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Practical Applications of Emerging Blockchain Concepts

By Janeiro Digital | June 20, 2017

Blockchain is all the rage and, as with the early days of any invention, confusion and hype abound. But implementations like Bitcoin, Ethereum, and Fabric are leading the way with practical applications. While you can bet blockchain concepts are poised for disruption in certain markets, blockchain itself doesn’t signal inevitable revolutions.

The buzz around blockchain includes several core ideas that have individual practical applicability:

  • The Blockchain
  • Smart Contracts
  • Distributed Ledger
  • Consensus

Each of these concepts warrants more detailed exploration. Before you dive in, though, get oriented with the short explanations and business cases below for each so you can start thinking about how these concepts might apply to your situation, one at a time or in combination.

Here are some ideas for how to apply the technical constructs of blockchain to your own world, here and now.

Blockchain is highly secure

The blockchain data structure is a very clever extension of traditional computer science. A block is a discrete set of data, often collecting transactions in the form of a ledger. A blockchain is a linked-list of these blocks. Compare a block to a page in a book. The page number tells you where each page falls in the sequence. In a book, even though the pages are in sequence, you could change the content of page two without any change to page three. In blockchain, the reference is more than just a sequential number. It’s a thumbprint, a hash of the block’s contents that includes a reference to the preceding block and therefore includes that block’s content. Changing the content of a historical block means changing the entire chain as each following block must be rebuilt. To replicate and distribute the chain, you must change all the copies, which is not easily done.

With or without a distributed ledger and blockchain replication, the increased effort of modifying a block is prohibitive. In IoT implementations, the increased attack surface of millions of connected things is causing a bit of panic among security professionals. Basic blockchain structures allow you to improve the security of devices in the field without an undue burden on suppliers.

Here’s a scenario. Let’s say you’ve decided to market a smart connected lawn mower. You want to send telematics information about push speed, blade rotation, grass moisture and more to a central analysis engine to determine how people are using the lawn mowers and provide improved designs and services to mower dealers. Several different suppliers make the electronics to your specifications and, based on cost and regulation, you’ll need to manufacture in multiple locations.

People hack the most surprising things—light bulbs, air conditioners, Roombas. While you can trust your suppliers, you don’t want a hacker taking apart the machine, replacing physical components and using the modem to maliciously connect to your device cloud. To prevent this, you can catalog the internal serial numbers of the key components and certificates inserted during manufacture and use this data to determine if someone has tampered with a mower before allowing it to connect.

Blockchain makes this process more secure because it introduces additional complexity for those looking to modify the device. Using blockchain, your suppliers can insert a record of the device componentry at a trusted moment: when it is manufactured. The suppliers will not need access to your internal systems and can simply post the as-manufactured configuration to the blockchain. This creates a more secure firewall because you can compare the device’s current componentry with that in the chain to determine if it is safe to allow into the network. To get around this security system, a hacker would need to tamper with the electronics and amend the device’s record in the block and the subsequent chain. Not an easy task.

This example is simplified somewhat and if you are a security professional, you certainly have many other things to consider. The point is, because of the way the blockchain uses hashes for reference, combining physical and digital security using blockchain instead of a traditional database can greatly increase the complexity and computational effort required to successfully breach a system.

Smart contracts are precise and reliable

Like identifiers, rules can be embedded in software inside the blockchain. These embedded rules are called smart contracts. The implementation of your particular blockchain system will support varying levels of embedded code, allowing you to create something akin to an IFTTT (if-this-then-that) script that is part of the record. The original application of smart contracts was to allow agreements to be embedded in the ledger. For example, if the market price of asset A is above X, then transfer 1,000 of my shares of asset A to account B. Because smart contracts are embodied in software, they are not open to interpretation the way typical written agreements can be. In the real world, terms of contracts requiring interpretation and flexibility may be desirable, because events aren’t always precise. In the business world, precision and reliability are usually the goal, and a machine executable smart contract can be put to good use.

