cost per order, on a signed baseline sample
Our approach · the method, in depth
We treat your back-office like a diligence target — then we instrument the fix.
Most automation projects start with a tool. Ours starts with a data-readiness diagnostic and a measured baseline, so the result can be proven instead of promised. This is the method behind the guarantee — written for owners and sponsors who've been burned by software projects before.
01
Diagnose
Profile the data and the workflow before a line of automation is built. The output is a scored readiness picture, not a hunch.
02
Model
Turn the readiness picture into a hard-dollar baseline and a target. Every figure shows its work, so the number is defensible.
03
Build & instrument
Deploy the wedge on one contained scope, reselling a proven engine, with a before/after harness wired in from day one.
04
Run & measure
Compare realized result to the signed baseline on annualized volume — then expand the ladder or hand off cleanly.
01The data-readiness diagnostic
The audit answers one question:
is your data ready to automate?
Dirty data is the single most common reason automation projects miss — duplicate SKUs that split inventory, inconsistent units of measure, fragmented customer records that break credit limits, null fields on cost and lead time, and stale pricing tables. We find it before we build, not after it has propagated.
The diagnostic is a structured profile of your own system: we measure duplicate rates by entity, null-field rates on the fields that matter, pricing-table staleness, and the channel mix of inbound orders — what share arrives as structured EDI versus unstructured email, PDF, and fax. That last number sizes the wedge.
The deliverable reads like a diligence memo: a prioritized use-case backlog on an impact/effort matrix, a scored data-readiness scorecard, and a baseline KPI snapshot. Quantified, sourced, conservative — with a named owner per metric.
What the scan profiles
- Entity duplication — customer, item, and vendor records, scored as a duplicate rate.
- Null-field rates — on cost, UOM, lead time, and customer terms.
- Pricing staleness — how old your active price records actually are.
- Channel mix — % EDI vs. unstructured email / PDF / fax (the wedge size).
- Workflow map — who touches an order, and where the hours go.
Roughly 70%+ of ERP initiatives fail to fully meet their business-case goals, frequently because of data. The diagnostic exists so yours isn't one of them.Gartner-cited, industry benchmark
02 · The measurement harness
Before/after, instrumented —
Before/after, instrumented —
so ROI is observed, not asserted.
We don't ask you to take savings on faith. The harness captures the baseline from your own ERP and a real order sample, then measures the same metrics after go-live, on annualized volume. The number is signed off at both ends. No black box — every figure traces back to a row in your system.
This is why we can put a defined portion of the build fee at risk against the target: we are measuring it the same way an underwriter would.
$ / order
min / order
processing time, timed before and after
% accurate
line-level accuracy vs. the source document
% touchless
orders entered with no human keystroke
Benchmark anchors for context (vendor-self-reported, cited as such): manual order entry ~$8–15 each (Mirage Metrics, 2026); processing time cut up to ~95% (Conexiom). We replace these with your own measured numbers on engagement #1.
03The integration approach
We adapt to your system —
not the other way around.
Live in roughly 30 days, with zero rip-and-replace. The point-solution vendors have already solved most of the plumbing; our job is the orchestration, the data, and the last-mile workflow.
P21 · Eclipse · SX.e · NetSuite
Distribution ERPs
Epicor Prophet 21 has an open SQL Server backend we can read and write cleanly. Eclipse and Infor SX.e are older but workable; NetSuite exposes modern REST APIs. We scope around what your ERP actually exposes — DDI, SAP Business One, Sage, and Acumatica included — and never promise a rip-and-replace.
Applied Epic · EZLynx · AMS360 · HawkSoft
Insurance AMS
For agencies, we integrate at the agency-management-system layer through each platform's API or supported export. [VERIFY] exact connector availability per AMS and version before we scope — we confirm it in the audit, not on a slide.
Conexiom / Esker · custom IDP
The engine + glue
We resell proven document engines (Conexiom advertises 40+ native ERP integrations) rather than rebuild them, and write a custom intake pipeline (LLM + Azure Document Intelligence / Textract) only where your documents are too messy or low-volume for an enterprise tool. Orchestration runs on Make or self-hostable n8n for data-sensitive clients; order-status and catalog Q&A sit on a vector store.
04Exception & human-in-the-loop design
Nothing dirty
auto-propagates.
Real customers don't send clean POs — they say "send the usual." The system learns each customer's shorthand from their order history and handles the routine cases. The genuinely ambiguous ones route to a person, not straight into your ERP.
Every automated action carries a confidence score. We set the thresholds with you: above the line, the order flows; below it, a human reviews. Thresholds start conservative and tighten only as the measured accuracy earns it. Dirty data never forces its way into your system of record.
That design is also a guardrail on the guarantee — data-readiness preconditions mean a payout is never triggered by a system that actually worked.
How an order is handled
- Document arrives (email, PDF, fax) and is read into structured fields.
- Each field gets a confidence score against the item and customer master.
- High-confidence orders post to the ERP through the channel you approve.
- Low-confidence or novel orders route to a reviewer with the source attached.
- Every correction feeds back, so the next one scores higher.
05Change management
Order-takers become order-makers.
The technology is the easy half. Adoption with long-tenured, valuable staff is where projects live or die — so we design for it from the start, and frame it as doing more with the staff you can't hire.
Involve, don't impose
The people who handle orders today help design the thresholds and the exception rules. They know the customers' shorthand better than any model does.
A quick win, early
We aim for a visible result in the first weeks on one channel or segment, then socialize it — momentum beats a mandate with skeptical teams.
SOPs, not tribal knowledge
You keep exception-handling SOPs and adoption metrics — so the capability lives in the business, not in a consultant's head.
This is how the guarantee gets earned.
The diagnostic is the paid front door. Start there, or book a call to walk through your data and your order channels.