Modern-day supply chains no longer operate on supply chain management (SCM) alone. Companies use various systems to manage their supply chains efficiently.
For example, a warehouse management system (WMS) helps in managing the inventory and orders, and a transportation management system (TMS) optimizes freight movements. Similarly, the Enterprise Resource Planning (ERP) system oversees accounting and other core processes, and the Internet of Things (IoT) devices provide real-time data on vehicles and equipment.
Each system plays a significant role in enhancing supply chain operations. However, none of them can be effective if they operate in isolation. Companies need to stitch them together to gain a holistic view of the supply chain, its challenges, and untapped opportunities.
Unfortunately, most of these systems don’t communicate with each other due to compatibility issues and technical complexities. This prevents companies from unlocking the full potential of their supply chain operations, negatively impacting their business.
Take the example of a freight forwarder. They were constantly receiving calls from store managers about the delays in container deliveries. They had no visibility of the port of origin or final destination. This led to store managers facing challenges in replenishing stocks and adjusting promotions.
So, what’s the solution to this problem?
The answer lies in unifying these systems using AI. Let’s explore this more.
How Can CSCS’s AI-Powered Platform Solve The Data Silos Conundrum?
Integrating disparate legacy systems can be quite a challenge. That’s why companies need an AI-powered platform that would convert fragmented supply chains into profit engines.
Remember the freight forwarder we mentioned in the beginning? The company used CSCS’s AI-powered platform to integrate carrier EDI feeds, IoT sensors, and terminal updates directly into the customer’s ERP and planning systems.
Now, every time a container is delayed, the system updates the expected arrival dates automatically. This helped the store’s merchandising team reallocate inventory, avoiding a 18% loss in seasonal markdown costs, and save millions in revenue. It helped the store plan more effectively and stock the shelves before demand peaked.
Like the freight forwarder, companies can build leaner warehouses, predict demand better, and increase revenue using the CSCS AI-powered platform.
CSCS AI platform is an “integration-first” solution that combines agentic AI and real-time insights to optimize supply chains, enhance security, and provide measurable outcomes to companies.
It offers powerful features like:
1000+ Prebuilt connectors for leading platforms like SAP, Oracle, Infor, and Shopify.
Event-driven. orchestration for real-time supply chains.
A single-pane user dashboard to provide data visibility at every stage – from PO to delivery.
Centralized monitoring and error handling console for proactive issue resolution.
The platform can help companies:
Integrate legacy systems: CSCS provides real-time APIs, EDIs, JSON, and other flat-file connectors to facilitate seamless integration of legacy systems and enhance interoperability across various systems. This enables companies to unify data, reduce manual work, and make faster decisions.
Improve supply chain performance: CSCS merges Ops data and IoT to provide rich insights on live inventory, shipments, and asset status across different locations. It also offers an intuitive dashboard that allows companies to identify and resolve issues proactively.
Automate tasks: CSCS’s AI platform eliminates manual tasks and streamlines processes like transportation and inventory management. For example, it helps companies with route optimization or choosing the right carrier. Similarly, it automates tasks like picking and loading. By integrating the various systems, CSCS enables companies to forecast demand in real-time and plan for stockouts and excess inventory in advance.
Ensure security and data governance: Data security is one of the primary concerns when integrating different systems using AI. However, CSCS employs robust encryption methods and maintains robust data governance to ensure compliance and privacy. It also supports cloud-native and on-premise installations, making it easy for companies to manage security more efficiently.
Why Human-in-Loop Is As Crucial As Agentic Optimization
There is no doubt that agentic AI does all the heavy lifting to optimize supply chain operations. CSCS agentic AI, for instance, helps companies schedule appointments, operate warehouses, and do yard check-ins.
It can help companies with:
Optimizing routes by identifying disruptions and optimal routes, or proactively suggesting rerouting alternatives.
Balancing inventory based on dynamic conditions like order drops, demand fluctuations, supplier delays, and inventory movements.
Automating slots of SKUs based on usage patterns and other factors like seasons and locations.
CSCS Agentic AI is designed to proactively detect exceptions and changing scenarios and execute corrective actions to improve supply chain operations.
However, no agentic AI platform can operate independently without human supervision. The CSCS platform is especially designed to automate operational and data-driven tasks. However, it cannot make critical decisions like human experts. Human experts are still needed to validate and override specific AI recommendations to align with business needs.
Take the example of yard operations. An AI agent can do regular check-ins automatically, but human operators are still needed to approve or review the actions.
Besides augmenting processes, human intervention is necessary to provide learning feedback to AI models and refine them to improve their performance. It is essential to safeguard operational reliability in AI-driven supply chains.
How to Use AI To Unify TMS, WMS, ERP, and IoT
Transitioning from siloed to unified supply chain systems isn’t easy. It is not an overnight process. It has to be done in a phased manner. That’s why we recommend a 30-60-90-day approach to implementation instead of blind adoption.
In the initial 30 days, understand the pain points and start with a dedicated pilot project that’s dedicated to a specific process. Assess the current data quality, integration readiness, and resource capabilities before launching the AI pilot. Track KPIs, such as reduction in dwell times and error reduction, before and after AI implementation to monitor effectiveness.
If the pilot was successful, consider going live with the AI workflows, monitoring the KPIs, and iterating on the workflows to improve AI effectiveness.
Once the pilot proves to be successful, consider scaling it to other processes and operations. Ensure issues like data integration, change management, and business alignment are addressed. In this phase, track KPIs, such as cost reduction, delivery performance, and SLA adherence, to know the real impact. This is also the phase where establishing and maintaining data governance becomes crucial to improve AI’s effectiveness.
Conclusion
Most legacy enterprise systems are fragmented and tough to sync. CSCS transforms these fragmented systems into a unified, intelligent supply chain platform, enabling companies to reduce labor costs, expedite shipments, and enhance supply chain visibility.
For more information about our AI-powered platform, contact us.
Frequently Asked Questions (FAQ)
Q: Why is integrating TMS, WMS, ERP, and IoT important?
Integrating TMS, WMS, ERP, and IoT can help companies eliminate silos, improve real-time visibility of their supply chains, and enhance operational efficiency.
Q. How can AI unify different systems in the supply chain?
AI-powered platforms utilize features such as prebuilt APIs and connectors to integrate the various systems across the supply chain.
Q. Why is human-in-loop as important as agentic AI?
While agentic AI optimizes the various processes across the supply chain by integrating systems, it cannot function without human intervention. Human supervision is needed to make critical decisions, validate AI recommendations, and maintain AI’s reliability and accuracy.