Order processing time is the time between a purchase order arriving and its validated entry in the ERP, including the acknowledgement sent to the customer. Hardly anyone tracks it, because the ERP knows when the order was entered but not when the email came in. Yet it is what the customer experiences, and it often decides whether the order ships today or tomorrow.
Entry time and processing time are not the same thing
Ask a sales administration team how long an order takes and the answer comes in minutes: five, ten, twenty for a large order with references to look up. That is entry time, the time actually spent working on it.
Processing time is often counted in hours. It adds up the time the order sits in the inbox, the time it waits for an answer (a price to confirm, a reference to check with the sales rep) and the entry time itself.
Take an example, purely for illustration. An industrial supplies distributor receives an order at 9:05. Between 9:00 and 11:00, the two people in sales admin answer the phone, deal with a complaint about a short delivery and enter the orders that arrived earlier. The 9:05 order is opened at 11:30 and recorded at 11:38. Eight minutes of work, two and a half hours of waiting. If you only measure the first figure, you miss what the customer is going through.
Why this metric slips past dashboards
There are several reasons it is so rarely measured.
- The two timestamps live in two systems. The time of receipt is in the mailbox, the time of creation is in the ERP. Depending on how it is configured, the ERP sometimes records only the date, not the time.
- Shared inboxes muddy the trail. Once an order has been forwarded, read and marked unread again, or printed to be keyed in later, nobody knows how long it has been waiting.
- Nobody really owns it. Sales admin tracks the number of orders entered and the errors, logistics tracks shipments, sales management tracks revenue. Waiting time falls between all three.
- The average is falsely reassuring. A reasonable average can hide orders that wait all afternoon every Monday or at every month end.
What a growing delay really costs
The most direct cost comes from the warehouse cut-off. Most warehouses launch the day’s picking at a set time. An order received at 13:20 but entered at 14:30, when picking starts at 14:00, ships the next day. For an electrical wholesaler supplying building sites, that is the difference between an electrician equipped on Thursday morning and an electrician left waiting.
Then come the chasers. A customer who has had no acknowledgement after a few hours emails or calls to check the order arrived. Every chaser is one more interruption for the team, which slows down the orders still waiting even further. The delay feeds its own queue.
Then there are errors. A team catching up on a backlog types faster and checks less: a forgotten customer price, a pack size converted wrongly, the wrong delivery address. Those errors come back later as disputes, credit notes and returns. To put figures on these costs, see our article on the true cost of manual order entry.
Finally, urgent orders get lost in the flow. An emergency repair order for a plumbing and heating distributor, or a stock-out at a food industry customer, lands in the same inbox as routine replenishment orders and waits its turn like the rest if nobody spots it.
Measuring your processing time in a week
You don’t need a dedicated tool for a first measurement. Over a normal week, record for each order received by email:
- the time the email was received;
- the time the order was created in the ERP;
- if possible, the time the acknowledgement was sent.
A sample of a few days is enough for trends to emerge. Then look at the distribution rather than just the average:
- the median, which gives the delay for an ordinary order;
- the share of orders received before the picking cut-off that were entered in time;
- the delay for the slowest orders, for example the slowest tenth;
- the differences by time of arrival and day of the week.
That last breakdown is often the most telling. Orders arriving first thing in the morning, after the weekend or just before the cut-off do not fare the same as the others.
What target to set
There is no ideal processing time that suits everyone. A useful target depends on your delivery promise and how your warehouse is organised.
One wording that works well: “every order received before the picking cut-off is entered and confirmed before that time”. It can be checked every day, it means something to logistics as much as to sales admin, and it translates directly into a delivery date for the customer. You can add a maximum time for the acknowledgement, which reassures the customer and heads off many of the chasers.
How to reduce it
Some levers are organisational: sorting the inbox at set times, spotting urgent orders as soon as they arrive, keeping a phone-free slot before the cut-off. They help, but they are limited by the number of people available, especially during busy periods (see how to absorb order peaks without hiring).
Automation tackles the main cause: the queue. With Eledone, every purchase order is read as soon as it arrives, whatever its format (PDF, spreadsheet, email body, scan). Items are matched in the catalogue, prices, stock and credit exposure are checked in the ERP, then the order is created and the acknowledgement sent, following the rules defined with each customer. Orders that need checking, such as an unusual price or an ambiguous reference, are flagged to the team with the reason. Processing time no longer depends on how busy the team is, except for the cases that warrant it. The details are on the order entry page.
Once automation is in place, processing time also becomes the simplest metric for judging whether it works: just compare it with your starting measurement.
Frequently asked questions
Should we measure up to order entry or up to the acknowledgement?
Both are useful. Entry in the ERP determines picking and therefore delivery. The acknowledgement is what the customer sees; it is what stops the chasers.
Our ERP only records the date an order was created. What can we do?
For a first measurement, a manual log over a few days in a simple spreadsheet is enough. You can also use the time the acknowledgement was sent, which is recorded in the mailbox.
Should EDI orders be included in the calculation?
It is better to track them separately. They arrive already structured and flow in without waiting; mixing them with email orders would artificially lower the average and hide the real problem.
How can we test automation on our own orders?
You can try Eledone online on one of your purchase orders: the agent reads it and finds your items on your website, in about a minute. For a test on your real order flow, connected to your ERP, the simplest option is to book a demo.
Want to know how long your orders are waiting, and what you could gain?
Book a demo