Operational intelligence for manufacturing
Find hidden
capacity in
your data.
Production data can show where time, output, and money are being lost. PMnE IQ turns your existing records into a focused review of what needs attention and what to investigate next.
From reports to decisions
Know what
to work on next.
Orders, confirmations, schedules, and scrap records rarely agree on their own. We bring them into one operating picture, check the assumptions, and trace losses back to the work center and cause.
What happened?
What did it cost?
What should we check?
Bring existing
Map fields and
plant rules
Validate the
numbers
Rank the
opportunities
Decide what
to do next
Your data first.
Your plant's rules.
Specific decisions.
Work already built
Tools shaped by plant problems.
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Production Schedule_Auto
A production schedule view built around existing order data.
Discuss this product →OT + CAPACITYLIVE
87% LOAD126HOURS03RISKS
OT & Capacity Planner
Compare planned load with available time to support OT decisions.
Discuss this product →LPA GENERATORWEEK 38
18ASSIGNED14CLOSED04OPEN
LPA Generator
Organize assignments, follow-up, and overdue audits.
Discuss this product →
Ops Finance Tracking
Bring spending and operating context into the same review.
Discuss this product →A focused first engagement
Find the loss.
Choose the action.
Start with a capacity and schedule execution review using records your team already has. We identify where output diverges from plan, test likely causes, and put the highest-value questions in front of your managers.
The first step is a scoped pilot with your data and plant rules. We review the findings with you before treating any estimate as an opportunity.
Discuss a pilot →
What the review is designed to answer
01
Where did planned output and actual output separate?
02
Which work centers, shifts, or part families account for the gap?
03
How much time or cost might be recoverable, and how confident are we?
04
What should the team verify or change first?
Bring the data you have
Production orders, schedules, confirmations, work centers, rates, and scrap are useful starting points. CSV and Excel exports can begin the conversation; a live connection can come later.
Map the meaning
Column names vary by system. We map fields into a common manufacturing model, confirm shift boundaries and business rules, and flag missing or contradictory records.
Act on verified findings
Each opportunity should show its source, assumptions, estimated impact, and recommended next check. If the data cannot support a conclusion, we say so.
Start with the problem
Let's examine
your capacity gap.
Tell us the decision your team is struggling to make and which production records you can export. A discovery discussion can establish the scope, data requirements, and price of a pilot.
01The gapWhere does plan and actual performance diverge?
02The evidenceWhat exports and plant rules can explain the gap?
03The pilotWhat can we verify in a small, defined review?
What PMnE IQ is
Manufacturing data.
Operational decisions.
PMnE IQ is being built as a decision layer for manufacturers. It connects orders, work centers, schedules, confirmations, rates, scrap, and cost so a manager can examine a specific loss and its likely drivers.
The current focus is a guided capacity review. The longer-term aim is a repeatable model that can take exports from different systems, ask for the plant-specific rules it needs, and produce traceable recommendations.
Built on your existing systems. The analysis is only as reliable as its inputs and confirmed operating rules.
Use existing exports
Start with the records your plant can provide.
Confirm plant rules
Shift, calendar, and routing details change the answer.
Show the evidence
Trace findings to records and assumptions.
Prioritize a decision
Put the most actionable questions first.
Our history
Built from problems
I've lived.
PMnE IQ grew from years of trying to answer the same question manufacturing leaders face every day: How do we turn all this data into a better decision?
Chris Mowers Founder, PMnE IQ
I'm a business manager with a background in production, manufacturing, and operations management. While leading people, schedules, capacity, and performance, I found a knack for turning complicated operational data into clear dashboards, automated reports, and decision tools people actually use.
That practical work became PMnE IQ: tools shaped by real plant-floor needs, built to create visible value without forcing a company to start over.
I grew up and still live in South Central Minnesota. I'm also a proud father of four—Ariah, Ariaella, Addie, and Ahliam. Those roots keep my approach straightforward: listen carefully, solve the real problem, and earn trust by delivering something useful.