In many companies, more days pass between a customer's enquiry and the finished quote in their inbox than anyone would guess - and very few of them are working time. The enquiry is read, a question goes back, a price is looked up, an approval is awaited, and in the end everything is retyped from the email. Measure that chain and you rarely find one big mistake; you find a series of small waiting periods that add up. Then the second half of the problem begins: the quote is out, but nobody follows up, because the reminder sits in one person's head rather than in a workflow. This article shows where the days between incoming enquiry and sent quote really go, how text modules, line-item templates and prices from the leading system shorten drafting, how following up becomes a planned task with a reminder date and a named owner, and which three figures actually steer a sales operation. How we record such a workflow on site is described under process analysis.
Key takeaways
- Quote lead time consists mostly of waiting, not of work. The follow-up question, the price search, the approval and the retyping from the email are four separate idle points - each one can be measured and shortened on its own.
- Text modules and line-item templates are the fastest lever. Copying the last quote instead regularly carries over someone else's customer name, outdated prices and items that do not fit the new case.
- Prices and articles belong in one leading system that the quote pulls from. The spreadsheet copy in the sales folder is the most common reason a quote has to be corrected afterwards.
- Following up needs a date and a name. A reminder set automatically when the quote goes out replaces the note in someone's head and makes visible who holds which open case.
- Three figures are enough to steer the process: quote lead time from intake to dispatch, the win rate per quote type, and the value of open quotes banded by age.
Where the days between enquiry and quote really go
Ask a sales team how long it takes to draft a quote and the answer usually comes in hours: half an hour, maybe a full one, three for the larger jobs. Ask the systems how many days passed between an enquiry arriving and the quote being sent, and the picture looks different. Both answers are correct; they simply measure different things. The hours are the work, the days are the lead time. And the lead time decides whether the customer receives the quote while still deciding, or only once they have long since looked elsewhere. The same distinction between work and idle time sits behind the question of how to shorten lead times by attacking waiting periods.
Break the path from enquiry to quote into pieces and you typically find four idle points. The first is the follow-up question: a detail is missing - quantity, date, specification, delivery address - the email goes out and the case waits for an answer. The second is price discovery: the article is not on the current list, a supplier price has to be requested or a special price looked up. The third is approval: above a certain amount or discount somebody has to sign off, and that somebody is on the road. The fourth is data entry itself - retyping the details from the email into the quoting screen, often twice, because the enquiry was already noted in a list beforehand.
These four points cost money, and the amount can be quantified. According to the labour cost survey of the Federal Statistical Office, labour costs per hour worked in the German private sector averaged 45,00 Euro (Federal Statistical Office) in 2025. Allow three hours of pure work for a mid-sized quote - writing the query, looking up prices, entering, checking, sending - and you arrive at 135 Euro (worked example) per quote, without valuing the waiting time at all. How to set up that calculation without slipping into false precision is described in the article on what a single case really costs.
Why this keeps slipping in daily business
Text modules and line-item templates instead of copying the last quote
The most common route to a new quote is the last quote. You find a similar case, copy it, swap the customer name, adjust the quantities and send it off. That is fast and works out in the majority of cases. The cases where it does not work out, however, are expensive: a customer name left standing in the body text, payment terms from a different contract, a line price from two years ago, a service that is not being delivered at all this time. In our experience such things are not caught on dispatch but when the customer reads them - and then they cost trust and a correction round.
The alternative is unspectacular and present in almost every quoting system: modules instead of copies. A quote then consists of a fixed frame - cover text, scope description, line items, terms, validity - and each part comes from a maintained collection. The clerk selects rather than searching and overwriting. Two things decide whether this holds: the collection has to stay small enough to survey, and it needs a named owner for upkeep. A module collection without a keeper falls into disrepair within a year and is then bypassed again - with exactly the same copying behaviour as before.
