Supply Chain Control Tower

Assembly Line

Manhattan Redefines Supply Chain Planning for the Modern Age

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🔖 Topics: Supply Chain Control Tower

🏢 Organizations: Manhattan Associates


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.

Read more at Business Wire

How Chemicals Supplier BYK Harmonized Supply Chain Planning Processes

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🔖 Topics: Supply Chain Control Tower

🏢 Organizations: BYK, SAP


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.

Read more at SAP News

Blue Yonder Announces Binding Agreement To Acquire One Network Enterprises for Approximately $839 Million To Create Multi-Enterprise Supply Chain Ecosystem

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🔖 Topics: Supply Chain Control Tower

🏢 Organizations: Blue Yonder, One Network Enterprises


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.

Read more at Blue Yonder

⛓️🧠 Multinationals turn to generative AI to manage supply chains

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✍️ Author: Oliver Telling

🔖 Topics: Generative AI, Supply Chain Control Tower

🏢 Organizations: Unilever, Siemens, Maersk, Pactum, Walmart, Scoutbee, Altana Technologies


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.

Read more at Financial Times

⛓️ A guide to supply chain control tower use cases

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✍️ Author: Ilya Katsov

🔖 Topics: Supply Chain Control Tower

🏢 Organizations: Grid Dynamics


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.

Read more at Grid Dynamics Blog

🧠 How a Data Fabric Gets Snow Tires to a Store When You Need Them

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✍️ Author: Susan Hall

🔖 Topics: Supply Chain Control Tower, Data Architecture

🏢 Organizations: American Tire Distributors, Promethium


“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.

Read more at The New Stack