# Quote Turnaround Time KPI and Queue Calculator

> Source: https://netray.co/tools/quote-turnaround-time-kpi-and-queue-calculator
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

Model how RFQ volume, quoting effort and estimator headcount drive utilization, queue wait and turnaround days.

## Category

mes-shop-floor

## Industry

Job Shops & Contract Manufacturing

## Audience

- Estimator
- Operations manager
- Sales manager

## Tool

**Kind:** calculator

**Currency:** $

**Inputs:**

#### RFQs received per week

**Key:** rfqs_week

**Type:** number

**Default:** 18

**Min:** 0

**Step:** 1

**Unit:** RFQs

#### Hands-on hours per quote

**Key:** touch_hours

**Type:** number

**Default:** 2.5

**Min:** 0.1

**Step:** 0.25

**Unit:** h

**Help:** Average estimator time per quote, excluding waiting.

#### Estimators

**Key:** estimators

**Type:** number

**Default:** 2

**Min:** 1

**Step:** 1

**Unit:** people

#### Productive quoting hours per estimator per week

**Key:** prod_hours

**Type:** number

**Default:** 28

**Min:** 5

**Max:** 40

**Step:** 1

**Unit:** h

**Help:** After meetings, shop-floor questions and admin.

#### Target turnaround

**Key:** target_days

**Type:** number

**Default:** 2

**Min:** 0.5

**Step:** 0.5

**Unit:** days

#### Hit rate

**Key:** hit_rate

**Type:** number

**Default:** 22

**Min:** 0

**Max:** 100

**Step:** 1

**Unit:** %

#### Average order value

**Key:** avg_order

**Type:** number

**Default:** 18000

**Min:** 0

**Step:** 500

**Unit:** $

**Outputs:**

#### Quoting hours demanded per week

**Key:** demand

**Expr:** rfqs_week * touch_hours

**Format:** hours

#### Quoting hours available per week

**Key:** capacity

**Expr:** estimators * prod_hours

**Format:** hours

#### Estimator utilization

**Key:** util

**Expr:** demand / max(capacity, 0.1) * 100

**Format:** percent

**Primary:** true

**Description:** Above about 85 percent, queue time grows quickly.

#### Average queue wait

**Key:** wait_hours

**Expr:** min(util, 98) / 100 / (1 - min(util, 98) / 100) * (touch_hours / estimators)

**Format:** hours

**Description:** M/M/1 approximation of pooled capacity: Wq = rho / (1 - rho) x average service time, with service time divided by headcount.

#### Expected turnaround

**Key:** turn_days

**Expr:** (touch_hours + wait_hours) / (prod_hours / 5)

**Format:** days

**Primary:** true

**Description:** Hands-on plus queue hours, converted using productive hours per day. Excludes customer clarification delays.

#### Quotes in process (Little's law)

**Key:** wip

**Expr:** rfqs_week * turn_days / 5

**Format:** decimal

**Description:** Average RFQs waiting or being worked: arrival rate per day multiplied by days in system.

#### Gap vs target turnaround

**Key:** gap

**Expr:** turn_days - target_days

**Format:** days

#### Orders won per month

**Key:** monthly_wins

**Expr:** rfqs_week * 52 / 12 * hit_rate / 100 * avg_order

**Format:** currency

**Description:** Monthly won value implied by the volume and hit rate.

**Chart:**

#### Turnaround days vs weekly RFQ volume

**Type:** line

**X:** rfqs_week

**From:** 4

**To:** 30

**Steps:** 27

**Series:**

- turn_days

**Disclaimer:** A queueing approximation that assumes random arrivals and similar quote effort. Real queues also depend on priority rules, interruptions and missing information.

## Content

**Intro:** Buyers often award to the first credible quote they receive. Turnaround time is therefore a sales metric as well as an operations metric. This calculator shows how quickly delays grow as estimator utilization climbs, using standard queueing math.

**Sections:**

#### How to use it

**Body:** Enter weekly RFQ volume, the hands-on hours a typical quote takes, headcount and realistic productive quoting hours per person. Productive hours are rarely above 30 per week once meetings and floor questions are removed. The calculator returns utilization, queue wait, turnaround in business days and the quote backlog implied by Little's law. Use the chart to see how the next 5 RFQs per week would change turnaround. Compare the result with the target to decide on hiring, templates or automation.

#### The math behind it

**Body:** Demand hours = RFQs per week x hands-on hours. Capacity = estimators x productive hours. Utilization rho = demand / capacity. For a single-server queue, average wait is rho / (1 - rho) x service time. We approximate a pooled team by dividing the service time by headcount, which is slightly pessimistic versus exact multi-server formulas but sufficient for planning. Turnaround = (hands-on + queue wait) / productive hours per day. Little's law states average work in system = arrival rate x time in system.

**Bullets:**

- Under 70 percent utilization: waits are small.
- 70 to 85 percent: waits noticeable, still manageable.
- Above 90 percent: small volume bumps cause multi-day delays.

#### Reading the result

**Body:** With the defaults, demand is 45 hours against 56 hours of capacity, about 80 percent utilization, which is workable but sensitive to spikes. Raise volume to 24 RFQs per week and utilization passes 100 percent: the queue grows without bound and turnaround climbs steeply, which the chart flattens at the 98 percent cap. The practical fix is usually reducing hands-on hours through templates and quote libraries before hiring.

#### Common mistakes

**Body:** Using paid hours instead of productive hours makes capacity look better than it is. Measuring turnaround from when you start rather than when the RFQ arrives hides queue time. Averages also hide long tails: track the 90th percentile turnaround in your ERP or CRM in addition to the mean.

**Cta:** If quote timestamps live in your ERP or CRM, we can help build a live turnaround dashboard by estimator and customer. This calculator stands alone for planning.

**Faq:**

#### What is a good quote turnaround time?

**Answer:** For routine job shop work, many buyers expect an answer within one to three business days. Complex assemblies and outside-processed parts take longer. Track your own median and 90th percentile and compare against how quickly winning competitors respond.

#### Why does turnaround rise so sharply near full utilization?

**Answer:** Queue wait scales with rho divided by one minus rho. At 80 percent the factor is 4, at 90 percent it is 9, and at 95 percent it is 19. Random bursts of RFQs overwhelm the team when there is little slack.

#### Does this include time waiting on the customer?

**Answer:** No. It models internal queue and work time only. Missing drawings, unclear specs and slow replies add elapsed days outside the model, which is why package completeness checks help.

#### How do I reduce hands-on quoting hours?

**Answer:** Standardize routings by part family, keep material and outside-process price lists current, reuse past quotes via ERP search, and pre-screen incomplete RFQs. Even a 20 percent cut in hands-on hours has a large effect near high utilization.

## Search terms

quote turnaround time calculator, quote turnaround kpi, estimator capacity calculator, rfq response time, quoting queue time, estimating department utilization, littles law quote backlog, how fast should we quote

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