Frame Module Source
----------------------+------------------------------+-------------------
Cover text | Salutation + enquiry ref. | Text module
Scope description | Variant by job type | Text module
Line items | Article, quantity, unit | Article master
Prices | List price + customer terms | Price list in system
Terms | Payment, delivery, execution | Text module
Validity | Date + binding period | Rule per quote type
Only the first column is identical in every quote. The second is selected,
the third is pulled by the system itself. What comes from a single source
needs no re-checking next time - and does not age inside an old copy.The difference is clearest when a price changes. If the price sits in the article master, you change it once and every future quote is current. If it sits in twenty copied quotes, you hardly ever update it completely, because nobody knows which copy will serve as the next template. The same logic applies to text with legal weight: payment terms, warranty notes, execution deadlines. Pull them from modules and you change them in one place. Copy them and you carry a different version in every quote - a pattern that resembles the retirement of grown spreadsheet solutions described in the article on replacing spreadsheet workarounds.
Prices and articles from the leading system
The second largest time trap in quoting is price discovery. It rarely costs much effort per case, but it interrupts - and interruptions create idle time. The clerk needs a price, does not find it on the screen, opens a spreadsheet in the sales folder, compares it against an email from purchasing and, in case of doubt, decides by feel. That spreadsheet is as a rule a copy, it is usually older than the prices in the inventory system, and in our experience it is the source of the renegotiation that takes place three weeks later.
The remedy is not a better spreadsheet but a decision about which system leads for which kind of data. Articles and list prices belong in the inventory system. Customer terms, volume tiers and discount limits belong on the customer record. The quote document pulls both and calculates; it stores no prices of its own. For that to hold, master data has to be sound - duplicates, orphaned articles and inconsistent units make any pricing rule worthless. The article on getting master data in order describes how that foundation is built, and the technical side of consolidation is covered by data integration.
Where quoting and inventory are separate programs, this is where the classic duplicate entry appears: the article is typed into the quote as free text because the number is not at hand, and entered properly again with the order. That exact pattern is covered in the article on eliminating duplicate data entry. That working with data is no side issue is also clear from the European target: for the Digital Decade, the European Commission has set out that by 2030 at least 75 percent (European Commission) of companies in the EU should use cloud services, data analytics or artificial intelligence. Anyone facing the selection of a new system will find the approach in the article on choosing business software requirements first.
One leading system per data type
Articles and list prices in the inventory system, terms on the customer record. The quote pulls the values and stores none of its own - so no price ages inside a copy.
Article number instead of free text
Every line item gets a real number. Free-text lines are the most common reason a quote cannot later be turned into an order without rework.
Tiers instead of ad-hoc discounts
Volume tiers and customer terms are stored, not calculated in someone's head. The discount becomes traceable and can be checked against the margin.
Approval limits stored as a rule
The amount or discount at which somebody has to countersign is a rule in the system. Approval then goes to a role with a deputy, not to a single person.
Validity and binding period on the document
Every quote carries an expiry date. It later drives the follow-up reminder and is what makes the list of open quotes analysable in the first place.
History per customer
Earlier quotes, accepted and rejected alike, stay visible on the customer. That saves searching the mailbox and supplies the data behind the win rate.
Follow-up as a planned routine, not a note in someone's head
A quote nobody tracks is an investment with no question asked in return. The effort has been spent, the outcome stays open, and after a few weeks nobody knows whether the customer walked away, is still deciding, or was simply forgotten. In many companies following up hangs on one person who remembers - and works exactly as long as that person is in the building, healthy and not on leave. A planned routine needs three things: a date, a name and a place where the outcome is recorded.
The date does not come from instinct but from the quote itself. Legally a quote is an offer, and whoever makes an offer is bound by it under Section 145 (German Civil Code) unless they exclude that binding effect. How long the binding lasts without an explicit deadline follows from Section 147 (2) (German Civil Code): until the point at which the offeror may expect a reply under ordinary circumstances. In practice you therefore put an explicit validity date on the document - and derive the follow-up dates from it: one well before expiry, one shortly before.
