---
title: "NHTSA complaint counts: ODI references and component rows"
description: "Distinguish NHTSA complaint rows from distinct ODI references, explain overlapping components, and prepare a reproducible count for attorney review."
canonical: "https://scalewithsearch.com/articles/nhtsa-complaint-odi-reference-component-row-counts"
---
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# NHTSA complaint counts: distinguish ODI references from component rows

A component comparison needs a counting unit. Six rows can represent fewer than six ODI references when one reference appears under several components. Label the unit before giving the total to an attorney. Keep the selected source snapshot and grouping rule beside the result.

The National Highway Traffic Safety Administration (NHTSA) maintains the Office of Defects Investigation (ODI) complaint database. Its flat-file dictionary distinguishes CMPLID, an internal unique sequence number, from ODINO, an internal reference number. It warns that ODINO can repeat across components. Older records can also repeat it across products owned by one complainant. See [CMPL.txt, fields 1 and 2](https://static.nhtsa.gov/odi/ffdd/cmpl/CMPL.txt), reopened October 28, 2026.

This guide uses invented rows to explain that distinction. The [personal injury firm overview](/for/personal-injury-law-firms) covers attorney-directed preparation more broadly. Here, the deliverable is a reproducible reading table. It identifies neither people nor potential claimants.

## Name the unit before making a comparison

Choose among rows, distinct references, and references within each component category. These units answer different questions. A row count describes the selected table. A distinct-reference count collapses repeated ODINO values within that selection. A component count depends on the chosen grouping rule.

Use full labels in a memo. “Six selected flat-file rows” is checkable. “Four distinct ODINO values within the selected rows” is also checkable. “Six complaints” leaves the reader to guess whether the writer counted rows, references, or something else.

| Proposed unit | What the worksheet counts | What the label leaves unresolved |
| --- | --- | --- |
| Selected rows | Every included row in one source snapshot | How many references or people those rows represent |
| Distinct ODINO values | Different reference values within the selection | People, incidents, vehicles, and legal claims |
| References per component | Distinct references assigned to each stated component category | Overlap between categories |
| Component rows | Rows carrying each original component label | Repeated references within or across labels |

Do not rename distinct references “unique people.” The counting exercise establishes no person-level identity. It also supplies no rule for deciding whether two reports concern the same underlying incident. Keep those unresolved concepts outside the tally.

Write the selection boundary with the unit. “Distinct references in this snapshot for these vehicle labels and dates” is narrower than “all complaints.” A filter creates a selected group. Its title should preserve that selection when the table leaves the worksheet.

## Read CMPLID and ODINO as separate fields

The dictionary calls CMPLID updateable and notes that record data can change between output files. Treat it according to that caution. Preserve CMPLID and ODINO separately when the approved research requires both. Do not replace one with the other to simplify a heading.

Field 2's older-record warning applies when LDATE precedes December 15, 2002. Preserve that exact condition in the research note. A repeated reference in an older selection deserves examination of the product dimension before the researcher describes the repetition. [NHTSA complaint layout, fields 1, 2, and 17](https://static.nhtsa.gov/odi/ffdd/cmpl/CMPL.txt).

That warning does not justify guessing a person's identity. Nor does it make every repeated reference an erroneous duplicate. Ask what each row represents in the selected evidence. Retain a row when it carries information the stated component comparison needs.

Keep a separate local row label for training examples. The labels R1 through R6 below are invented worksheet references. They are not valid substitutes for agency identifiers, and they describe no real products or complainants.

## Work through six synthetic component rows

Assume the worksheet contains the following six rows. Component Alpha and Component Beta are fictional teaching categories. REF-A through REF-D are synthetic reference placeholders. The table deliberately omits narratives, vehicle identifiers, locations, and personal attributes.

| Local row label | Synthetic ODINO placeholder | Synthetic component category |
| --- | --- | --- |
| R1 | REF-A | Component Alpha |
| R2 | REF-A | Component Beta |
| R3 | REF-B | Component Alpha |
| R4 | REF-C | Component Beta |
| R5 | REF-C | Component Alpha |
| R6 | REF-D | Component Alpha |

The selected row count is six. The distinct-reference count is four: REF-A, REF-B, REF-C, and REF-D. Component Alpha contains four distinct references. Component Beta contains two. REF-A and REF-C belong to both component groups.

| Synthetic result | Count | Included unit |
| --- | --- | --- |
| Entire selection | 6 | Rows |
| Entire selection | 4 | Distinct references |
| Component Alpha | 4 | Distinct references within Alpha |
| Component Beta | 2 | Distinct references within Beta |
| Alpha and Beta overlap | 2 | References present in both groups |

Adding the component counts gives six category memberships. It does not change the whole-selection total of four distinct references. The arithmetic counts a different unit because two references contribute to both groups.

