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Data Template: Order to Cash - Sales Order Processing

SAP S/4HANA

Order to Cash - Sales Order Processing Attributes (23) Order to Cash - Sales Order Processing Activities (15) Extraction Guides (4)

Your Order to Cash - Sales Order Processing Data Template

This data template provides a comprehensive guide to collecting the necessary information for analyzing your Order to Cash - Sales Order Processing. It outlines the essential attributes and key activities required to build an accurate event log. Additionally, you'll find detailed guidance on how to extract this data from your SAP S/4HANA system to kickstart your process optimization.

Recommended attributes to collect
Key activities to track
Extraction guidance for SAP S/4HANA

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Order to Cash - Sales Order Processing Attributes

These are the recommended data fields to include in your event log for comprehensive order to cash, sales order processing analysis.

3 Required 7 Recommended 13 Optional

	Name	Description
	Activity Name ActivityName	The name of the business activity that occurred at a specific point in the sales order process.
Description This attribute describes a specific step or event in the sales order lifecycle, such as 'Sales Order Created', 'Goods Issue Posted', or 'Payment Received'. These activities are derived from various status changes, document creation dates, and log entries across different SAP modules. Analyzing the sequence and duration of these activities is the foundation of process mining. It allows for the visualization of process maps, the identification of bottlenecks between steps, and the analysis of process variants to understand how orders actually flow through the system compared to the designed process. Why it matters It defines the steps in the process, allowing for the construction of the process map and the analysis of process flow and bottlenecks. Where to get This is a derived attribute, typically generated during data extraction by mapping status changes or document creation events from tables like VBAK, LIKP, VBRK, and CDHDR/CDPOS to meaningful activity names. Examples Sales Order CreatedDelivery CreatedInvoice CreatedPayment Received
	Event Time EventTime	The timestamp indicating when a specific activity or event occurred.
Description Event Time provides the precise date and time for each activity in the process, forming the chronological backbone of the event log. For instance, it records when a sales order was created, when goods were shipped, and when an invoice was paid. This attribute is critical for all time-based analysis. It is used to calculate cycle times between activities, identify delays, measure process performance against service level agreements, and analyze the overall duration of the sales order process. The accuracy of these timestamps directly impacts the quality of the process mining insights. Why it matters This timestamp is essential for calculating all durations, cycle times, and waiting times, which are fundamental to performance analysis. Where to get This is a derived attribute, sourced from various date and time fields in SAP tables, such as ERDAT/ERZET (creation date/time) in VBAK, LIKP, VBRK, or change log timestamps from CDHDR. Examples 2023-01-15T09:00:00Z2023-01-18T14:30:00Z2023-01-25T11:20:00Z
	Sales Order Vbeln	The unique identifier for a sales document, serving as the primary case identifier for the Order to Cash process.
Description The Sales Order number uniquely identifies a customer's request for goods or services. It is the central object that links all activities in the sales order processing lifecycle, from creation and confirmation to delivery and invoicing. In process mining, this attribute is essential for tracking the end-to-end journey of each individual order. Analyzing processes by Sales Order allows businesses to identify bottlenecks, understand process variations, and measure key performance indicators like cycle time and on-time delivery for each specific customer transaction. Why it matters This is the core identifier that connects all related process events, enabling a complete case-level view of the order lifecycle. Where to get This attribute is the Sales Document number from the VBAK table (field VBELN). Examples 100002341000056710000891
	Customer Number Kunnr	The unique identifier for a customer account.
Description The Customer Number is a unique key assigned to each customer in the master data. It is used in all transactions related to that customer, including sales orders, deliveries, and payments. Analyzing the process from a customer's view is critical. This attribute allows for segmenting order performance by customer, identifying which customers experience the longest delays, and understanding how process execution differs for key accounts. It is fundamental for dashboards that analyze cycle times by customer segment. Why it matters This allows for customer-centric analysis, helping to identify process issues that affect specific customers or customer groups and measuring customer-specific KPIs. Where to get This attribute is the 'Sold-to party' or 'Customer Number' from the VBAK table (field KUNNR). Examples C000123C000456C000789
	Material Number Matnr	The unique identifier for a product or material being sold.
Description The Material Number is the unique key for a product in the material master data. Each line item in a sales order corresponds to a specific material number. This attribute enables product-centric process analysis. It is used to analyze if certain products are associated with longer processing times, more frequent changes, or higher cancellation rates. This insight can help uncover issues related to specific product lines, such as supply chain complexities or data inaccuracies. Why it matters It facilitates product-level analysis, revealing if certain materials or product lines are associated with process delays, rework, or other inefficiencies. Where to get This attribute is the 'Material Number' from the sales order item table VBAP (field MATNR). Examples PROD-1001PROD-2005SERV-A01
	Net Amount Netwr	The net value of the sales order item or document in the document currency.
Description Net Amount represents the value of the order after discounts and surcharges but before taxes. It is a key financial metric associated with each sales order. In process mining, this attribute provides critical business context. It is used to prioritize analysis on high-value orders, understand if order value correlates with processing time or complexity, and measure the financial impact of process inefficiencies like cancellations or delays. For example, analysis may show that high-value orders are frequently delayed by manual credit checks. Why it matters Provides financial context to each case, allowing for value-based analysis to prioritize improvements on high-impact orders and quantify the cost of delays. Where to get This attribute is the 'Net value of the order item in document currency' from the VBAP table (field NETWR) or aggregated from the VBAK table. Examples 1500.00250.5012345.75
	Requested Delivery Date Vdatu	The delivery date requested by the customer for the goods or services.