Step 1: Set the reminder when the quote goes out
The date is created automatically on dispatch, not by hand later. Two points work well: a first contact after a few days and a second shortly before validity expires. Both hang on the quote, not on a calendar.
Step 2: Name the owner
Every open quote has exactly one name on it. Without one, the case falls between the chairs. Ownership includes a stored deputy so that leave and illness do not break the chain.
Step 3: Make contact and note the outcome
The call or email is the easy part. What matters is that the outcome lands on the case: confirmed, postponed, too expensive, awarded elsewhere. That note is the basis of every later analysis.
Step 4: Reschedule when there is no reply
If no answer comes back, the case is not ticked off but given a new date - with the same owner. After the second or third unsuccessful round, a rule decides that the case is closed.
Step 5: Close the case properly
Every quote ends in a status: accepted, declined with a reason, expired. A quote without a final status distorts every figure and inflates the list of open cases until nobody looks at it any more.
The date is created automatically on dispatch, not by hand later. Two points work well: a first contact after a few days and a second shortly before validity expires. Both hang on the quote, not on a calendar.
Every open quote has exactly one name on it. Without one, the case falls between the chairs. Ownership includes a stored deputy so that leave and illness do not break the chain.
The call or email is the easy part. What matters is that the outcome lands on the case: confirmed, postponed, too expensive, awarded elsewhere. That note is the basis of every later analysis.
If no answer comes back, the case is not ticked off but given a new date - with the same owner. After the second or third unsuccessful round, a rule decides that the case is closed.
Every quote ends in a status: accepted, declined with a reason, expired. A quote without a final status distorts every figure and inflates the list of open cases until nobody looks at it any more.
Step four is where most routines fail. As long as rescheduling remains a case-by-case decision, it will not be taken under pressure. Written as a rule - follow up twice, then close with a reason - it no longer costs any attention. Technically this is a small workflow with a date, a reminder and a status change, of the kind process automation covers. Organisationally it resembles the digital approval paths described in the article on digitising approval workflows: there too, the stored deputy decides whether the case keeps moving.
From accepted quote to order without re-entering anything
When the customer says yes, work in many companies starts over. The quote sits as a PDF in a folder, the order is newly created in the inventory system, the line items are retyped, the prices looked up once more. That is not just duplicated effort, it is also where discrepancies arise: a line that reads differently in the order than in the quote, a price rounded during transfer, a delivery deadline that does not travel along. At the latest this surfaces on the invoice, and by then clearing it up costs more than the entry ever would have.
| Aspect | Quote is carried over | Order is entered from scratch |
|---|---|---|
| Effort on acceptance | A status change and a check | Full re-entry of every line item |
| Discrepancies | Ruled out, because the same data continues | Typically arise in price, quantity or deadline |
| Traceability | Quote, order and invoice hang together | Three separate documents with no shared number |
| Response time | Order confirmation possible the same day | Waits for free capacity in data entry |
| Costing comparison | Quoted price and result directly comparable | Only analysable by hand |
| Prerequisite | Line items with article numbers, not free text | None - but the same effort every time |
The technical prerequisite is modest: quote and order have to live in the same system or be joined by a connection that transfers line items with number, quantity, unit and price. Where two programs are involved, this is the classic case for an interface - with error handling and a log, so that an aborted transfer does not leave half an order behind. Because this handover also marks the start of order processing, it pays to look at the chain behind it: the article on finding bottlenecks in order processing shows where the time goes after the customer says yes.
Three figures that steer a sales operation
A quoting process can be run on three numbers, and at the start no more are needed. The first is quote lead time: the span from the enquiry arriving to the quote being sent, measured in calendar days, not in working hours. It is the only figure the customer experiences directly. The average alone is not enough - the spread is what matters, because a mean of four days can consist of nothing but four-day cases, or of many one-day cases plus a few that sat for three weeks.
