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Case study · Manufacturing and distribution

Automating the order-to-invoice workflow for BBCP across Acumatica, SAP Ariba and SharePoint

BBCP has automated a connected order-to-invoice journey across MYOB Acumatica, SAP Ariba and SharePoint. AI-assisted extraction turns incoming purchase orders into matched sales orders, warehouse documents are captured automatically, and invoices are submitted back into SAP Ariba — cutting processing time by around 90% and saving roughly $150,000 a year.

15–20 min

Manual processing time per purchase order before automation

Baseline reported by BBCP prior to automation.

>90%

Reported reduction in order-processing time

Reduction reported by BBCP following implementation.

~$150,000

Estimated annual savings in processing time

Reported by BBCP following implementation.

7-step

Automated journey from PO receipt to invoice

PO received, AI extraction, sales order creation, Ariba order confirmation, warehouse docs scanned, shipment updated, invoice created.

The challenge

A manual, system-hopping order-to-invoice process.

BBCP's order-to-invoice process depended on manual handling between Outlook, MYOB Acumatica and SAP Ariba, with hours of manual matching every week.

Before automation, an admin would manually download each PO attachment, read the PDF, look up the customer and part numbers, determine the correct branch and warehouse, then create and attach the sales order in Acumatica by hand — around 15–20 minutes per order.

This manual, human-dependent process was error-prone and did not scale: warehouse teams received orders only after the full manual chain was complete, delaying fulfilment.

There was no consistent audit trail across the disconnected systems, and invoice submission back into SAP Ariba was a separate manual step.

System of record
MYOB Acumatica
Services applied
Workflow automation · Practical AI · System integration

Before and after

The same order, two very different journeys.

What a purchase order used to go through by hand, and the automated path it takes now.

Before · Manual process

  1. Purchase order email received with attachment

  2. Admin downloads attachment

  3. Reads PDF manually

  4. Looks up customer

  5. Looks up part numbers

  6. Determines branch & warehouse

  7. Creates sales order in Acumatica

  8. Uploads attachment to sales order

  9. Warehouse receives order (delayed)

15–20 minutes per PO · Human dependent · Manual errors · Limited scalability

After · Inturing automated workflow

  1. Email arrives

    orders@bbcp.com.au

  2. Power Automate trigger

  3. Separate attachments, convert to PDF

  4. AI extracts PO details

    • Customer
    • PO number
    • Line items
    • Quantities
    • Delivery address
  5. Business rules & matching

    API calls to Acumatica

    Customer match
    Part match
    Branch & warehouse match
  6. Exception / no match? Requires review

    YES
    Teams approval (human in the loop)
    NOStraight through
  7. Create sales order via Acumatica API

  8. Attach original PO to sales order

  9. Sales order available in Acumatica

  10. Warehouse receives order immediately

The approach

AI-assisted extraction, validated before it reaches the ERP.

The design principle was simple: automation handles the standard path completely, and people only see the records that genuinely need a decision.

  1. 01

    AI-assisted purchase order extraction

    Incoming PO emails to BBCP's orders inbox trigger Power Automate Desktop, which separates attachments, converts them to PDF, and uses AI Builder to extract structured order data — customer, PO number, line items, quantities and delivery address — from unstructured documents.

  2. 02

    Three-way matching against Acumatica master data

    Extracted details are matched against Acumatica via API calls: customer matching (handling real-world variants, such as recognising 'Rio Tinto Pty Ltd' as 'Rio Tinto Resources'), part/vendor matching, and branch and warehouse determination — all before a sales order is created.

  3. 03

    Exception handling stays human

    Where no confident match is found, the order is routed to a Teams approval flow for a person to review and resolve. Clean, matched orders flow straight through to sales order creation, with the original PO automatically attached.

  4. 04

    Connected through to fulfilment and invoicing

    Once confirmed, the sales order is created via the Acumatica API and made available to the warehouse immediately. Warehouse pick lists and kit assembly documents are scanned to SharePoint and linked back to the job, with shipment details updated automatically in Acumatica.

  5. 05

    Invoice submitted back into SAP Ariba

    At the end of the journey, the invoice is created and released in Acumatica, and Power Automate Desktop submits it into SAP Ariba — closing the loop from purchase order to invoice without manual re-entry.

Results

Measured outcomes, and general benefits.

We keep these separate deliberately. The first list is what BBCP reported. The second describes what this approach typically delivers and is not a client measurement.

Measured — reported by BBCP

  • Processing time per purchase order was cut by around 90%.
  • BBCP estimates savings of roughly $150,000 a year in processing time.
  • A full audit trail now exists across every transaction, from PO receipt through to invoice submission in SAP Ariba.
  • Warehouse teams receive confirmed orders immediately, rather than waiting on a manual chain of lookups and data entry.

General benefits — not client-verified measurements

  • Human review is retained exactly where it adds value: sales order review and release, warehouse physical processing, and invoice review and release.
  • Order entry capacity no longer scales purely with headcount.
  • Staff attention is directed to exceptions rather than routine data entry and matching.
  • The process is documented and supportable rather than dependent on one experienced operator.

Is order processing your bottleneck too?

If your team re-types orders into an ERP, a 30-minute discovery call is usually enough to size the opportunity.