Blockchains and Perfection: How to Measure Data Improvement and Value Added Features
Blockchains Don’t Need To Be Perfect; They Just Need To Be Better
Blockchain technology has immense benefits, addressing trust barriers in supply chains. However, people still ask one important questions: “don’t we still have to trust the person/thing mandated to input the data?”
Typically, the answer for this us yes!
You see, some people may see this as contradictory, considering blockchains should be completely trustable and solve issues to do with opacity within transaction chains, inefficiency, and friction. Since blockchain is an immutable ledger, most go ahead to argue that, all one is doing is creating an “immutable garbage-in/garbage-out problem.”
This is an important question, and actually points out to major challenges that make the technology much more important. For starters, one blockchain technology should be promised as some kind of super “trustless” utopia, because no such society can exist.
Blockchains Have Potential To Improve
While blockchains can’t fix every problem, they have the potential to become better and improve one aspect of trust in the economic architecture of the society. You see, here we have a system that records a sequence of data reliably within a specific dataset, and does so in a way that cannot be altered or manipulated by any single party, without a consensus agreement. This means we can effectively remove a layer of uncertainty from the trust equation, which happens to lie at the heart of most economic communities. This is, without a doubt, major progress.
Let’s be honest: these problems were not solved by enterprise software solutions and spreadsheets. With blockchains, the shared data that emerges from distributed ledger is more powerful and reliable. It is therefore safe to say that blockchain solutions are built to strengthen collective trust, and not diminish it.
Picking Patterns Of Untrustworthy Data Sources
Now, here’s the best thing about blockchains: it’s possible to spot patterns of bad behavior from untrustworthy data sources/people inputting the data, holding then to account. When decentralization is combined with other management tools like artificial intelligence and data analytics, its prospects are enhanced.
Take, for example, a factory staff who has been outsmarting others in the supply chain, recording false data about his work output consistently without detection. The behavior might not be visible to the naked human eye, but can’t be hidden from a computer running a complex network analysis. In a short span of time, it will uncover unusual pattern in the database and expose the factory worker.
In conclusion, a blockchain shouldn’t be perfect, and it can contain garbage. However, in most cases, it’s better than what we currently have.