If you are familiar with cryptocurrency, then you are probably familiar with blockchain. Blockchain is the underlying technology ensuring transactions are accurate, transparent and immutable. Why is this technology important? When you’re working across a large number of individual stakeholders, there’s always the fundamental presence of inconsistency. Even if you completely trust the other person, human error is unavoidable.
Let’s look at a quick example. If you’re going to meet a friend for dinner and their clock didn’t update for daylight saving time, it was an accident, but it didn’t make them any less late. Blockchain technology operates in a similar way to the clock on your cell phone which automatically makes this correction, but instead of the time coming from a single centralized decision maker, it is reached through a majority vote by all the participants on the network.
The primary difference between a blockchain and a database is centralization. While all records secured on a database are centralized, each participant on a blockchain has a secured copy of all records and all changes so each user can view the provenance of the data. The magic happens when there’s an inconsistency — since each participant maintains a copy of the records, blockchain technology will immediately identify and correct any unreliable information. Your friend’s watch would immediately self-correct for daylight saving time, even if a third person maliciously changed the time so they would be late, the time would immediately be verified against all participants and corrected.
When data can automatically identify and correct itself based on coded business logic (smart contracts) and consensus, participants are intrinsically able to trust it. When two businesses work together, they almost never share a single database with a single set of records, because the database is being maintained and updated by a database administrator (DBA). That DBA is being paid by one of the companies and thus has a stake in the success of one company but not necessarily the other. If they want to make a change that benefits their company, the other company would never know. Alternatively, on a more nefarious note, if a competitor decides to pay off the DBA, they can make any change they want to the database without either participant ever knowing.
When blockchain technology is incorporated into the data process, you remove the single point of failure, in this case the DBA, and ensure that if one of the participants makes a change it is immediately corrected by the other participants. After the data corrects itself, the unalterable record of changes will also indicate which participant tried to make the change. With the data process secured, a business can not only trust the data shared between the companies they are working with but can even trust the data shared by competitors. For example, if Samsung and Apple are sharing technology with each other, Samsung can trust that Apple has made payment for the technology and Apple can trust that Samsung has delivered it.
Trust the data
An interesting thing happens when competitors can trust the data being shared, it creates opportunities for more participants within the vertical to join the blockchain network and increase the visibility into the data. Expanding on the previous example, if Samsung and Apple are sharing technology and data on a blockchain network, and a transportation company joins the network, that data the transportation company wants to share on the network is immediately accessible to each of the other participants and then replicated to their records. Any time one of the participants makes a change, a new version of the record is validated by all participants. In this case, Apple could track the shipment from Samsung’s factory to Apple’s manufacturing center.
Additionally, if a bank is added to the network, payment to the bank and to each participant after a transaction can be triggered automatically when a condition in the data is met, and because this data is secured and validated by all the participants, no single participant can fraudulently, or accidentally, alter the data to meet the conditional trigger within the data.
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