Mastering blockchain for traceability and trust
Document sharing
Much of blockchain’s trustworthiness directly stems from the solidification of data governance mainstays of data provenance, data security, data privacy, and regulatory compliance. When these traits are combined with real-time capabilities in properly implemented deployments, blockchain becomes an optimized mechanism for the realities of working remotely in the increasingly decentralized data ecosystem. Its data governance qualities make blockchain a worthy tool for both protecting and sharing documents at scale between parties.
Wagner described the advantages of employing this technology in the fields of architecture and construction when building large structures. “Making even a small mistake in the placement of something and tracking who signed off on which part of a contract—or which change order at which point in time— has multiple hundreds of thousands of dollars at stake.” The distributed ledger technology approach enables a diversity of parties to readily review this information, audit it as needed, and establish a single version of the truth to ultimately discern who is responsible for what in order to minimize any errors. Even without the need to rectify mistakes, it’s an efficient mechanism for sending protected documents between numerous parties for this or any other project management use case.
Furthermore, it fortifies real-time, geographically dispersed workflows, which is invaluable in the current business climate. “With the myriad of contracts, agreements, change orders, blueprints—a decision-making flow around hundreds, even thousands of different individuals—there’s a way to keep track of who said what, who agreed to what, and who changed what at what point in time,” Wagner said. “And, everybody has a single source of truth, a single system of record, and an ability to refer to that again for auditability and reconciliation.”
Data modeling the truth
For blockchain to serve as a single source of truth between distributed parties using different data management tools, its diverse participants must account for their varying data models. Some users, for example, may rely on relational models while others favor graph techniques, XML, or something else. Often, agreeing on a common data model for interchanging data highlights the data privacy and security issues for which blockchain is renowned. Again, the key consideration is trust. “Often, it’s a frenemy situation,” Wagner acknowledged. A company may need to work with other companies but also compete with them and may have contractual reasons or compliance reasons to be cautious about how broadly and deeply it is able to share information.
Neutral data modeling options such as JSON (which is schema-on-read or schema-on-demand) are useful for providing a shared model into which blockchain constituents can painlessly wrangle their data. “You have to be able to layer in governance, visibility, and controls so it’s not unfettered transparency,” Wagner cautioned. “The ‘trust’ is also trust that people aren’t seeing the data they’re not supposed to see, as much as that they’re seeing the data they are supposed to see.”