Epicor is moving 20,000 manufacturers to Kinetic Cloud. The migration vendor confirms your data loaded. Not that your key metrics still calculate the way they did before. I independently verify they survive the move, established to a recognized standard and documented so the result is defensible.
Epicor is moving its customers from on-prem to Kinetic Cloud. The migration vendor will confirm your data loaded successfully. That is true, and it is not the same thing as your metrics still calculating the way they did before.
When a system moves, the logic underneath your numbers moves with it. A metric is a definition computed over your data, and that computation lives in the system, not in the rows. Move the system and you have quietly moved the computation, whether anyone meant to or not. The number still populates. It still charts. It sits in the leadership deck exactly where it always sat. Usually nobody catches the drift until a figure is wrong in front of leadership.
I independently verify that a defined set of your most-watched operational metrics survive the move. Established to a recognized standard (ISO 22400 / SMRP), checked by someone outside your team, and documented so the result is defensible. You do not get an absolute verdict. You get a clear, written account of what each metric means and whether it held, so you can make the call from the evidence.
Independence is the point. The person who built a number cannot certify their own work. I know, because I have had to reconcile my own migration and could not be my own outside check. That is the one thing an in-house analyst structurally cannot provide.
Independent, third-party proof that a defined set of your key operational metrics survive an Epicor → Kinetic migration. Established to standard, documented, defensible. The right first step.
The full picture: schema mapping and data-quality validation across your whole migration, not just a defined set of metrics. The verification engagement is step one toward it.
Once your data is trustworthy, the operations-intelligence layer that turns it into a clear, shared view of the floor. The same numbers, translated to every level.
Verify the numbers survive → validate the whole data picture → run operations on it.
Your shift supervisor stops walking into your office with a different number than the one on the screen. Everyone finally sees the same data.
If you can pull an ERP export, you can run OIM. No server, no implementation consultant, no six-month rollout.
Operations, maintenance, quality, and the executive team all working from the same numbers, translated to what each level actually needs to see.
Runs on hardware you own. No cloud subscription, no vendor access to your production data, no per-seat fees piling up each month.
The OIM is designed to be deployed, not implemented. Here's what the first week looks like.
Drop your ERP CSV exports into the OIM. Real-world exports: incomplete columns, inconsistent values, partial data. All handled without pre-processing. Epicor, and other common ERP formats, supported out of the box.
Before any analysis, OIM scores your data quality and tells you exactly what's missing, what's inconsistent, and where to focus cleanup. You trust the output because you've seen the input.
Throughput, OEE, downtime, and quality trends. Each translated into the numbers that actually matter to operators, plant managers, and the executive team. Everyone finally sees the same truth.
SQL connection, MES integration, IIoT data: OIM's architecture meets your team where you are and expands as you're ready. No rip-and-replace.
Most operations intelligence tools are designed for analysts and sold to executives. The OIM is built for the people actually running production.
Runs on hardware you own. No cloud dependency, no vendor access to your production data. You own the software; no per-seat or consumption fees layered on top.
The OIM is an intelligence layer on top of your ERP. Not a replacement. Your operators keep working the same way. The OIM makes the best possible use of the data they're already creating.
OIM scores your data quality and surfaces exactly what's missing, inconsistent, or needs operator attention alongside your dashboards, not as an afterthought. You trust the output because you've seen the input.
Medallion architecture, Kimball dimensional modeling, ISO 22400 metrics: the same architectural foundations used by enterprise platforms, without the enterprise price tag.
"No one had built a tool that actually fit how operations people work. So I built it."
I have spent nearly 15 years at a Fortune 250 electric utility. I have designed work orders, coordinated with operations to get the work executed, and run planning and scheduling for an entire business unit. At every level of that process, I built the analytic tools that gave the whole organization the visibility to work toward a shared goal.
I took that architecture and translated it for mid-market manufacturing. The OIM is the result. Everyone from the operator to the executive sees the same data, translated to their level.
Short, opinionated writing from someone who's actually run operations.
Read the Dispatch →Let's explore together if this solves your current reporting pain.
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