventional managerial wisdom has limited applicability to this weird (but also fascinating) new world. Industrial age frameworks, such as the 4Ps and the BCG matrix, were influential in stripping down to the most relevant details of managerial decision-making. Organization structures in BUs allowed for the focus and clarity of capital allocations on large and somewhat predictable businesses over long periods. This type of business thinking gave us excellent and cheap consumer products such as diapers, cars, TVs, and so many others. However, in the last years, technology passed a tipping point, where we can no longer fully predict or anticipate all its potential outcomes or developments. Ubiquitous digital devices and cheap computing power increased interconnectedness, expanding the space of possibilities offered by technology. As a result of the changing landscape, our traditional conceptual tools fail to address the platforms’ dilemmas. In some sense, innovation’s messy and uncertain realities confront our desire for the superficial predictability gained during the business cycles of the 20th century.
As the space of possibilities created by technological innovation unfolds exponentially, the critical challenge remains to incorporate novelty into the changing fabric of society. While this process provides and maintains an excellent experience for potential partners, platform growth occurs by exploring different adaptive responses to an unpredictable environment. This tendency is apparent in the changing nature of education platforms. A decade ago, Content was the main product for universities and other players. However, as institutions expanded their online ventures, Content became cheap and abundant. Over time, we have observed the emergence of several education platforms incorporating new elements of teaching solutions and resources, such as Knewtown adaptive tutors, Coursera MOOCs, and Canvas learnings management systems. As the world continues to change in unexpected ways during and uncertainty after COVID, the need for constant adaptation will continue to be a significant factor in defining the future viable solutions and their respective monetization alternatives.
This trend is also visible on many other types of platforms. In media and advertising, companies went from businesses based on ads to multiple monetization sources, including courses, subscriptions, and others. On gaming, Candy Crush Saga monetization evolved from a marketplace, selling powerups, extra lives, unlimited lives, to a unique currency (the famous gold bars) and bundles as additional revenue streams. Successful platforms show deliberate risk-taking to build the responses to broader context changes and the resulting creation of monetization options over time.
In contrast, it is common to see platform strategy discussion based upon large addressable markets, optimistic (and often unrealistic) timeframes to monetization, and idealized product roadmaps. By conditioning the platform development to preconceived growth patterns, managers and investors restrict the necessary risk-taking and experimentation. Over the long run, tinkering is essential to create adaptive responses to the changing environment and their corresponding future options for monetization (which might lie outside of those initially established expectations).
As the path to growth and monetization on platforms is often uncertain and unpredictable, the management of platforms depends on understanding some leading questions over different timeframes. In the short term, developers should address the individual experimentation on each side. Second, product roadmaps should include the combination of successful experiments into coherent product proposals covering. Over the long term, alternative paths of areas monetization emerge as a consequence of the previous experimentation and variety into flexible product roadmaps. By tackling these questions, managers can uncover the intermediate stepping stones that lead to the most promising monetization paths at scale.
As the landscape shifts and changes, it is crucial to communicate that the roadmaps do not deliver a fixed blueprint. They serve as guiding structures defined by the designer but are subject to feedback from users and developers. The validity of the roadmap depends on the designer’s ability to keep it open to change. Hence, the quote from Mark Zuckerberg about Facebook never being finished.
The resulting discovery process is far from the structured order we might have learned to have on stable and predictable industrial businesses. Rather than a top-down process proposed from the designer perspective, the approach requires a step-by-step adaptation of the MVPs (most viable products) according to the execution feedback and user engagement patterns. This process allows the execution teams to capture and incorporate different drivers of complexity not observed at the design phase while also responding to the various contextual changes occurring over the development cycle.
This pattern of platform development via bottom-up or emergent designs is similar to that observed in the creation of cities or communities. The resulting landscape may be different from the initial plan. Still, the unfolding result presents a richer and more surprising set of promising alternatives for growth. Alternative approaches conditioned by a fixed development roadmap with top-down control may look like the standardized architecture of former socialist countries — logic and orderly but disconnected from their surroundings. A single course can never match the creativity of a thriving ecosystem of partners combining their abilities to their surrounding context.
Managing even a simple platform using traditional organization practices can be challenging. Under a high degree of interdependence, a single intervention causes a chain of unexpected effects on different and seemingly distant areas. For example, looking at the 2-side hiring platforms. Adjustments in job ad placements translate into first-order results for Hirers in improved hirer engagement with the ads and later number of ads placed. The chain of the impact cascades over to the candidate side as well. Higher Hirer engagement on ads drives more frequent interactions with prospective candidates, fueling candidate satisfaction and future engagement with the platform. A growing platform business (content, education, hiring, and others) consists of individually inefficient but interdependent functions.
However, our incentive schemes tend to focus only on the immediately measurable results linked to the most apparent effects on a single side of the platform (in this case, the hirer side). By relegating the aggregated platform performance to a secondary place or limiting the performance metrics to the most visible effects in the short term, companies restrict teams’ ability to adapt and coordinate their answers to a broader range of signals coming from markets and users.
To address this issue, Rory Sutherland suggests changing the incentives: “I think having two budgets, two sets of metrics, and two sets of incentives for exploit and explore. It would be utterly insane to learn something in a test and fail to exploit it by doing more of it. Make the most of what you know, but always invest twenty percent in what you don’t know yet.”
Platforms are unique in enabling the creation and sustaining of these innovation ecosystems at scale. Much more than any particular lessons or best practices to be inferred from experience, what is truly important is to approach the possibilities offered by the increasing role of technology in our lives. The answers to these questions lie not on a fixed analytical approach but acknowledging our limited understanding of the rising complexity we live in and actively exploring the options that might contribute to a better and often unexpected future.