Supply Chain Control Tower
Assembly Line
Optimize Your Supply Chain Processes with Generative AI on AWS
AWS Artificial intelligence (AI) and Machine Learning (ML) capabilities help streamline procurement processes end-to-end, including automating PO generation and approval, and facilitating the invoice-to-payment workflow.
AWS generative AI can make generating and approval of POs more intelligent. It can automatically draft a PO based on supplier catalogs by generating contextual details such as item descriptions, quantities, delivery timelines, and terms. The orders are then automatically routed to an approval workflow. Invoice processing automation using ML capabilities streamlines extraction of invoice data such as line items, quantities, and amounts from scanned or emailed invoices. This data is fed into a data integration pipeline to automatically match invoices to POs and route them for automated review and approval.
The optimized procurement process reduces manual PO creation and matching checks, reduces errors, and ensures orders are placed based on up-to-date data and business constraints. This significantly reduces manual data entry, accelerates invoice-to-pay cycles, and ensures compliance with procurement controls, creating a seamless and efficient system.
Renault Group Acquires a Supply Chain Control Tower to Manage Transportation in Europe and Beyond
In 2020, Renault teamed up with Shippeo, a provider of software for multimodal transportation visibility, along with Google’s artificial intelligence model, to create the first control tower for the automotive industry in Europe. The application employs AI modules fed by real-time traceability data from logistics providers and production stock, along with other sources of news. The resulting support tool gave operational teams end-to-end coverage of operations on a global basis.
By the first half of 2021, 80 of Renault’s carriers had connected to Shippeo’s transportation visibility platform. The first version of the control tower for inbound deliveries went live in October of 2022, covering parts transportation by truck throughout Europe, the Middle East and North Africa. Outbound carriers were added shortly thereafter. As of January 2023, Renault had also integrated the tracking of 100% of its maritime transport services.
The control tower allows for a real-time link between parts transportation and vehicle production. Drawing on AI and machine learning from Google, the system calculates accurate estimated times of arrival, accounting for variables such as weather, strikes, border-crossing delays and traffic levels. The analysis helps it to detect potential disruptions early on, sharpening Renault’s crisis-management strategies and making possible mitigating efforts such as truck rerouting and acceleration, and transshipment of critical parts.
According to the automaker, the Shippeo application has led to “remarkable enhancements” in service levels for the transportation of parts from suppliers to the plants, while also improving safety and fostering global collaboration with supply chain partners. Tracking accuracy is based on a detailed analysis of GPS data, and weekly animation of the automaker’s 10 major carriers in the European region. At the factory, the tool has taken 15 minutes out of an average waiting time of 90 minutes for trucks, Renault added.
Unwrapping Hershey’s $250M manufacturing upgrade
The investment aims to digitize and automate Hershey’s processes, optimize procurement and manufacturing, and accelerate R&D and planning to boost visibility and streamline operations. Through the initiative, Hershey will be able to better integrate demand planning and bring more automation to the supply chain.
The lack of visibility prompted Hershey to unify its new business units under a single umbrella through an ERP integration using software provider SAP’s S/4 platform. “S/4 was an important foundation,” Buck said at CAGNY. “It enables us the end-to-end connectivity to better identify where there’s redundancy and take that and complexity out of our system.”
Technology is a pillar of Hershey’s current strategy, and the company appointed its first-ever chief technology officer in 2023. Deepak Bhatia came to Hershey after 12 years at Amazon, where his most recent role was VP of supply chain optimization technologies.
Visibility and real-time data also allow plant managers to proactively maintain lines, advancing the initiative’s goal to optimize manufacturing. Data analytics could reveal the best times to clean equipment so it doesn’t interfere with a production run, or when to replace a part before it breaks and causes longer-term issues.
The AAA initiative is slated for completion in 2026. From there, Hershey expects to save $300 million annually, with 30% of the savings from supply chain productivity. This year alone, Hershey expects to save $100 million, with $10 million coming from supply chain savings and the remainder from SG&A.
Modine Builds Supply Chain Resiliency Through Technology
Modine specifically identified the ability to optimize materials and manage its supply chain with predictive analytics and prescriptive execution recommendations as vital to digitally transforming its supply chain. To meet these goals, the company implemented LeanDNA, an intelligent supply chain execution platform.
The partnership between Modine and LeanDNA successfully addressed chronic part shortages and inconsistent deliveries. It introduced a supplier fulfillment control tower, establishing a structured framework and processes and enhanced communication. This project resulted in tangible and significant improvements, setting up the team to continuously improve and optimize their supply chain.
