Improving visibility to increase supply chain resiliency with AWS Supply Chain

Global economic, environmental, and social factors are still disrupting supply chains. This limits organizations’ ability to meet customer demand and manage operational costs. While supply chain issues are attributed to a variety of causes, the lack of supply chain visibility is at the top of the list. Research by Gartner found that improved supply chain visibility streamlines operations, boosts profitability, and elevates customer experience.

Supply chain related data is often scattered across disparate systems, including common sources such as spreadsheets. Traditional approaches use multiple reports tuned for a particular functional area or an approach with individualized platforms for order visibility, transportation visibility, etc. Both approaches slow customers down because of the manual effort needed to integrate disparate systems. Feedback from customers indicates two common challenges:

• Customers invest significant resources and money in consolidating data from various formats and maturity levels or assimilating information from sources such as spreadsheets.
• These custom integrated data solutions quickly become outdated and inaccurate.

To improve resilience, organizations must shift from reacting to a patchwork view of the past to anticipating the future based on comprehensive visibility of their supply chain operations.

This post explores the key supply chain visibility challenges faced today and how to improve visibility with AWS Supply Chain. You also learn how AWS Supply Chain can help you do the following:

1. Efficiently meet customer demand.
2. Improve market and environmental response agility.
3. Minimize operational costs of inventory, resources, etc.
4. Increase profitability.

Supply chain visibility challenges

Supply chains rely on connected functions such as demand planning, replenishment planning, transportation, and execution management. Ideally, these functions would interoperate seamlessly and harmoniously, but when we examine traditional approaches, we observe that interconnectivity is lost. Effective supply chain visibility means more than having a view of information or the ability to retrieve a status. Effective visibility means fast and predictive awareness that enables agile decisions.

Consider a simple multitier supply chain managing the flow of goods from suppliers to the rest of the supply chain. The following diagram depicts the supply chain of a retail store, which is a pyramid-like arrangement of suppliers, manufacturing facilities, distribution centers, and stores. The diagram shows a workflow of finished goods from suppliers to distribution centers, then to stores and another workflow of raw materials to a factory or manufacturing facility, to distribution centers, and then to stores.

Issues such as a delay notice for a supplier purchase order (PO) can cause a shortage at a key distribution center or at a factory, which could subsequently lead to stockouts at stores. This can lead to lower customer service levels and lost revenue. There are many other examples of supply chain issues that can disrupt performance, but awareness of issues before they cascade throughout the supply chain can help you stay ahead of problems.

Having integrated visibility allows you to quickly identify individual issues and associated impact. Improved visibility of the supply chain enables you and your team to quickly identify and address the far-reaching implications of any disruptions. This prevents poor customer service levels, increased costs, strained supplier relationships, disrupted production schedules, and potential loss of business.

Embracing enhanced visibility can accelerate disruption detection, improve your reaction times, and ultimately lead to better mitigation plans.

Access to information about other distribution centers, warehouses, and stores can help to identify possible re-balancing options. If a solution is found, coordination with other supply chain groups helps determine the best rebalancing options. This proactive approach can save time and prevent disappointed customers, lost revenues, and increased costs from ineffective alternatives solutions, such as using alternate suppliers or paying expedite shipping fees.

Improving Visibility with AWS Supply Chain

AWS Supply Chain is an end-to-end business application offering enterprise-wide visibility and actionable machine learning (ML) enabled Insights. Visibility and ML-powered intelligence improve your ability to identify and resolve impending supply chain related problems and increase supply chain resilience.

AWS Supply Chain serves as an intelligent layer that sits on top of existing functional systems such as Enterprise Resource Planning (ERPs), Order Management System (OMS), Warehouse Management System (WMS), Transportation Management System (TMS), and other data sources. Once data is ingested, the application uses ML models to render a view across your supply chain.

Data is contextualized and loaded into a supply chain data lake (SCDL) in the form of visual maps, enabling you to track your supply chain health. The following screenshot of the visual map available on AWS Supply Chain shows a map of the United States with an example supply chain spread across different locations. The map shows current inventory health, potential risks, and supply chain risks at all the locations. This dynamic map uses a color-coded donut graph to depict the health of each location. The individual donut graphs identify the percentage of the inventory that can support the demand and the percentage at risk.

AWS Supply Chain replaces the traditional approach, which requires consolidation of different data sources and manual creation of a unified view. This task can be time-consuming and provide only a snapshot of the inventory levels at the time data was first extracted. By the time you view the state of the supply chain, the information is likely obsolete.

The maps and views in AWS Supply Chain refresh as the source data refreshes. This maintains visibility without any manual intervention. You save processing time, get faster updates, and reduce the risk of data inaccuracies.

If you want a closer look, you can examine the warehouses, distribution centers, or stores to evaluate the supply chain health of that location. As in the map view, you see a color-coded depiction of the health of the location and a projection of the ability to support demand. This view shows inventory on-hand, inventory in transit, and inventory that might be at risk.

AWS Supply Chain analyzes supplier lead times and uses ML to predict future lead times. The lead time projections are then compared to on-hand inventory, open customer orders, and product forecasts to identify any potential problems. If issues such as inventory stockouts or overstock situations are identified, AWS Supply Chain uses ML algorithms to generate inventory rebalancing options to mitigate supply chain risks.

AWS Supply Chain evaluates other locations within your supply chain and automatically evaluates, ranks, and shares multiple rebalancing options for you to consider. The following screenshot depicts the system-generated recommendations and the scoring of each option. The recommendations screen shows a color-coded list of options that receive a score based on the percentage of the risk resolved, the distance between facilities, and the sustainability impact, which includes data on CO₂ emissions, for example. The colored boxes depict the future effect of the rebalance and potential issues that the rebalancing actions may cause. This view empowers you to balance potential risks quickly without jeopardizing other locations.

Future resolution and recommendations are also improved based on rebalancing decisions, so AWS Supply Chain learns and adapts to your preferences and decisions. You can also create watchlists by location, type of risk (such as stockouts and excess stock risks) to help you focus on specific locations, targets, or key business areas. This improves risk detection and your ability to accelerate risk mitigation decisions.

Conclusion

AWS Supply Chain increases supply chain resiliency by improving supply chain visibility. AWS Supply Chain simplifies many manual tasks and reduces unproductive time that’s normally required to determine supply chain health. You benefit from faster detection times and response times made possible by improved visibility, while ML detects supplier lead time anomalies, improves planning, and enables effective risk mitigation actions. Continuous and improved supply chain visibility helps you identify bottlenecks and potential disruptions, while accelerated decision-making allows you to quickly mitigate potential issues without impacting operations.

These improvements increase your supply chain resiliency by allowing you to effectively address customer demands, adapt to market and environmental changes, and reduce operational expenses. Visit AWS Supply Chain to learn more and get started, then visit the AWS Workshop Studio for a self-paced technical overview.