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By Bill Murphy · Powered by Colony Spark |
THE OPERATIONS
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ISSUE #13 · MAY 14, 2026 |
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Hi there,
Operators are not short on data this year. They are short on trust in what their systems are telling them.
This issue is about the gap between what the report says and what is actually happening: why it has gotten more expensive in 2026, what it looks like when a team closes it, and the system your team can run starting Monday.
— Bill
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The System Trust Gap.
More dashboards will not fix it. Exception ownership will.
Manufacturers are not short on software. They are short on trusted operating signal.
The factory has ERP. Finance has reconciliation workflows. Supervisors have reports. Sales and customer service have CRM notes, inboxes, and dashboards. Each system produces a version of reality, and operators still have to answer the same old question every week: is this number safe enough to act on?
That question is more expensive in 2026 because the operating environment has compressed the time between signal and consequence. A material shortage discovered after the plan is locked triggers premium freight, production rescheduling, margin leakage, customer escalations, and another round of manual follow-up. A dashboard that shows inventory but cannot explain whether the plant can actually execute is not a decision system. It is another place to check.
The pattern is not "bad data" in the abstract. It is exception ownership. When the system says one thing and the floor says another, who owns the discrepancy? Who confirms the signal? Who updates the record? Who tells purchasing, production, finance, and the customer-facing team what changed? If that ownership is unclear, the team quietly rebuilds the business in spreadsheets, side conversations, and Friday afternoon panic calls.
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Three 2026 signals that make the gap visible
· 75% of supply plan failures happen at the factory execution stage, not in the planning model. 73% say their ERP can show required materials but cannot prevent execution failures. 93% report difficulty getting ERP visibility into actual execution outcomes (LeanDNA via CFOtech).
· 64% of manufacturers spend 10%+ of their manufacturing budget reacting to disruption: premium freight, emergency sourcing, last-minute schedule changes. 84% hit inventory shortages multiple times last year. 80%+ are also carrying excess inventory at the same time.
· Plants generating 50–100+ weekly reports are absorbing 25–75 supervisor hours/week on manual compilation, with 1–3% transcription error rates and reports arriving 4–8 hours old (iFactory 2026 reporting guide).
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The operating question for 2026 is not "how many reports do we have." It is "which reports are allowed to trigger action, and who is accountable when the report is wrong."
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The gap is not "do we have the data." The gap is "does anyone own the exception, reconcile the signal, update the record, and turn system output into a decision before trust erodes."
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Trust is not a reporting preference.
It is execution capacity.
Ryan Hosmer, Light Composites, on closing the gap between system record and floor reality
Light Composites is a 55-person aerospace and medical composites manufacturer in San Diego. Before they rebuilt their operating layer, the business ran on paper and Excel. GM Andy Hosmer described it plainly: "We were doing everything on a paper system and Excel spreadsheets. Somehow, we were able to hold it all together, but we could not scale." Shortages were being discovered through frantic vendor calls, not the system.
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"Recently, we did an inventory check, and we were within 97 to 98% of what the system says we should have. Eliminating stockouts has been a godsend. Because if you have the order but cannot ship it, you are not going to make money."
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This is the trust gap in operator language. The breakthrough was not adding a dashboard. It was getting the system record close enough to physical reality that the team could ship from it, forecast from it, trace quality through it, and plan capacity against it. Hosmer also noted the second-order effect: "We have a high degree of confidence that the material it says went into it actually did, and that the labor recorded actually happened."
When the system record matches the floor, the team stops working around it. That is what closing the trust gap actually buys you: not better reporting, but the ability to act on what the system says.
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The takeaway
98% inventory accuracy is not the headline metric. The headline is that the team now trusts the system enough to make decisions from it instead of working around it. Trust is not a soft outcome. It is the difference between shipping the order and missing the order.
Note: Light Composites story originally published by their software vendor and republished by Manufacturing.net. The quotes are from the operator about their own business, but the case study isn't independent reporting. Worth treating as directional, not benchmark.
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The Weekly Customer Health Pulse.
One owner for the signals your systems already have.
Not a dashboard someone has to remember to check. A decision packet with named owners, trigger reasons, recommended actions, and write-backs.
Most customer risk does not appear all at once. It leaks through small signals that live in separate systems. A support ticket stays open longer than usual. A reorder comes in late. A payment slips from 31 days to 47 days. A buyer who normally answers same day goes quiet.
The Weekly Customer Health Pulse is an agentic workflow that pulls those signals into one weekly exception list, and updates the system of record so the loop closes.
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What it pulls
· Support tickets: open count by account, aging by severity, reopened tickets, escalations, SLA misses
· Order behavior: order frequency vs. 13-week and 52-week baselines, missed reorder windows, partial shipments, backorders, canceled lines
· Payment timing: DSO by account, change vs. normal behavior, past due amount, short-pay or dispute notes
· Communication pattern: days since last meaningful touch, unanswered emails, negative sentiment in notes, new stakeholders appearing in threads, mentions of competitor, rebid, or vendor review
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Trigger logic
· Red: severe escalation + missed reorder window + no customer reply in 7 days
· Red: payment delay 15+ days beyond account norm + unresolved billing or delivery dispute
· Yellow: order frequency down 25%+ from 13-week baseline + support tickets 2x baseline
· Yellow: expected reorder missed 10 business days + buyer communication volume down 50%
· Watch: new stakeholder on 3+ threads while order volume or payment timing is slipping
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Weekly output, Monday morning
1. Top 10 accounts needing attention: name, status, owner, trigger reason, evidence, recommended action, deadline
2. Newly deteriorating accounts: what changed, and whether it's operational, financial, relationship, or mixed
3. Recovery accounts: which signal normalized, whether records were updated
4. Write-back queue: CRM tasks created, account status updated, AR notes added, owners notified
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The write-back queue is the trust layer. If the agent only summarizes risk, the team gets another report. If it updates the system of record and creates owner-specific tasks, the business gets a cleaner operating loop. That is the difference between this and the dashboards already sitting unread.
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Path 1: Internal build
Start with exports from help desk, ERP, accounting, CRM, and email metadata. Define 8–12 triggers. Run it manually for 30 days before automating any write-backs. The first win is not the AI. It is agreement on which signals count and who owns each exception.
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Path 2: ERP or partner
If customer, order, AR, and support data already live in the ERP ecosystem, build the pulse there. Use native alerts where possible, then add an agent layer for cross-system reasoning and task creation.
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The operating question isn't how many reports you have. It's which reports are allowed to trigger action, and who is accountable when the report is wrong.
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THE OPERATIONS BRIEF
By Bill Murphy · Powered by Colony Spark
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Working through your own version of the trust gap? Or wrestling with a question this issue didn't answer? Hit reply, I read every one. Bill
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