Modine’s fast-track implementation of LeanDNA was completed within a record time of under two months. Modine’s eagerness to digitize the supply chain execution process has positioned them for strong results that can be built on as the team continuously optimizes with LeanDNA.
Manhattan Redefines Supply Chain Planning for the Modern Age
Manhattan Active Supply Chain Planning is the first and only solution unified with supply chain execution to eliminate systemic and operational silos, unlocking enterprise-wide optimization for the entire inventory assortment and all the resources required to flow it through the supply chain. From inventory and labor to distribution and transportation, all elements are synchronized and harmonized in real-time, seamlessly united under a single plan.
Manhattan Active Supply Chain Planning harnesses the power of AI to combine external data sources with internal patterns to produce more accurate and actionable demand forecasts. This innovative solution is capable of ingesting and rapidly processing vast amounts of syndicated data from external sources, such as influencer activity, industry-specific data sources, and localized data, all of which can influence and shape demand.
How Chemicals Supplier BYK Harmonized Supply Chain Planning Processes
BYK is a leading global supplier of specialty chemicals. The company’s innovative additives and differentiated solutions optimize product and material properties as well as production and application processes. Amongst other products, BYK’s high-performance additives improve scratch resistance and surface gloss, the mechanical strength or flow behavior of materials, and properties such as UV and light stability or flame retardancy. BYK also produces measuring and testing instruments that serve to effectively assess appearance and physical properties.
BYK found that the SAP Integrated Business Planning application for demand, a cloud-based application with comprehensive capabilities, could best meet its goals to harmonize demand planning processes across the organization and improve forecast accuracy. In addition, the company decided to use the SAP Supply Chain Control Tower solution, enabling the company to get real-time visibility and control over its supply chain.
Blue Yonder Announces Binding Agreement To Acquire One Network Enterprises for Approximately $839 Million To Create Multi-Enterprise Supply Chain Ecosystem
Blue Yonder, a leader in digital supply chain transformations, continues its forward momentum to revolutionize the supply chain and has announced the signing of an agreement to acquire One Network Enterprises (One Network) for approximately $839 million, subject to adjustments. One Network, provider of the Digital Supply Chain Network™, is known for its autonomous and resilience services and is a leading global provider of intelligent control towers. Upon completion, Blue Yonder will be well positioned to serve customers’ needs across planning, execution, commerce, and networks.
⛓️🧠Multinationals turn to generative AI to manage supply chains
Navneet Kapoor, chief technology officer at Maersk, said “things have changed dramatically over the past year with the advent of generative AI”, which can be used to build chatbots and other software that generates responses to human prompts.
New supply chain laws in countries such as Germany, which require companies to monitor environmental and human rights issues in their supply chains, have driven interest and investment in the area.
⛓️ A guide to supply chain control tower use cases
At a high level, we assume that the control tower receives a broad range of data from 1st and 3rd parties, and integrates with a number of operational systems, such as the system for warehouse management, and provides four categories of capabilities:
- Strategic planning. Decision support tools that are focused on long-term, often multi-year, time horizons.
- Inventory visibility. Near real-time insights and alerts that support ongoing operations.
- Inventory flow control. Decision automation tools for ongoing operations such as replenishment.
- Impact analysis and resolution. Tools for reacting to disruptions and deviations from planned scenarios.
The revenue-at-risk assessment is followed by the development of mitigation strategies. In particular, the company can change suppliers of certain parts or modify product designs to reduce the risks. Such decisions are supported by risk evaluation tools that allow one to assess the current risks and perform what-if analysis for alternative scenarios.
🧠How a Data Fabric Gets Snow Tires to a Store When You Need Them
“We were losing sales because the store owners were unable to answer the customers’ questions as to when exactly they would have the product in stock,” said Ehrar Jameel, director of data and analytics at ATD. The company didn’t want frustrated customers looking elsewhere. So he wanted to create what he called a “supply chain control tower” for data just like the ones at the airport.
“I wanted to give a single vision, a single pane of glass for the business, to just put in a SKU number and be able to see where that product is in the whole supply chain —not just the supply chain, but in the whole value chain of the company. ATD turned to Promethium, which provides a virtual data platform automating data management and governance across a distributed architecture with a combination of data fabric and self-service analytics capabilities.
It’s built on top of the open source SQL query engine Presto, which allows users to query data wherever it resides. It normalizes the data for query into an ANSI-compliant standard syntax, whether it comes from Oracle, Google BigQuery, Snowflake or wherever. It integrates with other business intelligence tools such as Tableau and can be used to create data pipelines. It uses natural language processing and artificial intelligence plus something it calls a “reasoner” to figure out, based on what you asked, what you’re really trying to do and the best data to answer that question.