Blockchain and other Distributed Ledger Technologies, an advanced primer

Gilles Hilary, Georgetown University

-- This blog post is directly inspired by the eponymous chapter forthcoming in Innovative Technology at the interface of Finance and Operations, Springer Series in Supply Chain Management, Springer Nature (edited by Vlad Babich, John Birge and Gilles Hilary).

Technology has always gone through recurring breakthroughs. At the moment, artificial intelligence (AI), distributed ledger technologies (DLT) such as blockchains, and the Internet of Things (IoT) are receiving a lot of attention and funding. Others such as quantum computing or 5G networks are emerging. New sensors and actuators, integrated into more and more “smart” objects, generate a greater, more diversified, and more timely flow of data. These technologies create synergies and foster the creation of “systems” (elements that interact with each other automatically and intelligently) and new economic models. To better understand these evolutions, John Birge, Vlad Babich, and I have edited a two-volume book that reviews recent developments in finance, operations and technology.

One of the topics of importance is the emergence of blockchain and other distributed ledger technologies (DLT). Although there are many versions of blockchain technology today, it was first introduced in 2008 as the technology supporting Bitcoin, the first successful virtual currency system. In and of itself, blockchain technology is much more than the underpinning for Bitcoin (and other cryptocurrencies) and has found many applications beyond its initial purpose. For example, Vlad Babich, and I cover some of these to the field of operations from a more academic point-of-view elsewhere (here and here).

A blockchain is essentially a database with a specific structure. Historically, databases were centralized entities with one owner (naturally, there could be multiple individuals representing this owner) and potentially many users. This basic technology started in the 1960s and now is very mature. For many applications, this approach remains natural (for example, a security exchange may want to centralize all transactions on one trading platform).

However, there is a need for multiple actors with potentially diverging interests to share data in some situations. Two companies may need to share sales/purchasing records but have opposite interests. Of course, these data exchanges have costs like for any transactions. There is an initial cost to set up the database and marginal costs to process subsequent transactions. The cost of integrating these different elements is often significant and increases as the number of nodes in the network increase.

DLTs offer an alternative approach to data sharing problems by massively distributing the database and removing the notion of ownership. They make it easy to add nodes to the network and lower the cost of processing additional transactions. However, these marginal costs remain higher than those associated with a centralized database that has been properly optimized for specific usage.

Although DLT removes the need for trusted intermediaries and offers additional features (such as added resiliency), the main benefit of DLT is to offer an alternative cost structure for databases. Most things accomplished with DLT can be done with alternative technology, but many of these possibilities are not economically feasible.

One framework for examining the optimality of a DLT approach is to consider the 4Vs of Big Data: Volume, Variety, Velocity, and Veracity. The core motivation of blockchain technology is to ensure that data cannot be easily manipulated. However, we do not have much of a historical perspective on whether DLT can indeed provide security that is superior to a traditional database protected with state-of-the-art technology (I covered security issues elsewhere). DLT security can also be negatively by affected layers built around the DLT per se (e.g., wallets, API). DLT can aggregate heterogeneous systems and add value through tokenization and smart contracts; thus, DLTs hold the promise of better integration of IoT. This appears to be one of the main benefits of the technology. Improved integration can also acquire data faster, but processing is less efficient than with traditional systems at the moment. The effect on Velocity is, therefore, generally undetermined. Finally, efficiency and scalability are currently the two main problems of this emerging technology. DLT is, therefore, unlikely to help with the volume of data.

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