How to Make IoT Power Your Supply Chain - CirrusLabs

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Organizations that still depend on legacy logistics processes miss opportunities to improve efficiency all along the supply chain. That reduces costs and can increase profitability.

Every business unit involved in the supply chain needs to collaborate for increased efficiencies. But many organizations fail to realize which parts of their company are involved. And they need to know which business units should take part. These include:

  • Analytics
  • Production
  • Sales
  • Marketing
  • Logistics
  • Warehousing

If they work together, the organization can deliver its end-product on time to the correct location.

Organizations soon learn the shortcomings of their processes and legacy systems. A disconnect between these business units causes costly deviations from requirements. The disconnect occurs because legacy systems lack a common chord to connect the flow of the product’s raw material to production. They cannot assure the cost justification, product authenticity and other specifics promised by the marketing team. This affects resource management, workforce management, tracking, customer service and service delivery.

Examining the Legacy Supply Chain

Before we discover how to improve the supply chain, we should examine the road map for a legacy supply chain. Looking at a textile manufacturer’s supply chain reveals its weaknesses. This company claims it’s the only U.S. manufacturer to import linen from the deep forests of the Amazon. The linen as a raw material gets shipped straight to the organization’s warehouse before use at the textile plant.

But the company’s different business units lack any information about the supply chain. They don’t know what raw materials and inventory are in stock, what orders are coming in or how much product is being manufactured at any given time. The supply chain system lacks checks to track deliveries, arrival times and what raw material remains in the warehouse.

The warehouse manager does keep track of the raw materials on delivery and shipment to the manufacturing plant. He’ll also record what manufactured products on site. The logistics team records what finished product it loads onto trucks for shipment to customers.

In this legacy supply chain, none of the business units can share data. The textile plant manager may order more raw materials from the supplier. But he might not know how much remains in stock at the warehouse. This may result in an oversupply or a shortage of raw materials. The sales and marketing team won’t know how much finished product sits on shelves in the warehouse. That may cause orders for much more product than customers need or want. It could leave the organization with a costly level of excess inventory. The organization may miss big sales when it can’t meet customer demand caused by an inventory shortage. A lack of raw materials to fill orders could compound the problem.

Without analytics, the organization can’t order enough raw materials for times of high demand. The human cost could come if manufacturing plant workers had their hours cut if the inventory excess inventory grows too large.

Every step lacks input from marketing or checks on the remaining product in inventory with the warehousing unit.

Digitization Creates Opportunities for Collaboration

Digitization opens avenues for collaboration within the organization. By using AI and blockchain the network tracks every step of the product. Data collection starts with the raw materials purchase and along every step through production at the textile plant. It continues with inventory controls, logistics and delivery of the product to customers.

Users from every business unit can track every stage in the supply chain. This enables anyone to prevent bottlenecks by foreseeing operations at every step in the supply chain.

Through integration of machine learning the system understands the road map. This enables it to predict the future needs of the organization. Use of ML allows them to factor in pricing, man-hours, equipment use, demand and other variables. And it returns predictive analytics to supply these answers.

A digital supply chain system can help organizations:

  • Cut costs
  • Forecast demand
  • Optimize processes
  • Reduce wasted time, and
  • Improve customer experiences.

How to Harness IoT to Digitize the Supply Chain

By implementing a digital supply chain system, an organization can realize efficiencies and cut costs. Successful implementation depends on careful attention to every part of the process. Every business unit in the organization needs to take part in the implementation and use of the new supply chain system.

Prescriptive Analytics Reveals Upcoming Bottlenecks

Legacy systems follow a linear approach to the supply chain. Each step in the supply chain gets separate attention, with few or no links to other steps. That means no one has a view of the big picture, which makes planning nearly impossible.

In our textile manufacturer example, the process starts with the purchase of the raw materials. It continues step-by-step through to delivery of the finished product. No interconnection occurs.

What the organization needs is an overview of the entire supply chain. This enables the organization to connect product orders to raw materials in stock. That assures enough raw materials are on hand to meet the needs of the manufacturing plant. The plant can then respond in a timely fashion to product orders from the sales and marketing business unit. When a customer makes an order that requires the linen, the organization meets the demand on time and delivers it where the customer wants it.