Tracking information in a precise, reliable way is especially helpful for businesses that must keep a financial account of seemingly endless detail, such as customs duties and tariff classifications. This is a complicated world of goods made from parts and materials from around the globe, crossing borders and navigating a maze of mind-boggling rules, trade agreements, and interpretation. Sorting all of it out with a combination of block-chain technology would be truly transformational. Luckily, the steps toward that transformation are accessible now.

Let’s look at an example. Imagine a supply chain has agreed to use a blockchain system (public or private) to store information about their parts and the origin of those parts. An assembly used in the manufacture of their rail industry products contains a wheel made in Canada, a gear made in Mexico and an axle made and assembled in the U.S. When exporting the assembly, the tariff classification and applicable import duties could vary based upon the end use, the tariff rules for the importing country and the applicability of tariff preference programs between the exporting and importing countries. That complexity can be facilitated with smart contracts.

The supply chain knows that the origin information for that assembly is 10% Canadian, 30% Mexican, and 60% U.S. This information can be posted to a distributed ledger to aid in the process of determining eligibility for tariff preference programs when it crosses a border. If the Mexican supplier changes their source of raw materials and now purchases the steel from Peru instead of locally in Mexico, the makeup of the gear changes. This may change the eligibility for tariff preference programs, depending on the tariff classification and cost of the gear.

To support the other members of the supply chain, the Mexican supplier can create a new record for gears manufactured with the Peruvian source, triggering a smart contract to inform the consumer of the gear and the U.S. manufacturer to update their records, which creates a new assembly that includes the new makeup of the Mexican gears. This, in turn, triggers a smart contract requiring a reassessment of the eligibility for a tariff preference program that may apply when the assembly is shipped across a border. With a little analysis, a further smart contract can be written to determine which assembly to use when shipping to certain locations where the origin of the components will provide an advantage based on the batch of gears used.

A scheme like this requires agreement along the supply chain and some well-written smart contracts, but it has the potential to save labor, ease audits, and considerably reduce customs duties and fees or customs penalties—particularly when the tariff preference program rules of origin are complicated. For heavy equipment manufacturers with a high instance of import/export this runs in the tens of millions of dollars per year.

Distributed ledgers facilitate implementation

Of course, all this communication requires consistent oversight to run smoothly. Quality and reliability vary greatly across suppliers. Record keeping is a constant flurry of emails and phone calls to verify the origin of a part. The rules about origin can change if an assembly, such as a transmission, is rebuilt. And tariff classifications have some quirky rules, such as rail car wheels used on a passenger car get a tax break, but the same wheel used on a freight car does not. This complication might be resolved by setting up a central authority to oversee and govern the entire supply chain, but that is impractical for many reasons. A central authority would have to be able to manage a constantly changing combination of suppliers. That would require coordinating all the data to build and maintain the database.

In business, efficiency is prized. It’s unrealistic to expect each supplier to coordinate with each of the other suppliers directly. And it’s overwhelming (for both the people and the computing power) for a centralized authority to manage the constantly changing data. Clearly, the supply chain origin and tariff classification problem is difficult to address with a typical, centralized database.

A distributed ledger solves this problem because the nodes in the supply chain need only insert and share their own data. In addition, they can join, leave, and rejoin the group as they wish, giving them power over their own processes and technology investments. In a distributed ledger, no central authority owns or controls the data. Instead, the distributed ledger is defined by predetermined rules about the data, such as what data must be included, how it is to be shared, etc. The rules are replicated across the distributed ledger, making it possible for each node to interact with them directly.

Control over the validity and availability of the data depends on application of the rules, not on a central authority. Reliability is determined through consensus (see below). Data from a node that does not follow the rules will be rejected as unreliable by the other nodes. In order to continue participating in the exchange, that node will need to modify its data practices to match the expectations of the group.

