5 SO vs DO Anomalies in SAP Business One You Must Watch

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In company operations, Sales Order (SO) and Delivery Order (DO) are two critical documents that must stay in sync.

However, in reality, differences or mismatches between them often occur—and are often not detected in time.

If these errors are ignored, the business may experience:

  • Inaccurate data
  • Potential financial loss
  • Audit issues
  • Customer complaints
  • Internal process bottlenecks

5 Anomalies in SAP Business One SO vs DO Reports

Here are the 5 most common anomalies that often appear in SO vs DO reports in SAP Business One—why they are dangerous, and how to detect them faster.

1. SO is “Closed”, but There Is Still Open Quantity

This is the most common anomaly. Example case:

  • SO status is Closed
  • But Qty Delivered < Qty Ordered

Why can this happen?

  • User manually closes the SO
  • There is a DO that has not been processed
  • Wrong data entry
  • Or the system does not enforce quantity validation when closing

Business risks:

  • Customer has not received the goods, but the system assumes the order is completed
  • Potential late deliveries
  • Mismatch between inventory and sales
  • Audit issues due to inconsistent figures

Why is this often overlooked?
Because it looks “normal” in the report—unless someone checks line by line.

2. Qty Delivered Exceeds Qty Ordered

This is rare, but very dangerous.

Example:

  • Customer orders 100 units
  • DO shows 105 units delivered

Common causes:

  • Input error
  • Duplicate DO
  • Mistakes in the warehouse

Risks:

  • Margin loss
  • Inventory shrinkage without being noticed
  • Audit red flags
  • Inconsistencies in FIFO/serial/batch tracking

If not checked regularly, this problem can continue unnoticed for a long time.

3. SO Has Been Open for a Long Time, but No DO Is Created

Example anomaly:

  • SO has been open for 60–90 days
  • There is no DO at all

Causes:

  • Dummy SO for simulation
  • Sales forgets to follow up
  • Customer cancels, but the SO is never closed
  • Goods are not yet available

Risks:

  • Inaccurate forecasting
  • Biased MRP/S&OP
  • Unrealistic sales pipeline

There is a hidden backlog

4. DO Exists Without SO (Document Mismatch)

This usually happens when:

  • Delivery is processed manually
  • Sales creates a DO without an SO
  • Emergency delivery process
  • Inconsistent data entry process

Risks:

  • Inaccurate sales data
  • Margins are difficult to analyze
  • Auditors will ask why
  • SO pipeline does not reflect real orders

Not every DO without SO is wrong—but it must be monitored.

5. Delivery Date Is Not Aligned with SO Date

Example issue:

  • SO dated on the 1st
  • DO dated on the 30th
  • Even though SLA is 3 days

Causes:

  • Warehouse overload
  • Backlog
  • Picking/packing queue
  • Wrong prioritization

Business risks:

  • SLA failure
  • Customer complaints
  • Decreasing sales due to poor lead time
  • Cash-flow delays

Many supply chain issues start from here.

Why Are These Anomalies Hard to Detect?

Because SO vs DO reports usually:

  • Contain hundreds or even thousands of rows
  • Staff are focused on daily operations, not analysis
  • Small issues seem “not significant”
  • It takes a long time to check each line
  • There is no system that automatically raises alerts

This is where AI can help.

How AI Helps Detect SO vs DO Anomalies Automatically

AI can:

  • Read the entire SO vs DO report in seconds
  • Detect quantity mismatches
  • Flag SO that are “Closed but still Open”
  • Identify DO without SO
  • Recognize unusual data patterns
  • Provide insights like a senior analyst

AI can even answer direct questions such as:
“Show me suspicious transactions for this month.”

For a live example, see the main article here:
👉 AI Insight for SAP Business One: A Smarter Way to Read Transaction Reports

Conclusion

The SO vs DO report looks simple, but it hides many potential issues that can impact:

  • Data accuracy
  • Customer satisfaction
  • Delivery process
  • Company profitability
  • Audit validity

By detecting anomalies earlier—especially with the help of AI—companies can work more efficiently and prevent major problems before they occur.

To learn how this AI works directly on your own data, please contact us for a demo.

What is SAP Business One?