As supply chain complexity escalates, one of the most significant but often underplayed challenges is forging trust between parties. Establishing the authenticity of goods, ensuring a continuous record of their full life cycle history, and verifying and managing buyers’ and sellers’ identities are among the most arduous processes for supply chain partners today—and they inject inefficiencies and cost into global operations.
Combining blockchain—the distributed ledger technology that forms the basis of the digital currency Bitcoin—with artificial intelligence (AI) and the internet of things (IoT) has the potential to resolve these concerns. The convergence of these technologies eliminates time-consuming and expensive manual efforts, automating trust between partners and bringing traceability to supply chains.
“Blockchain is fundamentally changing a lot of things,” said Scott Likens, a principal at PwC and lead of its new services and emerging technology practice, at the recent Business of Blockchain event in Cambridge, Massachusetts. “But you can’t ignore what’s happening when you do blockchain-plus.” Combining technologies to solve problems is laid out in PwC’s “Essential Eight” list, which identifies critical developing technologies as building blocks for five key convergence trends. Blockchain plus maturing technologies such as AI and IoT, Likens says, can automatically establish trust among entities in a supply chain or in broader society. “When they come together, we’re starting to see business value emerge.”
The high cost of trust
The opportunity for transformation is significant because the cost of establishing trust in a supply chain is incredibly high. Consider the problem of counterfeit goods: The Organisation for Economic Cooperation and Development estimates that $461 billion worth of fake goods are sold annually, amounting to 2.5 percent of global trade. According to the Global Brand Counterfeiting Report 2018, total global counterfeiting is expected to surge to $1.82 trillion by 2020, exposing businesses to revenue loss, quality issues, and potential reputational damage.
As companies grapple with how to build trust among their suppliers, they are doling out big money on activities such as duplicative testing, manual auditing, and reconciliation, while investing in extra insurance and legal assistance to backstop any failure to meet contractual obligations. In the airline industry, for example, carriers are grounding planes longer, hoarding an excess of spare parts, and avoiding the use of less-expensive used parts and planes because they don’t fully trust their provenance. The health-care industry feels the pain through payers that spend more than $2 billion annually maintaining provider databases to ensure clinicians’ credentials are verified and up to date. And that’s just a snapshot.
Technology convergence can eliminate many inefficiencies and costs. For example, a digital “birth certificate,” which includes relevant data such as product specifications, provenance, and cost, gets entered into enterprise resource planning systems (ERP) and then integrated with blockchain. That provides an immutable, secure distributed ledger that serves as an authoritative and secure source for all participants in a supply chain. IoT sensors can monitor location, temperature, and other conditions. That time-stamped data is also stored on the blockchain record to create continuous provenance. AI-powered analytics come into play for real-time insights like flagging parts for maintenance or determining more efficient use cases.
With all these different contributors, blockchain becomes the foundation for smart contracts—digitally signed agreements between partners that the software executes and enforces. In one example of an automated-trust workflow, a smart contract would consult the IoT-enabled record of provenance to make sure temperature or vibrations during transport of a product stayed within acceptable levels before any warehouse in the chain accepts delivery. A smart contract could also automatically calculate payment due or assign responsibility to the right party in the event of a mid-shipment problem or dispute.
The combination of blockchain, AI, and IoT is “absolutely” the thing that can automate trust, agrees Geoff Woollacott, principal analyst at market research company Technology Business Research (TBR). “Trust can only be automated by removing human judgment and human error from the tracking, but this has to come after the business rules have been established up front in the smart-contract triggering, tracking and sharing—as appropriate or permissioned—the requisite information.”
Tech convergence at work
While there are currently few pilot projects showcasing the potential of technology convergence, Likens describes a project in China designed to tackle the societal problem of food safety. Government, customs, e-commerce companies, manufacturers, and logistics providers were not sharing data in a way that would effectively show the authenticity of a product. A blockchain system was built in a matter of weeks that brought together a diverse set of data without changing any core systems. IoT was used to track products and collect data on them to prove they hadn’t been tampered with. AI and analytics then translated the flow of data, picking up any possibility of likely counterfeiting by flagging if a product wasn’t where it was supposed to be, or if it arrived at its intended destination prematurely. The end customer used a simple mobile app to confirm whether products were safe before their purchase.