Because the rules exist across the distributed ledger, nodes can join and leave the group as suits their business needs without risk to data integrity. Data sharing continues, evolving as necessary through the balance of participation and acceptance within the group. The use of a distributed ledger is particularly helpful where incentives rather than regulation provide the motivation to participate and the cost of entry is low as compared to the reliability of the transactions.

Here’s how all that might play out for our railroad supply chain. In reality, that chain will have many more than three participants. A case in which a U.S. manufacturer can source the wheel and gears from seven different suppliers in four different countries is still simplified, but serves to demonstrate the advantages of distributed ledger. Traditionally, the choice of supplier is based on availability, quality and material cost, not on customs impact. Drastically increased effort to track customs impact does not match the possible benefit to the supplier. However, if the suppliers all participate in a distributed ledger that includes their product’s manufacturing origin, incentive and potential profit increase. Calculating the impact of customs duties and fees gets much easier because all the required information is in an accessible and reliable ledger.

Suppliers are motivated to participate because they gain an advantage by making themselves an efficient and reliable partner. If a supplier does not participate, they lose preferred status and instead must have a compelling price or availability to compensate.

Consensus keeps the data valid and current

There are several consensus models being used with blockchain. For detailed implementations, explore Bitcoin’s proof-of-work, Ethereum Casper’s proof-of-stake, or Intel’s proof-of-elapsed-time.

In the proof-of-work model, nodes compete to get their ledger entries incorporated into the blockchain and accepted by the group, so that they receive the incentive. Keep in mind that blockchain does not require consensus to function. For example IBM’s Fabric operates as a private network where membership services replaced consensus. Nonetheless, where no central authority exists to manage membership services, consensus and competition work together to power distributed ledgers.

Consensus can also power the updating of software, and thus the rules of engagement for a specific blockchain system. Bitcoin is a great example. The source code is public and anyone can propose a change. However, each node may accept or reject the update. When sufficient nodes have accepted the new software, others must follow in order to remain competitive and receive incentives. If insufficient nodes accept the new software, the proposed features expire by consensus.

Let’s apply consensus to scientific research as a reference for decision making. Peer-reviewed science can be hacked. The most famous example is the notorious Dr. Bohannon hoax in which a study linking weight loss to a daily diet of chocolate made headlines. Reputable researchers can evaluate the validity of a study because they know which journals publish which kind of articles and the quality of the peer-review. However, an average person who wants to fact check that claim of chocolate weight loss lacks access to the information necessary to determine the reliability of the research.

Currently, only the experts in a field of research can find flaws in data, methods, or analysis sufficient for quality work to undergo valid peer-review. Even with this process, unreliable information can enter the field. It is possible to enhance this model by adding a ledger of published material accepted by consensus of a wider, informed audience.

A recently published researcher would submit a proposed addition to the validated ledger. The consensus process uses rules that require a supermajority of the participants to accept it before it becomes a valid entry, adding a layer of expert acceptance on top of peer-review. A search of the ledger would then determine whether the publication was accepted as good science by a qualified audience.

For this use of consensus to be successful—and avoid a free-for-all that undermines the acceptance of all the data—the underlying rules must also be accepted by consensus. For example, to limit ledger entries to validated data, a rule might be that a node must be an accepted research or analysis organization known to be current in the field for which they validate published works. Another rule might be designed to check political influence on scientific research by preventing political and corporate bodies from silencing findings contrary to their agendas. According to the byzantine general’s dilemma, two-thirds of the participants must be “loyal” to the principles on which the ledger is built. Consensus rules will be required to maintain a sufficient majority to keep the results valid.


Blockchain and the related concepts that have grown around Bitcoin, Ethereum, and other emerging implementations can provide flexible solutions to business problems today. While much of the technology needs to mature, the first step is practical application to a business problem.

Once you have a good match in technique, the search for the right technical solution begins.

→ Need help building a practical blockchain strategy? Get in touch.

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