# Quote Win/Loss Analysis Worksheet for Manufacturers

> Source: https://netray.co/tools/quote-win-loss-analysis-worksheet
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

Record outcomes and loss reasons, see price gap versus the winning bid, and compute hit rate by count and by dollar value.

## Category

cost-finance

## Industry

Job Shops & Contract Manufacturing

## Audience

- Estimator
- Sales manager
- Owner

## Tool

**Kind:** worksheet

**Mode:** editable

**Currency:** $

**Columns:**

#### Quote #

**Key:** quote

**Type:** text

#### Customer

**Key:** customer

**Type:** text

#### Part family

**Key:** family

**Type:** select

**Options:**

- Turned
- Milled
- Sheet metal
- Weldment
- Assembly
- Other

#### Our price

**Key:** our_price

**Type:** number

**Format:** currency

#### Winning price

**Key:** win_price

**Type:** number

**Format:** currency

**Help:** If you won, repeat our price. If lost and unknown, estimate from buyer feedback or leave equal to ours.

#### Won (1 / 0)

**Key:** won

**Type:** number

**Help:** 1 = won, 0 = lost or no decision.

#### Our lead time

**Key:** our_lead

**Type:** number

**Unit:** weeks

#### Winning lead time

**Key:** win_lead

**Type:** number

**Unit:** weeks

#### Primary reason

**Key:** reason

**Type:** select

**Options:**

- Won: price
- Won: lead time
- Won: relationship
- Lost: price
- Lost: lead time
- Lost: capability
- No decision
- Customer cancelled

#### Price gap vs winner

**Key:** gap

**Type:** number

**Expr:** if(gt(win_price, 0), (our_price - win_price) / win_price * 100, 0)

**Format:** percent

**Help:** Positive = we were higher than the winning price.

#### Lead time gap

**Key:** lead_gap

**Type:** number

**Expr:** our_lead - win_lead

**Format:** number

**Unit:** weeks

#### Won value

**Key:** won_value

**Type:** number

**Expr:** our_price * won

**Format:** currency

**Rows:**

**Quote:** Q-26-2101

**Customer:** Northline Hydraulics

**Family:** Milled

**Our price:** 48500

**Win price:** 48500

**Won:** 1

**Our lead:** 5

**Win lead:** 5

**Reason:** Won: relationship

**Quote:** Q-26-2108

**Customer:** Calder Aerospace Fittings

**Family:** Turned

**Our price:** 126000

**Win price:** 109000

**Won:** 0

**Our lead:** 8

**Win lead:** 7

**Reason:** Lost: price

**Quote:** Q-26-2112

**Customer:** Brightwell Controls

**Family:** Sheet metal

**Our price:** 34800

**Win price:** 33900

**Won:** 0

**Our lead:** 6

**Win lead:** 3

**Reason:** Lost: lead time

**Quote:** Q-26-2115

**Customer:** Ridgeway Pump Co

**Family:** Assembly

**Our price:** 71000

**Win price:** 71000

**Won:** 1

**Our lead:** 6

**Win lead:** 6

**Reason:** Won: lead time

**Quote:** Q-26-2119

**Customer:** Harlan Valve

**Family:** Weldment

**Our price:** 22400

**Win price:** 22400

**Won:** 0

**Our lead:** 4

**Win lead:** 4

**Reason:** No decision

**Totals:**

#### Total quoted value

**Key:** our_price

**Agg:** sum

**Format:** currency

#### Total won value

**Key:** won_value

**Agg:** sum

**Format:** currency

#### Quotes won

**Key:** won

**Agg:** sum

**Format:** integer

#### Average price gap

**Key:** gap

**Agg:** avg

**Format:** percent

**Summary:**

#### Hit rate by count

**Key:** hit_count

**Expr:** sum_won / max(count, 1) * 100

**Format:** percent

#### Hit rate by value

**Key:** hit_value

**Expr:** sum_won_value / max(sum_our_price, 1) * 100

**Format:** percent

**Description:** Value-weighted hit rate. A gap versus count hit rate shows whether you win small or large jobs.

#### Quoted value not won

**Key:** lost_value

**Expr:** sum_our_price - sum_won_value

**Format:** currency

**Notes:** Price gap = (our price - winning price) / winning price. Hit rate by count is quotes won divided by quotes issued; hit rate by value is won dollars divided by quoted dollars. Review at least 25 to 30 quotes before drawing conclusions, and separate by part family or customer type once you have volume.

## Content

**Intro:** Shops that track only total sales cannot tell whether they are losing on price, lead time or capability. This worksheet captures the outcome of each quote and calculates both hit rate measures, so pricing and capacity decisions rest on evidence.

**Sections:**

#### How to use the worksheet

**Body:** Enter each closed quote with our price, the winning price if known, the won flag and lead times. Pick a primary reason from the list. The sheet calculates price gap and lead time gap per row, then summarizes hit rate by count and by value. Ask buyers for feedback directly. Many will share the winning price range or the deciding factor when asked politely. Export to Excel and filter by reason or family to see patterns.

#### The metrics explained

**Body:** Hit rate by count is wins divided by quotes issued. Hit rate by value is won dollars divided by quoted dollars. When value hit rate is much lower than count hit rate, you win small jobs but lose large ones, which often signals price discipline or capacity limits on bigger work. Price gap compares your price to the winner. A consistent gap of 5 to 10 percent on lost quotes suggests a pricing problem, while gaps near zero with long lead times point to scheduling.

#### Reading the example

**Body:** In the default rows, two of five quotes were won, a 40 percent count hit rate, but value hit rate is lower because the largest quote lost on a 15 percent price gap. The Brightwell loss had almost no price gap but a three-week lead time deficit, so cutting price would have been the wrong response. Matching reasons to gaps stops teams from discounting when speed is the real issue.

#### Common mistakes

**Body:** Counting no-decision quotes as wins or ignoring them both distort results. Record them as non-wins with a clear label. Another mistake is guessing loss reasons. If you do not know, mark no decision rather than blaming price. Finally, do not change pricing from five data points: wait for a meaningful sample.

**Cta:** If your ERP holds quote and sales order history, we can help pull win/loss data automatically by customer and family. This worksheet works from a simple list.

**Faq:**

#### What is a good quote hit rate for a job shop?

**Answer:** It varies widely by market and RFQ source. Many custom job shops report somewhere from 10 to 40 percent. Repeat customers and relationship business convert much higher, open competitive RFQs lower. Track your own baseline rather than chasing a benchmark.

#### Why track hit rate by value as well as count?

**Answer:** Count treats a 500 dollar quote like a 500,000 dollar quote. Value-weighted hit rate reflects revenue impact. If the two differ greatly, you may be strong on small work and uncompetitive on larger programs, or the reverse.

#### How do I find out the winning price?

**Answer:** Ask the buyer. Some will share a range or say how far off you were. Otherwise note unknown and rely on the reason given. Do not invent a number, it will corrupt your price gap average.

#### Should lost quotes be reviewed in a meeting?

**Answer:** A monthly review of the largest losses is worthwhile. Look for repeating reasons, then adjust pricing rules, lead time promises or bid selection. Avoid relitigating single quotes without a pattern.

## Search terms

win loss analysis template, quote hit rate calculator, quote win rate manufacturing, why we lost the quote, hit rate by value, loss reason tracking, price gap vs winning bid, job shop win loss

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