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orchestration
November 4, 2025
Unifying Real-Time Data for End-to-End Supply Chain Orchestration
Special guest post written by Chris Cunnane with InterSystems Supply chain orchestration is the coordinated management of end-to-end supply chain activities, across planning, sourcing, production, logistics, and delivery, using technology, data, and processes to ensure that every moving part works together seamlessly. It enables organizations to attain an agile and resilient supply chain model through the use of decision intelligence. This is achieved through the See > Understand > Optimize > Act framework, which gives organizations the confidence to plan and respond to disruptions with assurance in their supply chain stability. See: gather raw data and information from your environment or a situation. Understand: analyze the information you’ve seen to build a comprehensive understanding of the context, your knowledge, and potential complexities. Optimize: develop the best possible solution or course of action to address the situation. Act: implement your chosen solution, putting your knowledge into practice. From a practical standpoint, this framework powers your supply chain application ecosystem with end-to-end visibility, insights, and better decisions. It helps organizations reach their supply chain goals by enabling them to align processes, stakeholders, and technology toward desired outcomes. The end result is reduced costs, improved operating margins, and optimized sustainability decisions, among others.…
travel
August 21, 2025
Hire, Onboard, Manage: Treating AI Agents Like New Team Members
Special Guest Blog Post written by Deborah Dull Imagine it’s launch season in your supply chain, and a team of AI agents is hard at work: coordinating shipments with suppliers, allocating inventory, and handling a missed delivery. It’s hard to go a day without hearing about the latest AI headlines: new LLMs, new applications, new use cases. These discussions are part of my every day. Business leaders and IT teams are eager to explore – and they have a lot of questions… and apprehension. In these discussions, we have found one framework that lands consistently: consider AI agents like new hires, not new software. Step 1: Hire Like You Mean It Just like hiring humans, this step is about defining what you need. The first decision is the purpose of the role: what problems are you trying to solve? Where are your people overwhelmed? Where is your business growing in coming months? From here, the next decision is to build the business case just like you would for a new headcount. For example, consider the ROI of having a digital employee who can process supplier performance data 24/7. Now, decide on the type of agent that will join…