# BOM Error Cost of Poor Quality Calculator

> Source: https://netray.co/tools/bom-error-cost-of-poor-quality-calculator
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

Quantify what BOM line errors cost when they are found late, and see the chance that a released BOM is completely clean.

## Category

engineering-plm

## Industry

Discrete Manufacturing

## Audience

- Engineering manager
- Configuration manager
- MDM lead
- Operations manager

## Tool

**Kind:** calculator

**Currency:** $

**Inputs:**

#### BOMs released or changed per year

**Key:** boms

**Type:** number

**Default:** 1200

**Min:** 0

**Step:** 50

**Unit:** BOMs

#### Average lines per BOM

**Key:** lines

**Type:** number

**Default:** 45

**Min:** 1

**Step:** 1

**Unit:** lines

#### Line error rate

**Key:** err_pct

**Type:** slider

**Default:** 0.5

**Min:** 0

**Max:** 2

**Step:** 0.05

**Unit:** %

**Help:** Share of BOM lines with a wrong quantity, part, revision, unit of measure or missing reference designator.

#### Errors first found on the shop floor

**Key:** floor_pct

**Type:** slider

**Default:** 25

**Min:** 0

**Max:** 100

**Step:** 5

**Unit:** %

#### Errors first found at customer or in the field

**Key:** field_pct

**Type:** slider

**Default:** 3

**Min:** 0

**Max:** 100

**Step:** 1

**Unit:** %

#### Cost per error caught in engineering or review

**Key:** cost_eng

**Type:** number

**Default:** 60

**Min:** 0

**Step:** 10

**Unit:** $

#### Cost per error found on the shop floor

**Key:** cost_floor

**Type:** number

**Default:** 900

**Min:** 0

**Step:** 50

**Unit:** $

**Help:** Line stoppage, expediting, kitting rework and scrap.

#### Cost per error found in the field

**Key:** cost_field

**Type:** number

**Default:** 12000

**Min:** 0

**Step:** 500

**Unit:** $

**Help:** Returns, warranty, retrofit and customer impact.

**Outputs:**

#### BOM lines handled per year

**Key:** lines_total

**Expr:** boms * lines

**Format:** integer

#### Expected line errors per year

**Key:** errors

**Expr:** lines_total * err_pct / 100

**Format:** integer

#### Share caught early

**Key:** eng_pct

**Expr:** max(0, 100 - floor_pct - field_pct)

**Format:** percent

#### Annual cost of BOM errors

**Key:** copq

**Expr:** errors * (eng_pct * cost_eng + floor_pct * cost_floor + field_pct * cost_field) / 100

**Format:** currency

**Primary:** true

#### Cost per BOM

**Key:** per_bom

**Expr:** if(gt(boms, 0), copq / boms, 0)

**Format:** currency

#### Chance a BOM has no errors

**Key:** clean

**Expr:** pow(1 - err_pct / 100, lines) * 100

**Format:** percent

**Primary:** true

**Chart:**

#### Annual BOM error cost vs line error rate

**Type:** line

**X:** err_pct

**From:** 0

**To:** 2

**Steps:** 40

**Series:**

- copq

**Disclaimer:** Illustrative model. Use your own cost per escape from rework, scrap and warranty records.

## Content

**Intro:** A small error rate per BOM line sounds harmless until you multiply it by hundreds of lines per BOM. This calculator shows the yearly cost of BOM errors based on where they are caught, and the surprisingly low probability that a large BOM is fully correct.

**Sections:**

#### How to use it

**Body:** Enter the number of BOMs released or changed each year and their average line count. For the line error rate, audit a sample of BOMs against the engineering source such as drawings or the CAD structure, and count lines with a wrong part, revision, quantity or unit of measure. Then estimate where errors are first discovered. Costs rise by orders of magnitude from design review to the shop floor to the field, so use cost figures from your own rework, expedite and warranty records where possible, even if they are rough.

#### The method

**Body:** Expected errors equal total lines times the error rate. The early catch share is whatever is not found on the shop floor or in the field. Annual cost is expected errors multiplied by the weighted cost of the three stages. The clean BOM probability treats each line independently: the chance of no errors is one minus the line error rate, raised to the number of lines. At a 0.5 percent error rate, a 45-line BOM is clean only about 80 percent of the time, and a 300-line BOM about 22 percent. This is why line-level accuracy targets need to be much tighter than BOM-level targets.

**Bullets:**

- Errors = BOMs x lines x error rate
- Cost = errors x weighted cost by discovery stage
- Clean BOM probability = (1 - error rate)^lines

#### Using the output

**Body:** The sweep chart shows cost rising linearly with error rate, so halving the rate halves the cost, but moving errors earlier can matter even more: shifting ten points of errors from the shop floor to engineering review cuts the weighted cost noticeably. Typical controls are release checklists, CAD to ERP BOM comparison, unit of measure validation, and first-article builds. Common mistakes are counting only errors that stopped production, ignoring errors that silently cause a wrong cost roll, and assuming errors are independent when one wrong revision often corrupts several lines at once.

**Cta:** Automated comparison of CAD or PLM structures against ERP BOMs, with exceptions listed for an engineer to approve, catches errors before release. Netray can build that against your own systems.

**Faq:**

#### What counts as a BOM line error?

**Answer:** Any line whose part number, revision, quantity, unit of measure, scrap factor, effectivity or reference designator differs from the approved design intent. Missing lines and extra lines count too. Define the rule before sampling.

#### Is a 0.5 percent line error rate typical?

**Answer:** Rates vary a lot with process maturity, from well under a tenth of a percent in controlled release environments to several percent where BOMs are edited directly in the ERP. Measure your own through a sampled audit.

#### How do I estimate cost per shop floor error?

**Answer:** Add expediting, line downtime, rework labor, scrap, extra kitting and planner time for a handful of recent incidents and average them. Field cost needs warranty and customer cost data, and often dominates the total.

#### Why use independence for clean BOM probability?

**Answer:** It is a simplification that gives a usable lower-bound view. In reality errors cluster, so the true clean fraction is usually somewhat higher than the independent model predicts, but the message stands.

## Search terms

bom error cost, cost of bad bill of materials, bom accuracy cost of poor quality, bom errors found on shop floor, bom accuracy probability calculator, cost of late engineering error detection, bom data quality business case

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