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Blockchain Product-Market Fit: Re-framing the Harvard model

As the interest in blockchain continues to grow and more companies, product managers, investors and the like try to find their footing in the market, key questions that need answered are where the industry is trending, how far will the technology will take us. One reference is the Harvard Business Review model (complete reference article here), which analyzes blockchain adoption along two dimensions of use cases — degree of novelty and amount of complexity. The adoption is said to evolve over 4 phases, as shown in the quadrants, drawing upon the evolution of the internet as a basis for modeling the blockchain technology diffusion. With so many of us needing a solid method to assess Product-Market Fit for blockchain, and help in hypothesizing and thinking through market needs and development priorities, the question arises if this Harvard model is actually a good reference? Or, will we miss focusing on the right things or worse, will we be blindsided as we go about architecting what we think is the blockchain business and its future?

How does the Harvard Model fall short?

The Harvard model (diagram A) does provide a good context by using the internet and TCP/IP models of technology adoption. It also does recognize blockchain adoption could be influenced by and, or, run into slow-moving organizational systems and barriers.

But, the Harvard model falls short in at least five areas, leaving us to look for another tool to better assess how blockchain transformation is going to happen.

The Five Weaknesses of the Harvard model:

1. Ignores the “platform” effect, assuming instead a somewhat linear pipe-like progression through use cases tackling novelty and complexity. While these are two key dimensions, network effects is a fundamental driver of adoption and scaling. Especially for open-source projects, like blockchain.
2. Ignores the community and the value creation from interactions among the blockchain community members, which form a positive feedback loop to further strengthen the appeal of the platform.
3. Ignores the “disruptive” value of blockchain. In fact, the Harvard model rejects the disruptive effects, stating “That’s because blockchain is not a ‘disruptive’ technology, which can attack a traditional business model with a lower-cost solution and overtake incumbent firms quickly.” This completely misses the point when we know blockchain in fact can reduce costs by removing intermediaries, can target new consumers (disadvantaged groups, unbanked etc.), and drive operational costs down by automated, trustless (ie., without expensive centralized institutions) enforcement of digital assets, regulatory and contractual compliance and security.
4. Ignores the concept of “whole” product that Geoffrey Moore identified as a key driver in his seminal work on technology diffusion. We will look at this from some contemporary empirical examples and discuss how they do apply to blockchain products in follow-up articles.
5. Underestimates the true transformative effects by pegging “smart contracts” as the ceiling in its transformative example. The truly transformative blockchain projects will likely use smart contracts merely as baseline building blocks and the full effects of blockchain will be far more fundamentally transformative. New yet-to-be conceived business models and business categories will spring up in blockchain a la ride-sharing, gig economy, and social media businesses that evolved from the transformative platformization of the internet. If digitizing of assets was the core of the internet that triggered such economic changes, smart contracts at the core of this new platform will unpack even more interesting economic milestones.

Adoption Challenges for Blockchain

The reality is there are adoption challenges for blockchain, and the prevailing thesis is we are stuck at the chasm (diagram B). We need a mechanism, a framework to help us understand how to approach the Product-Market fit that would help us cross this chasm. This is not a theoretical pursuit as much as a method for a hard-nosed approach to frame the challenges correctly, understand business history for the right lessons, and deploy the right levers to accelerate usage.

There is a lot of development going on in this industry, and some of these do follow such overlapping lines that a shakeout may be inevitable. So, we do need to get past the “early adopters” — arguably bitcoin and other concept trials in the industry today are proof points for “early adopters” — and design the right market models that will interest the “pragmatists” so we could converge on networks and protocols that will survive the market tests with the right economic models to rapidly cross the chasm and grow.

These will take a lot of trials, experiments and a lot of building of high-impact “killer” use cases and applications. Which brings us to the need for the right framework to drive the Product-Market fit for the blockchain ecosystem.

The Platform-Ecosystem Fit Model for Blockchain Adoption

What is proposed is a new model (diagram C) that reframes the Harvard model and addresses the weaknesses previously discussed. I have retained the use cases, or adapted them rather, on the vertical axes, but added an entirely new dimension, calling it “stages of adoptions” on the horizontal axis. This axis starts with the developers, then adds the industry-vertical communities they belong to and eventually, the entire industry ecosystem as a whole.

