The Three Pillars of a Distributed Ledger Technology ("Blockchain") Enterprise Use Case

Blockchain is often called a "better mouse trap" for transaction management - but the "best mouse traps" don't have to be traps at all - and the cheese can be peacefully shared if the setup is right.

There's some confusion on whether distributed ledger technology (DLT, to which I refer for enterprise blockchains vs. broader cyrpto/public blockchains) is appropriate for a given scenario. There's also a ton of different decision frameworks addressing this same question, and articles on public vs. private ecosystems, using a traditional database, etc. I've found that three "pillars" tend to be true for an enterprise DLT use case that's worth standing up at a high level.

Pillar 1: Multiparty ecosystems with common goals but differing incentives

e.g. Walmart, Kroger, Tysons, and other suppliers all want to provide healthy chicken to the market, but compete & negotiate with each other – DLT works there.

Note that the parties don't have to be separate companies - are your HR, finance, marketing, sales, services, engineering, and management teams always perfectly aligned ?

Pillar 2: Regulated activities with well-defined boundary conditions

e.g. Blocksure focuses on insurance back-office payments & premium management.

Same applies to bills of lading, food handling regulations, and other supply chain rules in the chicken example above.

Pillar 3: Actionable shared data

e.g. a recent pilot of 300 banks on the R3 system had success in sharing Know Your Customer data.

Data that actually makes a difference AND that parties are willing to share is a fundamental ingredient to a successful blockchain use case. Governance and data sharing agreements are the most crucial yet often the most difficult parts of launching a successful DLT ecosystem.

In evaluating these pillars, if there's gray area or any two of them are true for a given scenario, you might still be able to set yourself up for a distributed future using blockchain-based data sharing & verification concepts. Please comment below or contact me if you'd like to learn more.

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