Is your team unsure how technology can revolutionize supply chain risk management? There’s nothing like real-life success stories to make the case for adopting a winning strategy. Check out our ten examples from Everstream clients to see how many ways supply chain risk management could help your organization adopt and streamline risk management practices for operational success.
SCRM example 1: Holistic supply chain view to avoid costs
By giving DuPont increased visibility into their supply chain, Everstream was able to help them proactively prevent risks and discover cost efficiencies. With several key business units that required monitoring, they were looking for a system that would allow all stakeholders access to critical supply chain information.
Everstream’s solution equips DuPont with a targeted risk assessment process and a supply chain incident monitoring platform, powered by AI. This gives DuPont clarity into the seven risk factors with most influence on their supply chains: strikes, power outages, telecoms outages, industrial fires, terrorist attacks, IT failures, and the financial stress of suppliers.
Everstream’s custom solution for DuPont ensures end-to-end supply chain visibility, automatically quantifies risk, and helps the risk management team make informed and proactive decisions to prevent disruptions and create efficiencies.
SCRM example 2: A proactive approach to supply chain risk
Cisco is a global IT leader that provides businesses around the world with hardware, software, and services used to run critical infrastructure. Aiming to continually improve their service operations performance, in line with their core values, DHL Service Logistics and Cisco approached Everstream for support on enhancing their network’s overall resilience to any event, major or minor.
Accordingly, Everstream’s platform supplies a thorough view into all operating locations and major freight lanes within the network, tracking them by geo-coding at the street address level. The platform uses AI to automatically provide details into any potential risks, including severity, allowing the Cisco team to make contingency plans and other strategic risk management decisions.
SCRM example 3: Resilience supports personnel and security
Andritz Group supplies and services complex, high-value plant equipment across several industrial sectors, often working in very remote and politically unstable regions around the world. To safeguard their deliveries and ensure the safety of their personnel, they turned to Everstream to provide continuous data and analytics, helping Andritz understand the scope of their risk exposure.
Everstream’s solution creates risk “heat maps” using a variety of data sources, giving Andritz an overall view into the risk exposure in a region. The platform also makes specific risks associated with locations clear, coded down to the street address level of individual sites. AI provides the analysis of this mountain of data, leaving the security team free to consider the analyzed data and make effective critical decisions.
Figure 1: Companies in manufacturing, chemicals, energy, and more rely on supply chain risk management from Everstream Analytics.
SCRM example 4: Driving down supply chain risk, strengthening resilience
Like many manufacturers, ZF uses airfreight, provided by DHL, as a last resort to avoid delivery delays or to maintain production schedules. As a result, any disruptions within the airfreight ecosystem became a crucial risk to ZF. Additionally, ZF was having trouble effectively communicating the potential impact of delays to automotive OEMs when delays occurred. Therefore, ZF and DHL Global Forwarding (DGF) began a joint pilot to minimize risk and maximize efficiency within ZF’s airfreight network, utilizing Everstream’s supply chain risk platform.
Everstream’s platform provided customized risk assessments and AI-powered supply chain monitoring capabilities, mapping the network from end-to-end and considering ZF and DHL’s specific and complex needs. For example, though DHL runs ZF’s airfreight network, ZF undertakes customs clearance between countries. Therefore, any rerouting must be done within the framework of ZF’s existing customs clearance brokers.
The pilot was very successful, and ZF was not only able to fully visualize and prioritize risks, but also able to easily communicate any potential impacts to their OEMs.
SCRM example 5: Critical cargo arrives on time
With hundreds of facilities, Google is responsible for shipping substantial amounts of high-value and time-critical hardware to strategic locations around the world. Delayed or lost in-transit hardware can throw entire projects into disarray or reveal proprietary information.
Everstream’s platform constantly collects real-time data from numerous external sources, collating incidents that could impact Google’s transportation network. By tracking Google’s in-transit inventory, AI can highlight which events may have critical outcomes and provides the Google team with actionable information.
By implementing this system, Google was able to provide logistics personnel, carriers, and internal customers faster and more accurate information, increasing on-time delivery. Additionally, Google was able to manage three major incidents over two months without disrupting wider operations.
