There is more to the problem than data entry
Imagine a wholesaler receiving orders in a shared inbox. One customer sends a PDF; another puts the order in the email itself. An administrator looks up the customer account, matches product descriptions to internal codes and enters the order.
The steps look predictable until a customer uses an old product code or orders twenty items when the product is sold by the box. At that point, better extraction is not the whole answer. Someone needs to establish what the customer means.
Start with a limited scope, such as repeat orders from existing customers for known products. Urgent orders, amendments and new customers can stay with a person for now. This makes it easier to see which work is genuinely repeatable.
Agree what makes an order ready to process
Work with the order administration team to define the required information and checks. In this example:
- The customer and delivery address are known and appropriate for the order.
- A customer reference is available, or an agreed alternative is used.
- The product code, quantity and ordering unit are unambiguous.
- The requested delivery date and any special arrangements are clear.
- It is clear who can approve pricing, delivery or other exceptions.
A populated field is not necessarily a correct one. Check, for example, whether the product code exists and whether the quantity uses the agreed unit. Missing or unreadable information should not become a plausible guess.
Also agree how an authorised sender is identified. A familiar name at the top of an email is not, on its own, an adequate check.
One possible route from inbox to order system
The sequence below is a design example. Agree with the process owner which steps may run automatically.
Receive
Register the request and its source. Apply the agreed sender and attachment checks before processing the information.
Extract
Read the required fields from the message or document. Keep the connection to the source so a reviewer can see where a value came from.
Validate
Compare the fields with customer and product records and the agreed order rules. Set unclear cases aside.
Approve
Only pass orders that meet the agreed conditions. Where manual approval is required, the process waits for it.
Transfer
Pass the approved information to the order system through a suitable integration, import or other execution method.
Confirm
Check that the order has actually been recorded and retain its reference. Acknowledging an email is not the same as confirming a recorded order.
When the route changes
- Unclear information: clarify before approval.
- Repeated order: check whether it is a repeat or an amendment.
- No confirmation: investigate before submitting again.
An illustrative process. Exceptions return to a person before processing continues.
Three exceptions to decide on before you start
| Situation | Next step | What to avoid |
|---|---|---|
| The product or quantity is unclear | A person requests clarification; the order waits for a recorded decision. | Filling in a missing value automatically and submitting the order anyway. |
| An order is emailed again | Compare it with the existing request and establish whether it is a repeat, an amendment or a new order. | Treating every new email as a new order. |
| The order system gives no clear confirmation | Check whether the order was recorded before taking further action; investigate an uncertain outcome. | Blindly submitting it again and potentially creating a second order. |
Do not let the exception queue become another unattended inbox. Decide who takes ownership, what information they need and when to escalate. A correction should be traceable without reconstructing the entire process.
Choose the technology once the process is clear
First check whether the existing order system offers a suitable import or integration. If it does not, interacting through its user interface may be an option to investigate. Availability, access permissions and ongoing maintenance all affect that decision.
AI is optional. Consistent input may be handled with rules. For varied documents, you can investigate whether AI helps prepare the information, provided uncertain results remain visible and cannot independently create unwanted orders.
Also establish what data an external service would receive and who could access it. Do not use real order documents in a trial environment before agreeing how data will be used and protected.
Clearer input may be the better first step
If missing information causes most of the rework, an agreed order format, an existing customer portal or a clear work instruction may already help. Automation does not have to be the first investment.
A small trial is most useful when you know which part you want to improve. Compare not just entry time, but also the effort spent checking orders, resolving exceptions and maintaining the solution.
What should a trial help you assess?
Use examples that represent the actual work, including exceptions. Agree in advance when to proceed and when to revise the approach.
- How many requests can follow the agreed route?
- How much manual checking and rework remains?
- Are repeated and amended orders handled correctly?
- Can you tell whether each request is waiting, rejected or recorded?
- Can the responsible person understand and resolve failures?
Extracting a document successfully does not prove that the order process works. Assess the outcome in the order system and keep uncertainties visible. This example does not establish a general savings percentage.
Five questions about your own order process
- Which types of orders recur regularly?
- What information does someone currently look up, correct or request?
- Which exceptions genuinely require a decision?
- How do you currently know that an order was recorded correctly and only once?
- Who owns the process when something goes wrong?
Does this sound like your order process?
Describe where orders get held up or where information is entered again. We can discuss which step is worth investigating. You do not need to have chosen a solution first.
Discuss your order process