While blockchain elevated the level of trust, it didn’t do so in isolation. Consumers said they trusted the outcome even more if an unbiased third party—a consultant, for example—could provide an accounting of what transpired before it was entered into blockchain. “Blockchain has never been beaten, but the end points have, so IoT provides a different way of protecting the end point,” Likens explains. In the end, he says, the project helped create new data sets, transparency, and, ultimately, value to the consumers.
In a similar example, enterprise application software company SAP is working with Bumble Bee Foods to use blockchain and ERP to trace the journey of yellowfin tuna from ocean to table. The initial implementation relies on QR codes to track the fish; the long-term plan is to swap out that technology for radio-frequency identification tags for faster processing, and to employ IoT sensors in the plants receiving the goods to improve speed and accuracy.
“There is a more efficient and economical way for companies to enable the best possible food quality than building up a fleet of refrigerated vehicles to transport tuna,” says Torsten Zube, vice president and head of SAP’s Innovation Center Network. Instead, the tuna will be stored in a box that can monitor the temperature of the food during transportation, mimicking a cold chain, or refrigerated supply chain. “IoT helps control the temperature while blockchain creates trust across different parties to ensure the end user gets a high-quality, fresh, and safe product,” says Zube.
Identity management and verification is another use case in which converged technologies can have real impact. Likens cites the example of a utility company that has to bring on hundreds of contractors in a short time to deal with a national disaster. While existing onboarding techniques might take a full day to confirm a single contractor, a system powered by blockchain, IoT, and AI can be faster and more efficient. Before any one incident occurs, utilities can build a blockchain that stores contract employees’ personal information, credentials, and qualifications, including biometrics. Upon hire, IoT sensors and AI-powered facial recognition verify workers’ identities and deliver confirmed records of their qualifications.
Leading practices for getting started
Despite the promise, there’s no easy on-ramp to a converged-technology implementation of blockchain and its counterparts. Here are PwC’s recommendations to ensure successful execution:
Make the business case. Blockchain isn’t the right solution for every problem, so don’t start with the technology. Begin by identifying the problems blockchain can solve. To determine whether blockchain is a good fit, ask such questions as, “Is there a need for multiple parties to share and update data? Are there verification requirements? Do intermediaries add complexity?” From there, companies can craft a solid business case and strategic blueprint for blockchain implementation. Without such a roadmap, business stakeholders won’t have a clear vision of where to start, and that can lead to uncertainties, spiraling project costs, and potential delays. As part of the roadmap, companies should start small, targeting specific problems, and broaden the scope as confidence in blockchain builds.
Build an industry ecosystem. Blockchain’s value increases when multiple parties are involved, so organizations need to bring together a group of stakeholders to collectively agree on standards that will define the business model. That means sharing information with supply chain partners and other companies that may be considered competitors, but whose cooperation is necessary to decide things such as the rules of participation along with governance mechanisms, risk and control frameworks, and fair distribution of costs and benefits. While experts recommend initially focusing on a select few players, organizations will need to broaden their networks by influencing peers to join at a later date.
Determine rules of engagement. There is no single model for operation, so participants in a blockchain ecosystem will need to make decisions about operating standards based on design and use case. Will blockchain be permissionless (available to all) or permissioned (restricted in some way)? The ecosystem will need to address compliance, cybersecurity, privacy, and legal requirements, as well as rally around the appropriate architecture.
Navigate regulatory uncertainty. If designed properly, blockchain eliminates the need for a central authority, which reduces costs and delays, but it also removes institutions that help ensure market stability. Ecosystems should stay abreast of regulatory developments and engage with industry groups to help shape their emerging policies and best practices.
TBR’s Woollacott recommends that organizations think big and develop their “long-term aspirational objective.” To start, they’ll need an understanding of multiple technologies for a small-scale pilot. Then they should enroll ecosystem participants with a “what’s in it for them” value proposition, focusing on how their participation will either cut their costs or grow their revenue or their total addressable market, or revenue opportunity. Doing so will help them build the required ecosystem to do what they set out to do.
Blockchain may have grabbed headlines as a disruptive force for financial transactions, but its real impact may come from transforming operations such as supply chain. As part of a converged-technology model along with IoT and AI, blockchain has the power to automate trust across parties, freeing enterprises from the burden of inefficient and costly practices and optimizing an ecosystem for competitive advantage.