Five roadblocks on the path to Blockchain Industrialization

Every technology, in its emerging stages, has certain limitations which need to be overcome in order to propel the technology to maturity/Industrialization. Blockchain is not an exception. The perspective of limitations may vary from one professional to another but in my mind, there are five key challenges that need to be overcome to take this technology to Industrialized stage. Those five challenges have been discussed below.


Latency in Blockchain context is the time it takes for transactions to be confirmed on the Blockchain (which is the time between the creation of the blocks of data and their subsequent confirmation and verification in the Blockchain). What this means is that unlike conventional transaction processing systems used for credit cards and banking, adding records to a Blockchain is more analogous to an airline reservation and similar booking systems that commit orders to a database and may take several seconds.

As Technology advances, the speed of systems will improve and Latency may not be a hindrance.

Lack of Regulation

As is the case with all emerging technologies, Blockchain regulation is still a Grey area. There are some emerging frameworks but nothing that is definitive and robust. One major implication of lack of regulation is in the area of dispute resolution. This may not exactly be a showstopper but leads to caution in foraying too much into this domain.

As regulative legislations evolve and mature, so will the adoption of Blockchain technology on an Industrial scale.

Energy Consumption

It is open knowledge that a huge amount of processing power is required to verify Blockchains. This cost is significant and is one of the reasons that large server farms that process these transactions are in geographies where energy is cheap and ambient air temperatures are cool (like Iceland, Siberia, Scandinavia etc.)

Data Quality

One big challenge is the ability to capture the data as close to the source as possible to ensure its accuracy. Companies and Supply Chain leaders will have to ensure more audits of data quality, which is essential for many of the merging systems and technologies to work effectively. Regular, random quality checks can be carried out on data across the Supply Chain at regular intervals to avoid the issue of false data corrupting trust in the information

Lack of Knowledge

Again, since the technology is emerging, expertise in this technology is limited to professionals who have led projects for early adopters. As the number of adopters grow, market will have more individuals who have actual experience implementing this technology.

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