# OCR Pilot Test Plan Template

> Source: https://netray.co/tools/ocr-pilot-test-plan-template
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

A fill-in plan for piloting OCR or document AI on invoices or quality records, with scope, sample set, measures and exit criteria.

## Category

ai-automation

## Industry

Discrete Manufacturing

## Audience

- Project manager
- AP manager
- Quality manager

## Tool

**Kind:** template

**Output:** document

**Fields:**

#### Pilot name

**Key:** project

**Type:** text

**Default:** Supplier invoice capture pilot

#### Company

**Key:** company

**Type:** text

**Default:** Acme Precision Ltd

#### Sponsor

**Key:** sponsor

**Type:** text

**Default:** Controller

#### Pilot owner

**Key:** owner

**Type:** text

**Default:** AP manager

#### Start date

**Key:** start

**Type:** date

**Default:** 2026-11-02

#### End date

**Key:** end

**Type:** date

**Default:** 2026-12-11

#### Document types in scope

**Key:** doc_types

**Type:** textarea

**Default:** Supplier invoices (PO-backed), credit notes. Excluded: freight bills, utilities.

#### Sample set

**Key:** sample

**Type:** textarea

**Default:** 300 documents from 25 suppliers, drawn from the last 90 days, including 40 scanned and 20 non-English documents.

#### Primary success metric

**Key:** metric

**Type:** select

**Options:**

- Field-level accuracy
- Touchless rate
- Handling time per document
- Cost per document

**Default:** Field-level accuracy

#### Success target

**Key:** target

**Type:** text

**Default:** Header fields 97 percent correct, line items 93 percent correct

#### Hosting

**Key:** env

**Type:** select

**Options:**

- On-premises
- Private cloud
- Vendor SaaS

**Default:** On-premises

**Blocks:**

#### {{project}}

**Body:** Company: {{company}}
Sponsor: {{sponsor}}
Pilot owner: {{owner}}
Dates: {{start}} to {{end}}
Hosting: {{env}}

#### Objective

**Body:** Decide with evidence whether document capture can read the documents below at an acceptable accuracy and cost, before committing to a full rollout.

#### Scope

**Body:** {{doc_types}}

#### Sample set

**Body:** {{sample}}

A person who is not on the project team will key the correct values for each sample document before the pilot starts. This is the answer key.

#### Success criteria

**Body:** Primary metric: {{metric}}
Target: {{target}}

Secondary measures: exception rate, minutes of human review per document, data stays inside the agreed boundary.

#### Method

**Table:**

**Columns:**

- Step
- Activity
- Owner
- Date

**Rows:**

**0:** 1

**1:** Collect sample and build answer key

**0:** 2

**1:** Configure and run extraction

**0:** 3

**1:** Compare output to answer key by field

**0:** 4

**1:** Review errors with AP and quality users

**0:** 5

**1:** Decision meeting

#### Risks

**Table:**

**Columns:**

- Risk
- Mitigation
- Owner

**Rows:**

**0:** Sample not representative

**1:** Draw across all suppliers and months

**0:** Confidential data exposure

**1:** Run inside the agreed network boundary

**0:** Answer key errors

**1:** Second reviewer checks 10 percent

#### Decision and approval

**Signatures:**

- Pilot owner
- Sponsor
- IT security

**Notes:** A starting template. Adjust scope, measures and approvals to your own governance process.

## Content

**Intro:** Most OCR pilots fail because nobody agreed up front what good looks like. This plan fixes the scope, sample set, measures and decision rules before any software runs.

**Sections:**

#### How to use the template

**Body:** Fill in the pilot name, dates, scope and target, then export to PDF or Word and circulate before kickoff. Get the sponsor to sign the success criteria. Changing the target after seeing results is the most common reason pilots produce a false yes or false no, so treat the signed criteria as fixed.

#### Building the sample set

**Body:** Pick documents that represent real volume, not the clean ones. Include scanned pages, multi-page invoices, credit notes, non-English documents and the suppliers that cause you the most exceptions. Three hundred documents across twenty or more suppliers is a workable starting size for a header-level read, but line items need more lines, not more documents. Keep a hold-out set that the vendor never sees.

#### Measures that matter

**Body:** Field-level accuracy compares each extracted value with the answer key. Touchless rate is the share of documents that post with no human touch. Report both, because high accuracy with low confidence still sends many documents to review. Also record review minutes per document so you can calculate cost, not just accuracy.

#### Common mistakes

**Body:** Do not let the software vendor choose the sample. Do not count a document as correct when the total is right but the PO number is wrong, since that breaks matching. Do not skip the data governance question, especially for defense, aerospace and export-controlled documents, where where the model runs may matter as much as how well it reads.

**Cta:** Netray runs pilots with open-weight models on your own hardware, so documents never leave your network. We can help build the answer key and scorecard.

**Faq:**

#### How long should an OCR pilot last?

**Answer:** Four to six weeks is common: one week for the sample and answer key, two for configuration and runs, and the rest for review and decision. Longer pilots tend to drift in scope without producing better evidence.

#### Who builds the answer key?

**Answer:** A person independent of the vendor and project team, ideally an AP clerk or quality technician who knows the documents. Have a second person check a subset to catch keying errors in the key itself.

#### What accuracy should we target?

**Answer:** It depends on your downstream controls. Set targets by field, with stricter values for amounts, PO numbers and vendor identity than for descriptive text, and agree them with the process owner before the pilot.

#### Can I use this for quality documents?

**Answer:** Yes. Replace the document types with certificates of conformance or test reports, and add the fields that matter, such as heat number, part number and specification revision.

## Search terms

ocr pilot test plan, document ai proof of concept template, invoice capture pilot plan, ocr proof of concept plan, intelligent document processing pilot, ocr evaluation test plan template

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