An acceptable summary is: “Four synthetic references appear across six component rows; two references occur in both categories.” Another acceptable summary gives each category separately and states that the categories overlap. Neither summary establishes six people or six failures.

For a real comparison, keep enough authorized evidence to reproduce category membership. The attorney should be able to ask why one reference appears in two columns. A short overlap note is more useful than silently forcing each reference into a single category.

## Keep raw labels beside the reviewed category map

The dictionary defines COMPDESC as the specific component description. It also notes historical changes to component and product labels. See [CMPL.txt, field 12 and change notes](https://static.nhtsa.gov/odi/ffdd/cmpl/CMPL.txt). Retain the original label when preparing a broader comparison category.

Treat a category map as the research team's interpretation. Give it a version and a reviewer. If two source labels seem similar, record the proposed relationship for review. Do not erase the source distinction because the chart becomes easier to read.

For a synthetic example, suppose “Alpha assembly” and “Alpha control” are proposed for one umbrella category. The attorney might accept that grouping for preliminary reading. Another question might require separate categories. Preserve the decision's purpose so a later researcher knows where it applies.

| Mapping record | Editorial worksheet entry |
| --- | --- |
| Original label | Exact component text from the permitted evidence |
| Proposed category | Team-defined comparison label |
| Mapping version | Date and version of the reviewed rules |
| Reason | Why this grouping fits the current research question |
| Unresolved labels | Values requiring further review |
| Reviewer | Responsible attorney or assigned research reviewer |

When a map changes, identify the affected summaries. Recompute them under the stated version or retain the earlier map for comparison. Do not attribute a category increase to new evidence when a broader mapping rule caused it.

Keep unresolved labels visible. Excluding them may be appropriate for a narrow comparison, but the exclusion needs a tally and reason. A chart with no exception note can conceal which parts of the source the researcher could not interpret.

## Explain why these counts are not a failure rate

A failure rate requires a defined numerator and a compatible exposure denominator. The selected complaint rows provide neither a verified failure numerator nor a vehicle-exposure denominator for this exercise. Dividing them by another convenient total would change the question without establishing the needed relationship.

NHTSA describes complaint information as an input used with other data to identify issues warranting investigation. That description does not turn the worksheet into a comparative-safety study. Read the [agency's Complaints background](https://www.nhtsa.gov/nhtsa-datasets-and-apis#complaints) before describing what the research supports.

If someone asks which vehicle is safer, record that as a separate research question. Ask what evidence and method would support the comparison. Do not rank products from these counts. Complaint reports alone establish no defect, causation, injury total, or legal eligibility.

Also avoid converting the two component counts into percentages of all vehicles. In the synthetic example, four out of four references carry Alpha. That describes category membership within an invented selection. It establishes nothing about how frequently any real component fails.

A precise denominator label can still support a limited descriptive calculation. For example, “two of four synthetic references appear in both categories” states the table's overlap. Keep that statement attached to the synthetic example and its selected-reference denominator.

## Fix the date basis and snapshot alongside the unit

Counts need a period definition as well as a unit. A receipt-month selection differs from an incident-month selection. The sibling [complaint date guide](/articles/nhtsa-complaint-incident-received-added-dates) explains FAILDATE, LDATE, and DATEA. Choose the date basis before comparing two periods.

Use one source snapshot for a same-time comparison wherever the research question permits it. Record the snapshot reference and access date. If two summaries use different observations, say so. A changed total may reflect changed source content or different local selection rules.

If the researcher receives both an API export and a flat-file excerpt, preserve their original structures. This guide verifies no equivalence between their identifiers or component fields. Resolve the mapping before combining them. Similar labels do not prove that row counts are comparable.

During review, separate three questions: what entered the selection, how it was grouped, and what changed since the prior worksheet. Each needs its own evidence. A single “new complaints” column can hide all three decisions.

