Leak 28 · Sales & Quoting - Slow quote response
The RFQ arrives at 9 a.m. The quote goes out two days later, after a supplier price check and a cross-reference hunt. The customer decided yesterday.
Diagnostic note. Symptoms, required records, an initial check, and possible fixes. This shorter note does not include a full worked example.
What is it?
For routine MRO and stock items, the first acceptable quote often wins. Response time is a competitive variable that most distributors do not measure. The delay usually comes from a few repeatable causes: waiting on supplier pricing, looking up cross-references by hand, re-keying line items, and quotes queuing behind the day’s orders.
- Family
- Sales & Quoting
- Primary owner
- Inside Sales Lead
- Secondary owners
- VP Sales, Purchasing Manager
- Primary impact
- Win rate
- Typical data source
- Email timestamps, ERP quote dates, supplier quote requests
- Detection difficulty
- 30-day measurability
Ask yourself
Do you measure the time from RFQ received to quote sent, and do you know how it compares to competitors?
Yes, partially, no, or don’t know. “Don’t know” is the most useful answer, because it points at the test below.
What does it look like?
Warning signs. None of these proves the leak exists. They tell you where to look.
- No measurement of RFQ-to-quote time.
- Quotes waiting on supplier cost for items that were quoted last month.
- Line items typed by hand from emailed PDFs.
- Customers chasing quotes before they are sent.
What data do I need?
The minimum viable set. Most of it is already in your ERP.
| Field |
|---|
| RFQ received timestamp (email) |
| Quote sent timestamp |
| Line count and share of non-stock items |
| Outcome |
The initial check
Start with a small sample. Gathering the exports, agreements, or observations is separate from running the check; agree that work with the person who owns the records.
- 1Take twenty recent quotes and find the email that requested each.
- 2Calculate hours from request to quote for each, and note the reason for any over one business day.
- 3Group by cause: supplier pricing, cross-reference, re-keying, queue.
Response time = quote sent − RFQ received, in business hours; by cause of delay
Then ask one question: Which cause of delay appears most often, and is it a data problem or a workload problem?
How much could it be costing us?
A conservative range, not a headline. The goal is a number management can trust enough to investigate.
Quoted value per year × win-rate improvement from faster response × gross margin. Estimate the improvement from your own data by comparing win rate on same-day quotes to slower ones, controlling for quote type.
Common root causes
Fixes fall into three layers. Not every problem needs software, and almost none needs AI first.
- Process
- Quotes are not prioritized or timed, and supplier pricing requests have no standard.
- Data
- Cross-references and recent supplier costs are not maintained, so each quote starts from scratch.
- Technology
- RFQ intake is manual. Nothing extracts lines or checks stock and cost automatically.
What should we do?
Start with the simplest intervention that could solve it. Move down the list only if the one above is not enough.
Level 1
Visibility
A weekly response-time report by rep and quote type.
Level 2
Standard
A same-day target for stock quotes, and a maintained cross-reference table.
Level 3
Workflow
RFQ intake that extracts lines, matches them to your catalog, and gives the rep a reviewed list to price. See the RFQ intake example project.
Where AI helps
- Reading RFQs in any format and extracting line items.
- Matching customer and competitor part numbers to your catalog.
Where AI probably doesn’t
If quotes are slow because two people handle sixty a day, the fix may be staffing or prioritization before automation.
Before you call it a leak
- Speed matters less on engineered or project quotes, where accuracy and relationship dominate. Segment by quote type.
Think this might be happening in your business?
Turn the finding into a next step.
If the numbers say there is something there, send us what you found and we will help you decide whether it is worth a full investigation. No transaction files needed for that conversation.
Related leaks
- Leak 27 · SalesQuotes that are never followed upA quote goes out. Nothing happens. Nobody calls, because the quote is not in anyone’s queue. The customer bought from whoever called.
- Leak 30 · SalesLow-probability quotes consuming excessive laborA customer sends thirty RFQs a quarter and buys twice. Each RFQ takes an hour. Your quote desk is their free pricing service.
- Leak 34 · OperationsManual order-entry reworkA customer PO arrives as a PDF. Someone types it into the ERP, checks it against the quote, fixes the part numbers, and emails an acknowledgement. Fifteen minutes, forty times a day.
- Leak 40 · DataPoor substitute and cross-reference dataThe customer asks for a competitor’s part number. The rep asks the product manager, who checks a catalog, who calls the supplier. Two days later the customer has bought it elsewhere.
Let’s start with one thing.
What would better performance look like?
Bring a result you want to improve, a symptom, or a workflow you already understand. You do not need to know the bottleneck yet. We’ll help choose what to investigate first.
No transaction files needed for the first conversation.