Doing this allows the model to deliberately treat blockchain as a multi-sided technology infrastructure platform where there are contributors and consumers of technology. Here, the user adoption and use-cases adoption progress initially within various sub-ecosystems, with active community participations via open source tools and forums, before unpacking even more synergies in the wider ecosystem as a whole. The “interactions,” can well be among each other and not only with the platform, as open-source GitHubs tend to see a lot of cross pollination of both ideas and tech. We can think of these interactions being a key currency indicating the “richness” of the ecosystem and a measure of overall platform innovation adoption. And we immediately see there are advantages to being able to instigate interactions by seeding the ecosystem with let’s hypothetically say cryptographic primitives, or other such building blocks, and open up access and discussions among the community on their applications and usefulness. This helps in accelerating further interactions and reinforces positive behavior and drive product fit. Modeling these interactions and factoring in community events yield a better sense for the adoption curve of the platform in the ecosystem. Hence the name of the framework “Platform-Ecosystem Fit model.”

Adoption by developers is the critical first step to seed more proofs of concepts and build confidence among this vital group. I call these initial use cases “confirmation” use cases as these are essentially carried out to understand the development efforts and challenges, and the technology capabilities. These are foundational to being able to move up toward “substitution” use cases, where current technologies may be substituted by use of blockchain in use cases similar to or mirroring current deployments. Examples may be database applications that need some level of immutability or public accessibility (decentralization) and therefore may now be substituted by a blockchain application. And so on, eventually leading to the more transformative models.

In this version of the framework, I lay out three radial zones of market maturity, yellow being the least transformative, and green being the most transformative. Obviously this is a framework that can be adapted and versioned as needed. I use arcs to denote the zones allowing for fluid interactions and to recognize these are somewhat free flowing “zones” of work as opposed to rigid quadrants of linear progression. The arcs are not to be considered as rigid divisions but rather a threshold for attaining certain critical mass of maturity at each zone before being able to move the chain, pun intended, up the market. For example, the supply chain community could define the number of MVPs or POCs whilst in yellow zone; and while in the blue zone, set the minimum number of deployments or other KPIs with defined “standardization” needed for participants being able to work within the community before opening up to other communities (in the blue zone still) or becoming part of a wider, more transformative ecosystem in the green zone.

As we move diagonally across the maturity curves, up along the vector labeled “trajectory of maturity,” we progressively unlock the product-market fit for blockchain as both the developer community and the use cases mature in sophistication, depth and variety. As well as, in range of use cases and the extent of engagement these have — be it at developer level, at the vertical community level, or the entire industry. The length of the vector could vary for different industries and, or, applications within an industry, which in turn dictates the time to cross the chasm ie., attain product-market fit

We are, as an industry, in the yellow zone, and there are some early experimental efforts to begin poking into the next blue layer of maturity. There are many, many verticals in the blue zone, two of them are shown here as examples, being formed daily with a lot of focus on standards and identification of key use cases and sometimes very vertically oriented development approaches. We are really far from defining definitive use cases for the green layer. However, the kinds of transformational use cases being painted today by many blockchain visionaries are critical to inform and accelerate the overall platform, the technology and the entire ecosystem.

The interesting leverage a product marketer gets through this Platform-Ecosystem Fit model is in seeing the interplay between the use cases and degree of engagement that needs to be driven within the developer community. This forces the melding of business models and real value-yielding applications with active engagement within the community that need to build and validate them. At each stage of adoption, or level of use case sophistication, there is a certain degree of product-market fit or the teams fail fast and re-boot. As we develop and break through these individual product-market fit applicable to different levels of use cases and different developer and vertical communities, we push the innovation diffusion process forward.

In follow up articles, we will develop the theme further. Keep a lookout for additional discussions including:

• On boarding the developers, the first step in market validation for blockchain.
• What is the blockchain “whole product:” or how does Geoffrey Moore’s model apply to blockchain “products?”. Examples from industry.
• Building the vertical communities and the idea of marketplace economics of primitives.

Key Readings: :

1. Six Keys to Building New Markets by Unleashing Disruptive Innovation (Clayton M. Christensen, Harvard Business School)
2. How blockchain technology will impact digital economy, (Christian Catalini, MIT)
3. Pipes to Platforms readings & MIT Platform Strategy Summit 2015 (Sangeet Paul Choudary)
4. The Synergies Gained from Building on Ethereum’s Decentralized App Ecosystem (Preethi Kasireddy)
5. Platforms Revolution (Geoffrey Parker, Marshall Van Alstyne, and Sangeet Paul Choudary)