SCRM example 6: Protection for temperature-sensitive products
Glanbia Performance Nutrition (GPN), a major division within Glanbia PLC, produces a variety of performance nutrition products across consumer sectors. After experiencing significant product losses due to freezing and melting, as well as complications with rail embargos and other supply chain disruptions, GPN needed to engage with logistics companies that provided temperature-aware transportation options.
Everstream designed a platform for GPN that supplies lane risk analysis, advanced weather forecasting, and shipping environment temperature data. The platform uses data analytics and AI to provide equipment recommendations in line with temperatures during a given shipment. As a result, GPN has been able to make proactive, weather-informed decisions, reduce transportation costs, and prevent spoiled products.
Figure 1: In this example, supply chain risk management software alerted clients of disruption 11 days before news media coverage.
SCRM example 7: Enhancing risk analysis tools and improving planning
A world-leading specialty chemicals company, Evonik Industries AG must keep a close eye on risks to maintain regulatory compliance and uphold their reputation. As a subscriber to and a champion of the values of the Responsible Care Initiative within the global chemical industry, Evonik aims to ensure the safety of all parties involved within their supply chains, especially where transporting or storing hazardous materials. Therefore, Evonik sought a comprehensive overview of the status of goods in transit, transportation risks and disruptions, and the ability to intervene with alternate solutions when necessary.
Everstream’s platform took Evonik’s existing supply chain data streams, drawing analysis from those and from Everstream’s database to create risk heat maps. The platform also provides continuous monitoring of Evonik’s supply chains, notifying the Evonik team of accidents, delays, strikes, and other disruptions. This allows Evonik to prioritize risk reduction activities and make quick and effective decisions in the face of an incident.
SCRM example 8: Keeping patient-critical supply chains running
A global medical device company manufacturing patient-critical products, Medtronic wanted to understand and minimize risks within their supplier network. Working with Everstream to map their entire supply chain, they discovered they had over 12,000 sub-tier suppliers for just a single product.
Everstream’s platform uses AI to highlight risks or disruptions that may occur within the multi-tier supply chain, from raw materials to manufacturing to shipping to clients. The company can then take appropriate actions, pivoting quickly to ensure that lifesaving or life-sustaining products only face minimal delays within the value chain.
SCRM example 9: Critical supply secured and shipped before first COVID-19 shutdown
At the beginning of the Covid-19 pandemic, Everstream’s platform alerted one customer, a Tier-1 automotive manufacturer, to an incident in a key factory in Wuhan, as well as limited air cargo capacity out of China. This automated alert, powered by AI and filtered through Everstream’s advanced analytics, led them to make an extraordinary maximum quantity one-time buy, shipped through the Russian rail system.
This decision-making process allowed them to secure key supplies ahead of a very serious disruption, ensuring their production could continue, and gave them a huge competitive advantage over other automotive companiesv who could only react to the incident after the fact.
SCRM example 10: Strengthening supply chain risk management and response
Schneider Electric uses Everstream’s platform to automatically receive real-time notifications of events that may impact global transport logistics. This streamlined system allows Schneider to get ahead of issues that could cause delays, giving them extra lead time to make critical mitigation decisions and re-route shipments as necessary. Schneider has noted that this has previously prevented over 100 major events from negatively impacting their logistics, and has improved their customer delivery predictability.
AI is a powerful tool when used for risk management. Everstream’s clients were able to make effective decisions, and often discovered other ways to increase operational efficiency. Combining the raw analysis power of AI with the oversight of humans, allows risk management teams to make quick, efficient, and effective risk management decisions.
Supply chain risk management can help any organization adopt and streamline their supply chain operations. We’ve provided ten examples of real-life success stories from our Everstream clients that demonstrate how SCRM can revolutionize supply chain operations, increase efficiency, reduce costs, and improve service. Whether you’re just getting started with SCRM or looking for ways to optimize your existing practices, take inspiration from these examples on how AI-powered analytics can take your supply chain risk management to the next level.
