Few technologies have generated as much excitement and curiosity as distributed ledger technology, a.k.a. blockchain. Across industries—particularly the supply chain—organizations have looked at distributed ledger as the answer to many long-held questions and challenges.
How can we:
While numerous pilot programs by large players like Walmart and Target have proved the viability of blockchain as a supply chain management solution, it has since evolved into a very mature offering.
Today, it’s no longer a question of “what if” for blockchain applications in the supply chain. It’s a question of “how.”
Currently, there are blockchain platforms available out of the box that can integrate and fit directly into your organization’s technology stack, creating an immutable, decentralized record of all data from the various systems across the supply chain—from your suppliers down to the consumer level, and back.
The most notable platforms—like the solution offered by Omnichain—use a Blockchain-as-a-Service (BaaS) model for delivery, which streamlines implementation time, while keeping costs low and making deployments scalable. Omnichain Vice President of Product and Operations, Diane Sullivan, provides a great explanation of BaaS and its benefits in this blog post.
Such solutions are helping companies move beyond the hype and take pragmatic steps to put distributed ledger into practice within their business. This, in turn, is helping to drive up adoption. In fact, in Deloitte’s 2019 Global Blockchain Survey, 86 percent of surveyed senior executives reported that they predict blockchain will achieve mainstream adoption—with 53 percent citing it as one of their top five priorities.
With the maturation of blockchain as a supply chain solution, it’s only natural for it to converge with other powerful digital technologies like artificial intelligence (AI) and machine learning (ML).
Namely AI and ML can now tap into the holistic supply chain data logged on a distributed ledger and start connecting the dots to find actionable information. So rather than requiring supply chain managers and other decision makers to comb through all that data themselves—which can cause analysis paralysis—the AI does it for them and at greater speeds and scale.
Combined with domain knowledge of your business, data, KPIs and fundamental objectives, the algorithms can learn, become smarter over time, and predictively guide you towards targeted outcomes.
These predictive analytics offer timely insights in how to:
As a result, your supply chain transforms from a binary system of inputs and outputs to an intelligent, well-oiled machine that can readily adapt to real-world, real-time data. Such predictive supply chain management—with blockchain at its foundation—is the future that’s possible now.
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