Omnichain's predictive analytics inform decisions
Last month, FE provided an extensive look at blockchain technologies and their application in food and beverage. Though relatively new, blockchain distributed ledger technology (DLT) applied in food and beverage can speed up tracebacks from days to seconds, as IBM and Walmart demonstrated a few short years ago. Blockchain technologies can, of course, be used in the supply chain to provide a verifiable journey of a product or ingredient (including conditions) from the farm to the consumer.
So along the way, blockchain technologies can be used to aid in food safety and recalls, get a handle on food fraud, satisfy regulatory compliance, improve sustainability by finding faults in the supply chain, help companies become more sustainable and provide consumers with information to make better buying decisions. Blockchain technologies can also help with product design and lifecycles.
While interviewing the experts last month, I found one innovator—Pratik Soni, founder and CEO of Omnichain—who is already taking blockchain technologies to the next level: artificial intelligence (AI) and machine learning (ML).
Omnichain offers an end-to-end software platform that enables processors to establish their own blockchain network and distributed ledger of supply chain data—from farm to fork. Soni says it’s a solution that is ready to deploy out of the box through a blockchain-as-a-service (BaaS) delivery model, which streamlines implementation time and costs—and is affordable enough to let small and mid-sized processors use the technology.
I asked Soni to fill us in on some details.
FE: How and why did you start Omnichain?
Pratik Soni: Omnichain is the accumulation of my own 20+ years of experience in supply chain management strategy and execution. I founded the company in 2016 out of a growing gap I saw where companies were investing heavily in the physical supply chain, but not so much digitally, creating siloed operations.
Namely, each stakeholder tended to rely on their own systems, databases, spreadsheets or even paper files to manage their respective roles. The supply chain was growing more fragmented and complex, making important aspects of supply chain management difficult.
I set out to create a solution that would connect stakeholders and their supply chain data to enable greater transparency, traceability and holistic supply chain management. Distributed ledger technology, aka blockchain, was the ideal technology to power this connectivity. We officially launched the Omnichain platform in February 2019 and have been on an upward trajectory, growing our client base.
FE: How is Omnichain similar to—or different from—other blockchain systems?
Soni: Similar to other enterprise blockchain solution providers: We use proven distributed ledger systems like Ethereum and Azure Blockchain Service. Like these organizations, we’re creating private ledgers with user-based permissions for who can publish to the network. Their data is then validated and decentralized on blockchain among stakeholders.
What differentiates us is we have an entire suite of applications for critical supply chain functions that is also decentralized. This includes applications for channel allocation, demand forecasting, supply chain planning, inventory management, transportation management, returns management and supplier integration. So if you’re using our supplier integration app, it can also be permissioned and distributed to your supplier base. The goal is even greater connectivity, flow and collaboration between participants in the supply chain.
The main differentiator between us and other providers? We not only provide a way to connect disparate supply chain data, but also the ability to take action on it. Our customers can apply artificial intelligence (AI) and machine learning (ML) and leverage their holistic, decentralized data to drive better workflows, gain predictive and prescriptive analytics, and orchestrate their entire supply chains.
FE: Tell us some more about the role AI/ML play in Omnichain.
Soni: AI and ML play significant roles in our solution architecture. With access to big data on blockchain, our AI and ML applications can run calculations and analytics and deliver actionable information to decision-makers. These algorithms make up an “intelligence layer” that sits between our foundational mesh connectivity layer, i.e., the distributed ledger, and the user interface of our platform.
Among the information delivered to users, there are intelligent recommendations for next best actions and alerts to issues or workflow exceptions. The algorithms get smarter and more attuned to your business and supply chain network over time. Taking into account both historical and real-time data, the predictions get better too, so customers can make proactive decisions to stay ahead of the curve.
FE: How “real time” does the system need to be?
Soni: The more real time a system can be, the better. But the truth is, blockchain can have latencies, depending on the number of transactions. After all, there’s the time needed to publish and validate the data on the network. We’ve taken measures to combat latency through a system for the efficient storage and retrieval of discrete transactional information, which we own the intellectual property for.
Basically, we not only publish data onto the distributed ledger network, we also have a data storage layer that records that data too. Customers can thereby process that data as close to real time as possible if there is any latency on blockchain.
FE: For any blockchain supply chain system to work, don’t you have to get buy-in from all participants? How do you do that?
Soni: It depends on each company’s business model and how granular they want to get. You may not need every participant on the ledger—only key players or nodes. But if someone important asks, “Why do I have to join?” you can gain their buy-in by communicating its shared value for the entire supply chain. Essentially, enhanced levels of communication and transparency enable better efficiencies, which have downstream business benefits. Everyone can be more agile, nimble and effective. It’s a win-win for all.
FE: How does Omnichain connect players in the supply chain, and who pays and on what basis?
Soni: We have a robust API connectivity layer that can connect parties via web services or direct point-to-point connectivity. As to who pays, we have a BaaS model that is transaction-based, meaning payments are based on the volume of transactions logged to the ledger. Then, we also have a traditional user-based, monthly subscription model. Mainly, it is up to each participant to pay, which is why it’s important to communicate that shared business value. Some of our customers do pay for their suppliers as well, recognizing the benefits outweigh the subscription fees.
FE: How does a user connect an existing ERP or food safety/quality management system to Omnichain?
Soni: Our customers aren’t technically connecting their ERP or food safety/quality management systems to our platform. They’re simply sharing data from these systems to the ledger. Thus, our platform is software agnostic and fits within existing technology stacks.
FE: Can you describe how any food or beverage customers are using Omnichain?
Soni: We’re working with frozen treat brand Ruby Rockets to connect its suppliers and improve ingredient traceability. Currently, we’re also helping a leading producer of pancake and waffle mix tie together its suppliers, warehouse systems, distributors, ERP systems and more on our connectivity layer. Notably, we’re helping them improve their lot and batch code management, which was challenging before. Ultimately, they want to get more accurate demand forecasts, optimize production planning and drive more intelligent supply chain planning, execution and delivery.
For more information, visit www.omnichains.com