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Everstream Analytics sets the global supply chain standard. Through the application of artificial intelligence and predictive analytics to its vast proprietary dataset, Everstream delivers the predictive insights and risk analytics businesses need for a smarter, more autonomous and sustainable supply chain.What are supply chain risks examples? ›
- Global political unrest. ...
- Economy and inflation. ...
- Climate-driven disruptions. ...
- Non-compliance with ESG and related mandates. ...
- Cyber threats. ...
- Product, and raw materials shortages. ...
- Logistics risks. ...
- Demand volatility.
Everstream Analytics sets the global supply chain standard. Through the application of artificial intelligence and predictive analytics to its vast proprietary dataset, Everstream delivers the predictive insights and risk analytics businesses need for a smarter, more autonomous and sustainable supply chain.What is the role of AI in supply chain risk management? ›
AI-powered systems can continuously monitor and analyze supply chain data, providing real-time visibility into operations. By tracking key performance indicators, demand patterns, and supplier performance, businesses can quickly identify any deviations or potential risks.What are the 4 supply chain risks? ›
Supply Chain Risks Continue Mounting
Most of the risks that could disrupt your operations fall into four broad categories: economic, environmental, political and ethical. Examples of economic issues are a supplier going bankrupt, a recession or a work stoppage at a key manufacturing partner.
- Natural Resources. The supply of natural resources such as water.
- Materials. The production of materials such as steel.
- Ingredients, Parts & Components. ...
- Finished Goods. ...
- Retail, Ecommerce & Services. ...
- Customer. ...
- Returns, Reuse & Recycling. ...
- Distribution & Fulfillment.
- Strategy risk. This type of risk involves choosing the right supply management strategy. ...
- Market risk. Market risk involves your company brand, compliance, financial and market exposure. ...
- Implementation risk. ...
- Performance risk. ...
- Demand risk.
Supply chain management has five key elements—planning, sourcing raw materials, manufacturing, delivery, and returns. The planning phase refers to developing an overall strategy for the supply chain, while the other four elements specialize in the key requirements for executing that plan.What are the 3 key categories of supply risk? ›
Supply chain risk can be classified as operational, financial, regulatory, and reputational. These are very strong drivers for the adoption of more sustainable supply chain practices.How is AI used in supply chain? ›
Supply chain automation. Modern supply chain automation is not possible without AI. AI gives supply chain automation technologies such as digital workers, warehouse robots, autonomous vehicles, RPA, etc., the ability to perform repetitive, error-prone tasks automatically.
The Everstream is a massive, underground expanse in the New World, characterized by its winding rivers and hot pools of glowing magma and burning rock, contrasting the dark stone and occasional floor of water where the Stream meets the sea.What is AI powered supply chain? ›
AI in supply chain and logistics provides real-time tracking mechanisms to gain timely insights including the optimal times by where, when, and how deliveries must and should be made.What is an example of AI in supply chain? ›
AI can work with Internet-of-Things (IoT) sensor inputs to provide visibility into supply chains. For example, Roambee's AI-powered platform combines real-time IoT sensor information with data streams from carriers, ports, airport operations, rail lines, traffic reports, and weather forecasts.What are the problems with AI in supply chain? ›
Challenges of Implementing AI in Supply Chain Management
High implementation costs: Developing and integrating AI solutions into existing supply chain systems can be time-consuming and expensive. Companies must invest in infrastructure, training, and ongoing maintenance to fully realize the potential benefits of AI.
AI and machine learning can help companies accurately forecast demand, improve inventory management and reduce emissions and waste in their supply chains. One maritime transportation provider applied machine learning to existing historical data to create more reliable baseline probability forecasts.What are the 3 issues throughout the supply chain? ›
Shippers' Top 5 Supply Chain Challenges:
Keeping transportation costs down. Keeping up with customer/industry demands. Sourcing consistent, reliable carrier capacity. Keeping up with the latest technology solutions and demands.
Supply Risks: Supply risks occur when the raw materials your business relies on aren't delivered on time or at all, thereby causing disruption to the flow of product, material, and/or parts.