Supply Chain Control Tower
Assembly Line
⛓️🧠 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.