## Prepare a reproducible reading table for the attorney

The following table is a proposed research template. It carries the decisions that give a count meaning. Use it with a bounded, approved source selection. Keep confidential matter connections in the firm's separate authorized environment.

| Reading-table field | What the researcher records |
| --- | --- |
| Research question | Exact comparison the attorney requested |
| Source snapshot | Official source, saved version reference, and access date |
| Dictionary | Inspected revision and field numbers |
| Selection | Vehicle labels, product scope, dates, and exclusions |
| Counting unit | Rows, distinct ODINO values, or category memberships |
| Identifier treatment | Separate handling of CMPLID and ODINO |
| Category mapping | Original labels, map version, reviewer, unresolved values |
| Overlap | References appearing in more than one category |
| Result | Number with its full unit label |
| Limits | Missing exposure denominator and unresolved interpretations |
| Attorney questions | Applicability, grouping suitability, and further evidence needed |
| Review outcome | Accepted wording, rejected interpretation, or request for more evidence |

Ask the reviewer to reproduce the six-row exercise before accepting the proposed labels. The expected answer is six rows, four distinct references, and two overlapping references. If the result differs, resolve the counting rule before applying it to actual research.

Retain rejected interpretations too. A note explaining why “six unique complaints” was rejected can prevent that phrase from returning in the next memo. The [business memory guide](/articles/business-memory-for-ai-agents-guide) covers preserving decisions with their supporting evidence.

## Scope the workflow around reviewed definitions

The [injury-firm intelligence overview](/intelligence/personal-injury-law-firms) places public-source comparisons within an attorney-led review process. A useful first deliverable is the accepted reading table, category map, and example summary. It needs no claimant search or outbound contact capability.

Scale With Search can scope a research workflow after the firm identifies its permitted sources, counting definitions, and review owner. Keep the boundary explicit: prepare evidence for judgment, preserve the reasoning, and leave the professional decision with the responsible attorney.

[Discuss the research workflow](/work)

## Source and example notes

Sources reopened October 28, 2026: [NHTSA datasets and APIs, Complaints](https://www.nhtsa.gov/nhtsa-datasets-and-apis#complaints) and [CMPL.txt](https://static.nhtsa.gov/odi/ffdd/cmpl/CMPL.txt). The dictionary states April 30, 2026 as its last update. Fields 1, 2, 12, and 17 control the identifier, component, and older-record definitions discussed here. Examples use invented references and categories. No archive, narrative, VIN, incident location, complainant, or private matter record was retrieved.


Continue the website review: [AI-native injury law firms: the first functions to build](/articles/ai-native-injury-law-first-functions); [Chicago crash injuries: distinguish the most severe category from the number of people](/articles/chicago-crash-injury-severity-person-counts); [Chicago crash maps: keep missing locations in the coverage count](/articles/chicago-crash-map-missing-location-coverage); [Injury law firm AI rules: data, approvals, and spend](/articles/injury-law-firm-ai-rules-data-approvals-spend); [NHTSA complaint dates: separate the incident, receipt, and file addition](/articles/nhtsa-complaint-incident-received-added-dates); [Injury firm rebrand: map old website pages first](/articles/personal-injury-firm-rebrand-website-redirects); [AI gets your injury firm wrong: check the source facts](/articles/personal-injury-firm-wrong-ai-answer-facts); [Injury law firm virtual offices and Google profiles](/articles/personal-injury-law-firm-virtual-office-profile); [Injury website settlement calculators: check the promise](/articles/personal-injury-settlement-calculator-website-review); [Spanish injury firm pages: review the whole inquiry path](/articles/personal-injury-spanish-website-page-review); [Personal injury website leads: test the case review path](/articles/personal-injury-website-case-review-delivery); [Injury firm website fees: explain costs separately](/articles/personal-injury-website-contingency-fee-costs); [Injury website form spam: protect the real inquiry path](/articles/personal-injury-website-form-spam-control-review); [Injury website file uploads: define the private handoff](/articles/personal-injury-website-medical-record-upload-brief); [Personal injury settlement results on your website](/articles/personal-injury-website-settlement-results); [Injury website thank-you pages: keep the receipt plain](/articles/personal-injury-website-thank-you-page-privacy).


[personal injury law firms](/for/personal-injury-law-firms): website and search resources.


## Related: personal injury law firms

- [Injury firm rebrand: map old website pages first](/articles/personal-injury-firm-rebrand-website-redirects)
- [AI gets your injury firm wrong: check the source facts](/articles/personal-injury-firm-wrong-ai-answer-facts)
- [Injury law firm virtual offices and Google profiles](/articles/personal-injury-law-firm-virtual-office-profile)

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Scale With Search  2026  [scalewithsearch.com](https://scalewithsearch.com)
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