The second is the win rate, and not as a single total but per quote type. Maintenance, new business, spare parts and project work behave completely differently; a combined figure hides exactly the differences that would support a decision. The third is the value of open quotes, banded by age: what is still outstanding, how old it is, and how much of it has already passed its validity. That banding makes the follow-up backlog visible without anyone working through lists. Which properties a figure needs to hold up in daily use is described in the article on metrics that actually help; the technical delivery is covered by metrics and reporting.
Quotes are legally binding
A dependable analysis also requires that ownership is kept clean on the technical side. If the accounts of departed colleagues stay active, open quotes hang on names nobody covers any more - the case appears on no reminder list and quietly expires. How access and responsibilities can be handed over in an orderly way when staff join and leave is covered in the article on account access when staff join and leave. Where the raw data for lead time comes from is shown in the article on reading processes from system data.
Which lever changes what
The three figures point to where to start. A long lead time with short working time points to waiting periods. A low win rate in one single quote type points to price or scope. A high value of old open quotes points to follow-up. The levers below are ordered by effort: the first three need no new software, the last three require a change in the system.
- Avoid return questions: count the details most often missing and turn them into a short enquiry form or a checklist for the phone. Whatever is present at first contact does not create two days of waiting later.
- Attach approval to a role: it is not the person who countersigns but the role, with a stored deputy. That often shortens the third idle point more than any speed-up of the work itself.
- Maintain and prune the modules: a manageable, formally owned collection of text and line-item templates replaces the copying of old quotes and keeps legally relevant passages in one place.
- Tie prices to their source: articles and terms come from the inventory system, the quote only calculates. The spreadsheet in the sales folder is not banned but made redundant - the safer way to be rid of it.
- Set the reminder automatically: dispatch creates two dates with an owner. A small piece of automation is enough, and the effect on the value of open quotes is usually measurable within a quarter.
- Set up the handover into the order: the status change creates the order from the existing line items. That saves the re-entry and keeps quote, order and invoice on the same case number.
The order matters: measure first, then change, then measure again. Introduce the reminder without knowing the value of open quotes beforehand and you cannot afterwards demonstrate that it worked - and you lose the argument for the next step. The measurement itself takes little effort, because the necessary timestamps occur in the systems anyway: the date the enquiry was created, the date the quote was sent, the date of the status change.
Fifty quotes are enough to start
What a company can prepare on its own
The larger part of the work comes before the technology, and it can be done without outside help. Work through the six points below and you have already described the quoting process and know which change is worth making. None of it requires specialist knowledge; it requires writing down honestly, for a few weeks, what actually happens.
- Pull the last fifty quotes and note two dates per case: when the enquiry arrived and when the quote went out. The difference is the lead time.
- Name the quote types that genuinely differ - maintenance, new business, spare parts, project. Without that split the win rate says little later on.
- For two weeks, write down the missing details that triggered a return question. The list is usually short and is the basis for a better enquiry form.
- Check where the price in the last quote came from: article master, price list, spreadsheet or memory. Every source outside the leading system is a finding.
- Write down the approval limits that actually apply, including deputies. They often exist as a habit but nowhere as a rule.
- Assign a name and a date to every open quote. Even this list, drawn up once by hand, makes the backlog visible.
The most expensive quote is not the one that was lost but the one that was forgotten. It cost the full effort, appears in no statistic, and does not even supply a reason to learn from next time.
The chain does not end with the order. Delivery follows, and payment stands at the end - and payment has lately been taking longer: in the first half of 2026 suppliers and lenders granted their customers an average payment term of 32,21 days (Creditreform), companies with more than 250 employees were granted 35,51 days (Creditreform), small firms only 26,37 days (Creditreform), and in arrears small firms added a further 10,52 days (Creditreform). Gain two days at the front and put follow-up in order at the back, and you shorten the whole distance from enquiry to money in the bank - the final leg is described in the article on automating dunning for faster payment.
Sources and Studies
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