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By Bill Murphy · Powered by Colony Spark |
THE OPERATIONS
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ISSUE #17 · JUNE 11, 2026 |
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Hi there,
AI agents are being sold as the layer that finally connects planning, procurement, production, finance, and customer communication. The catch is that they fail in exactly the places your operation has been quietly held together by tribal knowledge: undocumented handoffs, bad ERP data, the one person who knows when to break the rules.
This week I’m walking through six tools mapped to the seams where workflow debt actually lives — and what the platforms pushing the autonomous supply chain story are promising on top of all that.
— Bill
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AI Is Exposing the Workflow Debt.
The agents work where the workflow does. They fail where it doesn’t.
Manufacturers and distributors are hearing that AI agents can connect planning, procurement, production, finance, and customer communication. The operating reality is less glamorous: agents fail where the workflow is still undocumented, owned by one person, or dependent on bad ERP data and inbox handoffs.
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Where the agent breaks — three failure modes
· Incorrect ERP data. The agent acts on a master record nobody has cleaned in two years.
· Email-based coordination. The handoff lives in an inbox, not a system the agent can see.
· Unclear ownership. One person holds the logic for when to break the rules — and no one wrote it down.
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ERP and AI platforms are pushing autonomous supply chain promises, while operator conversations keep pointing back to the same three things: incorrect data, email-based coordination, and unclear ownership. The gap between the pitch deck and the shop floor is not a technology gap. It is a workflow debt that the agents are now exposing in public.
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The winners are not buying more AI. They are redesigning the work AI is supposed to touch.
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Foundational readiness
is the constraint.
Caleb Thomson of Gartner on why supply chain AI investment keeps bumping into the same wall
Caleb Thomson is Senior Director Analyst in Gartner’s Supply Chain Practice. Speaking at the Supply Chain Symposium/Xpo in Orlando in May, he put a clean read on a pattern operators have been describing in different words for the past year.
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“Persistent volatility is driving interest in evaluating AI-orchestrated capabilities, but investment remains constrained by foundational readiness. Even among leading supply chain organizations that have demonstrated success with performance gains and ROI on their AI investments, few have truly embedded AI into their core operations.”
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Read the second sentence carefully. Even the leaders, the ones with documented ROI, have not embedded AI into their core operations. That is not a capability gap. It is a readiness gap — the data, the workflows, the ownership model. The interest is real. The foundation is the part still under construction.
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The takeaway
The investment that pays off is not a bigger AI license. It is the unsexy cleanup work — documented workflows, clean master data, named owners — that lets the AI find solid ground when it lands.
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Why This Takes Six Tools.
Your operation wasn’t built in one system. It can’t be fixed by one.
Four foundation tools, two platform plays — mapped to the seams where workflow debt actually lives.
Orders arrive in your ERP. Someone decides whether you can fill them by checking a spreadsheet or sending an email. Purchasing reacts when inventory drops — in a separate system. Finance tracks cost somewhere else. Customer updates flow through a rep or a portal that talks to none of the above. And somewhere in there, one person holds the logic for when to break the rules.
Each of the six tools below maps to one of those seams. The tools aren’t the problem. The undocumented handoffs at each seam are. AI can only help at the seams if they’ve been mapped — which is exactly what this stack is designed to do.
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Part 1 · Before You Automate
Fix the foundation. Then invite the AI in.
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1. Scribe
Workflow Documentation / Workflow AI
Captures how work actually gets done — screen by screen — and turns it into step-by-step SOPs and process guides. Its newest products analyze those documented workflows and feed structured context directly to AI agents. Scribe’s benchmark data shows AI agents given unstructured knowledge performed 10% worse than baseline; agents given Scribe’s structured workflow data improved output quality by 71%.
Why it’s here: The workflow debt problem is literally their founding thesis.
Free tier available; Pro & Enterprise custom pricing. 600,000+ organizations, $1.3B valuation (Nov 2025). · scribe.how
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2. Trainual
SOP & Process Documentation
Turns your procedures, policies, and processes into searchable, assignable, trackable training manuals — with AI-assisted content building and built-in verification that people actually know the process.
Why it’s here: Before AI can touch a workflow, someone has to get it out of someone’s head. One of the most accessible on-ramps for mid-market teams to externalize tribal knowledge into role-assigned SOPs.
Starts ~$89/month for up to 25 users. SMB to mid-market. · trainual.com
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3. Celonis
Process Mining / Process Intelligence
Connects directly to your ERP, WMS, and transactional systems and reconstructs how processes actually run — not how you think they run — by mining event logs. Surfaces deviations, bottlenecks, and offline workarounds across procurement, order management, and production.
Why it’s here: If AI is supposed to automate a process, you first need to know what the process actually is — including every undocumented workaround. Customers like Molex use it to expose the gap between documented procedures and what’s actually happening in SAP.
Enterprise, custom pricing. #1 process mining vendor, 47.4% market share (2024). · celonis.com
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4. Syniti
ERP Data Quality / Master Data Management
Cleans, aligns, and governs master data across SAP and other ERP environments before AI systems are given access to it.
Why it’s here: AI is only as good as the data it touches. Syniti is the unsexy prerequisite for everything else on this list — SAP-recommended for manufacturers cleaning data before any AI migration.
Enterprise, custom pricing. · syniti.com
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Part 2 · What the Platforms Are Promising
Know what’s being sold before you buy it.
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5. Kinaxis Maestro™
Supply Chain AI / Autonomous Planning
End-to-end supply chain orchestration with agentic AI — agents can autonomously monitor, predict, and act on inventory, disruptions, and demand balancing in real time, not just surface recommendations.
Why it’s here: Kinaxis is one of the loudest voices pushing the autonomous supply chain narrative. If you want to understand where the promise is being made — and where it’s currently bumping into workflow debt reality — start here.
Enterprise, custom pricing. $391M ARR (Q2 2025). Gartner Magic Quadrant Leader. · kinaxis.com
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6. o9 Solutions
AI-Powered Supply Chain & Enterprise Planning
The “Digital Brain” platform — connects demand planning, supply, procurement, and finance in a single AI-driven environment using agentic and generative AI across the full planning cycle.
Why it’s here: o9 is making the same autonomous supply chain bet as Kinaxis, built for the large enterprise that wants to consolidate everything into one planning model. Worth watching to understand where this market is heading.
Enterprise, custom pricing. Targets Fortune 500 manufacturers and distributors globally. · o9solutions.com
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Buy the platform last. Document the workflow, clean the data, name the owner first. The agents reward the operators who did that work.
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THE OPERATIONS BRIEF
By Bill Murphy · Powered by Colony Spark
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Already running a workflow-documentation play before the agents arrive — or watching the AI hit the same wall everyone else is hitting? Hit reply, I read every one. Bill
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