Establishing this value cycle embraces a non-linear approach to optimize the entire supply chain. By creating touch points across the supply chain it improves business processes. This increases productivity and profits.

The integration of all processes into this non-linear approach allows planners to account for external factors to focus on shorter delivery times. They can allocate delivery trucks and vendors to meet production and time to market commitments.

Predictive analytics in the new supply chain system enables them to make plans that minimize unexpected events and clears bottlenecks sometimes before they begin. That makes creating and following budgets easier to do.

The organization achieves this by integrating AI, big data and machine language to continuously learn from existing uses cases. By tracking every entry point at every stage in the process, the system can reveal every roadblock and bottleneck in the process. It can even predict the cost each bottleneck would create if it wasn’t resolved. That adds more proof of the ROI gained by implementing the digital supply chain management system.

Digitization Realizes On-Demand Sourcing Efficiencies

Manufacturers need raw materials to create their products. Keeping a steady supply of raw materials on hand as it’s needed is a key factor in delivering finished products to customers.

This also makes establishing suppliers for those materials integral to the supply chain. Updating to a digital supply chain system helps an organization establish and track relations with a variety of suppliers. The integration of SaaS based operations enables the organization to track materials from each vendor. It also makes it possible to confirm the quality of the materials.

By adopting this new system, the organization can adopt a just-in-time inventory system. Orders for raw materials occur only to meet production demand. The systems enables the organization to forecast demand, preventing bottlenecks.

Short production runs allow manufacturers to quickly move from one product to another. That cuts costs by minimizing warehouse needs. The organization also spends less on raw materials because they buy only enough to manufacture the products ordered.

Contrast this with the legacy just-in-case ordering strategies. In these, an organization keeps enough inventory on hand to deal with the greatest possible market demand. This strategy forces the organization to keep large amounts of inventory on hand and untouched. A large order could deplete even this supply. That would leave the organization unable to cope with even smaller orders until it receives more raw materials.

Adopting this on-demand materials sourcing can seem costly. It requires the purchase and maintenance of sensors, trackers and the software to make use of them within the supply chain. But the greater efficiencies and customer satisfaction assure an ROI that makes it worthwhile.

Smart-Warehousing Creates Efficient Product Flow

Early adopters of supply chain management digitization take advantage of smart warehousing. This enables warehouse managers to track the location of inbound and outbound trucks. They can schedule arrivals, allocate space for storage and assign robotic or human resources needed to move and store goods and materials until needed.

When an inbound truck shares its location, the warehouse creates a manifest for tracking purposes. The system stores data on the truck’s arrival time and if that differs from its scheduled arrival. It slots a parking space as necessary and allocates loading dock space. The system designates the workers or robots required to move the goods and how long they’ll be in the warehouse. This helps the organization to efficiently use space, manage resources, and cut costs by predicting the movement of raw materials.

Sharing this data through the blockchain alerts the manufacturing team about the next shipment of raw materials. It tracks and alerts business units on the time of delivery and expected volumes to meet market demands.

Organizations realize cost reductions by digitizing these processes with barcodes. That improves logistics, including enabling the use of robotics. Use of this shared network delivers cost reductions, efficient management of storage space and of human resources.

Digitization Enables Efficient Fleet Maintenance

Organizations have seen few changes to logistics systems before digitization. Many large organizations have yet to add predictive analysis to forecast future logistics needs. That makes them unable to react to external factors. They’ll feel the effects of bad weather conditions, human interactions and other variable elements.

Big data and machine learning brings digitization to logistics. This helps create efficient spare part management for organizations’ existing vehicle fleets and machinery. The digitization empowers them to predict the resources required to maintain their fleets. This reduces costs and ensures timely deliveries.

Early Adoption Gives Organizations an Edge over Competitors

Besides these examples, many other ways exist to use ML, IoT, blockchain, and big data to digitize a supply chain. Not all systems are perfect. It might take a considerable amount of time to convert to a functional digitized supply chain and realize its full potential.

But early adoption gives organizations the edge required to be pioneers. And that edge can make them leaders in their industries.