Supply Chain is a cluster of independent units in an organization including, analytics, production, sales, marketing, logistics, warehousing and transport that work together to achieve a common goal of supplying a finished product to the end consumer.

In an ideal scenario, these departments work coherently to achieve a single point mission and deliver on said results in a pre-defined time frame. However, most of the times, processes and legacy systems are far from perfect. They often lack a common connect between said units causing costly deviations in resource management, workforce management, tracking, customer service, and service delivery. With legacy systems, there is no common chord that connects the flow of the product raw material to production. They do not justify the cost involved, the authenticity of the product, or any other specifics promised by the marketing team.

Let us analyze the journey of a product in a legacy supply chain module. Take an example of a textile manufacturer who touts about being the only manufacturer in the United States to import their Linen from the deep forests of Amazon. Any raw material that comes their way would be stored in their warehouses, sent to the plant for production and there would be no intermediate checks to monitor intricate details of this process. The logistics team would load their trucks with the finished goods and deliver them to the retailers or users without looking at the big picture. The marketing propaganda of said manufacturer is not something their warehousing or logistics team would know.

With digitization, organizations are now opening avenues for collaboration and efficient internal linking using AI and Blockchain. The Blockchain network tracks every step of the product from raw materials to production and the distributed ledger system allows for multiple permissioned users to monitor every stage and prevent bottlenecks by foreseeing operations at every unit in the chain.

Digitization in the form of integrating Machine Learning allows the system to understand the roadmap efficiently and predict the future needs of the organization in terms of manpower, raw material, and other elements by factoring in various components of pricing, man-hours, equipment involved, and a plethora of other variables involved.

In short, Digitization enables organizations to cut costs, forecast demand, optimize processes, reduce time atrophy, and offer improved customer experience.

Here’s how you can harness IoT to digitize your supply chain:

Prescriptive Analytics:

Increased efficiencies in supply chain management can be achieved when all the processes involved are integrated into a non-linear approach with visibility. When this is achieved, planners can factor in various external attributes to focus on reducing delivery times, sourcing on-demand delivery vendors, or sourcing back-up fleets to meet production and time to market commitments. This can be achieved by integrating AI, Big Data and ML to constantly learn from the existing use cases, from every entry at every stage of a product and from every roadblock and bottleneck in the process. Thereby, delivering a tailor-made approach to efficiently manage the supply chain and predict the hurdles involved and be better prepared to tackle them or chart a new route to eliminate them.

On-Demand Sourcing:

Sourcing raw materials is an integral part of Supply Chain Management. Creating a plethora of vendors and integrating SaaS based operations with vendors enables organizations to monitor and validate the authenticity of the products sourced. Digitizing sourcing enables the organization to enable a P2P model of commerce and improves efficiency metrics in cross border payments. This radical a shift in the way the legacy systems function and enables reduced costs for sourcing and increases efficiency in delivery timelines.

That said, there would be a significant cost to the company in enabling on-demand sourcing as there would be costs involved for procuring and maintaining sensors, trackers, and software installation and maintenance. But, on a broader perspective, these costs will revolutionize the way sourcing happens in the supply chain and deliver improved efficiency and yield greater customer satisfaction.


Smart warehousing has been adopted by major organizations who were the early adopters of digitization in supply chain management. With this, warehouses can track the location of inbound trucks, schedule arrivals, allocate space for storage and assign the robotics and manpower required to move and store goods for their speculated time periods.

When an inbound truck shares its location, the warehouse creates the manifest that will allow a smooth transition into the warehouse while storing information on the time of arrival, its delta from the scheduled time, parking slot allocation, robots required to move the goods, and duration of procurement. This helps the organization to efficiently use space, manage resources, and cut costs by predicting the next inflow and outflow.

These sets of data can again be shared on the blockchain to alert the manufacturing team about the next shipment, time of delivery, and expected volumes to meet market demands.

Digitizing these processes by 3D printing bar codes, enabling robotics in logistics, and enabling a shared network has delivered results in terms of cost reduction, efficiently managing storage space, and human resources.

Efficient spare part management

Logistics play a predominant role in the supply chain management industry and yet has not seemed disruption since its inception. Even today large organizations do not have a predictive analysis in place to forecast the future needs of this wing due to the involvement of various external factors including human competence, weather conditions, and other variable elements.

With Big data and ML, logistics is witnessing digitization in the form of efficient spare part management for their existing fleets of vehicles and machinery. Digitization empowers organizations to predict the resources required to maintain their fleets and schedule bulk orders to schedule maintenance while reducing costs and ensuring timely deliveries.

These are few of the many ways by which ML, IOT, blockchain, and Big data can be used to digitize a supply chain. Not all systems are perfect and witnessing a fully functional digitized supply chain might take 5 to 10 years, but early adoptions give organizations the edge required to be the pioneers.