Supply chain management is the handling of the entire production flow of a good or service — starting from the raw components all the way to delivering the final product to the consumer. A company creates a network of suppliers (“links” in the chain) that move the product along from the suppliers of raw materials to those organizations that deal directly with users.
According to CIO, there are five components of traditional supply chain management systems:
Planning
Plan and manage all resources required to meet customer demand for a company’s product or service. When the supply chain is established, determine metrics to measure whether the supply chain is efficient, effective, delivers value to customers and meets company goals.
Sourcing
Choose suppliers to provide the goods and services needed to create the product. Then, establish processes to monitor and manage supplier relationships. Key processes include: ordering, receiving, managing inventory and authorizing supplier payments.
Manufacturing
Organize the activities required to accept raw materials, manufacture the product, test for quality, package for shipping and schedule for delivery.
Delivery and Logistics
Coordinate customer orders, schedule deliveries, dispatch loads, invoice customers and receive payments.
Returning
Create a network or process to take back defective, excess or unwanted products.
Effective supply chain management systems minimize cost, waste and time in the production cycle. The industry standard has become a just-in-time supply chain where retail sales automatically signal replenishment orders to manufacturers. Retail shelves can then be restocked almost as quickly as product is sold. One way to further improve on this process is to analyze the data from supply chain partners to see where further improvements can be made.
By analyzing partner data, the CIO.com post identifies three scenarios where effective supply chain management increases value to the supply chain cycle:
- Identifying potential problems. When a customer orders more product than the manufacturer can deliver, the buyer can complain of poor service. Through data analysis, manufacturers may be able to anticipate the shortage before the buyer is disappointed.
- Optimizing price dynamically. Seasonal products have a limited shelf life. At the end of the season, these products are typically scrapped or sold at deep discounts. Airlines, hotels and others with perishable “products” typically adjust prices dynamically to meet demand. By using analytic software, similar forecasting techniques can improve margins, even for hard goods.
- Improving the allocation of “available to promise” inventory. Analytical software tools help to dynamically allocate resources and schedule work based on the sales forecast, actual orders and promised delivery of raw materials. Manufacturers can confirm a product delivery date when the order is placed — significantly reducing incorrectly-filled orders.
The supply chain is the most obvious “face” of the business for customers and consumers. The better and more effective a company’s supply chain management is, the better it protects its business reputation and long-term sustainability.
IDC’s Simon Ellis in The Path to a Thinking Supply Chain¹ defines what is supply chain management by identifying the five “Cs” of the effective supply chain management of the future:
- Connected: Being able to access unstructured data from social media, structured data from the Internet of Things (IoT) and more traditional data sets available through traditional ERP and B2B integration tools.
- Collaborative: Improving collaboration with suppliers increasingly means the use of cloud-based commerce networks to enable multi-enterprise collaboration and engagement.
- Cyber-aware: The supply chain must harden its systems and protect them from cyber-intrusions and hacks, which should be an enterprise-wide concern.
- Cognitively enabled: The AI platform becomes the modern supply chain's control tower by collating, coordinating and conducting decisions and actions across the chain. Most of the supply chain is automated and self-learning.
- Comprehensive: Analytics capabilities must be scaled with data in real time. Insights will be comprehensive and fast. Latency is unacceptable in the supply chain of the future.
Many supply chains have begun this process, with participation in cloud-based commerce networks at an all-time high and major efforts underway to bolster analytics capabilities.
While yesterday’s supply chains were focused on the availability, movement and cost of physical assets, today’s supply chains are about the management of data, services and products bundled into solutions. Modern supply chain management systems are about much more than just where and when. Supply chain management affects product and service quality, delivery, costs, customer experience and ultimately, profitability.
As recently as 2017, a typical supply chain accessed 50 times more data than just five years earlier. However, less than a quarter of this data is being analyzed. That means the value of critical, time-sensitive data — such as information about weather, sudden labor shortages, political unrest and microbursts in demand — can be lost.
Modern supply chains take advantage of massive amounts of data generated by the chain process and are curated by analytical experts and data scientists. Future supply chain leaders and the Enterprise Resource Planning (ERP) systems they manage will likely focus on optimizing the usefulness of this data — analyzing it in real time with minimal latency.
With IBM Services, you can evolve your supply chain processes into intelligent workflows, to reach new levels of responsiveness and innovation. Challenge siloed processes to uncover efficiencies, enable your teams to execute and deliver, and use emerging technologies like AI and blockchain to unlock opportunities in every step of the value chain — from demand planning to order orchestration and fulfilment.
1 The Path to a Thinking Supply Chain (PDF, 1.5 MB), Simon Ellis & John Santagate, IDC Technology Spotlight, August 2018