Don’t let blockchain complexity bog down business applications

The real key, though, is that a blockchain creates a distributed ledger. It’s a history of all the transactions, just as an accounting ledger is for financial payments. And there are some notable differences in how the ledger can be configured for blockchain business applications to avoid bogging down their performance.

One part of the original cryptocurrency version of blockchain is something called consensus. Since cryptocurrency transactions are conducted in the open on the internet, there needs to be a way to verify that the data in a blockchain hasn’t been corrupted. Consensus is the idea that a majority of servers in a network approve each transaction before it’s executed, so a single actor is less likely to be able to corrupt data.

However, in a narrower enterprise blockchain setting, not everyone on the internet can access the distributed ledger; only trusted players in a controlled group can do so. That means consensus on ledger-changing approvals can be ignored, or at least reduced in scope. In the business world, with limitations on who joins private blockchain networks, the companies that set them up can focus more on managing permissions than on consensus — thus, easing blockchain complexity.

Another core aspect of cryptocurrency blockchain technology is the smart contract, which is a program that runs on a blockchain network and defines the parameters for an agreement between the parties in a transaction. For instance, a cryptocurrency payment won’t be forwarded unless the predefined rules set out in a smart contract are met.

That’s a useful element for many applications, particularly the trading of tokens that have monetary or other forms of value. But it’s another form of blockchain complexity that often isn’t needed for the kinds of transactions processed in business applications.

Take supply chain management, for instance. In conventional IT infrastructures, a manufacturer uses supply chain software to track all the raw materials being fed into the production process. Each company in the supply chain has its own systems, separately tracking the same things as the manufacturer. Reconciling differences in the data in multiple systems can be time-consuming, and opening up databases to business partners is complex.