Description This date represents the customer's desired delivery time for the items on the sales order. It is a key piece of information used for planning, scheduling, and service level agreement (SLA) measurement. This attribute is essential for measuring customer service levels and logistical performance. It serves as the baseline for the 'On-Time Delivery Rate' KPI, where it is compared against the actual goods issue date or delivery date to determine if the customer's request was met. Analyzing deviations helps identify systemic issues in fulfillment or planning. Why it matters This is the primary date for measuring on-time delivery performance, a critical KPI for customer satisfaction and supply chain efficiency. Where to get This attribute is the 'Requested delivery date' from the sales order schedule line table VBEP (field VDATU). Examples 2023-02-012023-03-152023-04-20
	Sales Document Type Auart	A classification that distinguishes different types of sales documents, such as standard orders, returns, or credit memos.
Description The Sales Document Type controls how a sales document is processed in SAP. It defines details like the number range, required fields, and the overall transaction flow. Examples include 'OR' for a standard order or 'RE' for a returns order. In process mining, this attribute is crucial for segmenting the analysis. Comparing the process flows for different document types can reveal significant variations in cycle times, rework rates, and automation levels. This helps in tailoring process improvement initiatives to specific order types. Why it matters It allows for the segmentation of sales orders into different categories, enabling a comparative analysis of how different types of orders are processed. Where to get This attribute is the 'Sales Document Type' from the VBAK table (field AUART). Examples ORRECRSO
	Sales Organization Vkorg	An organizational unit responsible for the sale of specific products or services.
Description The Sales Organization represents a selling unit in a company. It is responsible for negotiating sales terms and distributing goods and services. Each sales transaction is assigned to a specific sales organization. This attribute is a primary dimension for performance analysis. By filtering or comparing data across different sales organizations, businesses can benchmark performance, identify regional or divisional best practices, and understand how process efficiency varies geographically or by business unit. Why it matters Enables performance comparison and benchmarking across different business units, regions, or companies within a corporate group. Where to get This attribute is the 'Sales Organization' from the VBAK table (field VKORG). Examples 10002000US01DE01
	User Name Ernam	The SAP user ID of the person who created or last changed the document.
Description This attribute captures the user responsible for a particular activity, such as creating the sales order or posting the goods issue. It links process steps to the individuals or teams who performed them. Analyzing activities by user helps in identifying training needs, understanding workload distribution, and detecting deviations that may be specific to certain users. It is also valuable for compliance and audit purposes, providing a clear record of who performed key actions within the process. Why it matters It enables analysis of process performance by user or team, helping to identify top performers, training opportunities, and workload distribution. Where to get This attribute is the 'Name of Person who Created the Object' from tables like VBAK (field ERNAM for creation) or from change document headers in CDHDR (field UNAME). Examples CBURNSDSCRANTONJHALPERT
	Distribution Channel Vtweg	The channel through which products or services reach the customer, such as retail, wholesale, or online.
Description The Distribution Channel defines the method of selling and distributing products to customers. It is a key organizational element that, along with the Sales Organization, defines the sales area. Analyzing processes by distribution channel helps businesses understand if certain channels are more or less efficient than others. For example, orders from the 'Online' channel might be highly automated and fast, while orders from the 'Direct Sales' channel might involve more manual steps and take longer. This enables targeted improvements for specific channels. Why it matters Allows for performance analysis across different sales channels, such as web, direct sales, or retail, to identify channel-specific bottlenecks or best practices. Where to get This attribute is the 'Distribution Channel' from the VBAK table (field VTWEG). Examples 102001
	Division Spart	An organizational unit that represents a specific product line or business area.
Description The Division is used to group materials or services, often representing a product line. It is part of the sales area definition and helps structure the business from a product-oriented point of view. This attribute is useful for analyzing process performance for different product groups. It can help answer questions like, 'Does the processing of spare parts orders differ from the processing of finished goods orders?' This segmentation is key for the 'Cycle Time by Product Line' KPI and related dashboard analysis. Why it matters Enables process analysis based on product line or business area, helping to uncover performance differences between various parts of the business. Where to get This attribute is the 'Division' from the VBAK or VBAP tables (field SPART). Examples 000105
	Document Currency Waerk	The currency code for the amounts specified in the sales document.
Description This attribute defines the currency (e.g., USD, EUR, JPY) for monetary values like the Net Amount within the sales document. It provides the necessary context for correctly interpreting and aggregating financial data. While not directly a driver of process flow, the currency is essential for any financial analysis. It ensures that monetary values are understood correctly and is necessary when converting amounts to a common currency for reporting on a global scale. Why it matters Provides essential context for all monetary values, ensuring accurate financial analysis and reporting, especially in global operations. Where to get This attribute is the 'SD document currency' from the VBAK table (field WAERK). Examples USDEURGBP
	End Time EndTime	The timestamp indicating when a specific activity or event concluded.
Description EndTime marks the completion time for an individual activity. While StartTime indicates when a task began, EndTime captures when it finished, making it possible to measure the duration of active work. This attribute is crucial for accurately calculating activity processing times. It allows analysts to distinguish between the time spent actively working on a task (Processing Time = EndTime - StartTime) and the time spent waiting for the next task to begin (Waiting Time = NextActivity.StartTime - CurrentActivity.EndTime). This distinction is fundamental for precise bottleneck analysis. Why it matters It enables the precise calculation of activity processing time, which is essential for distinguishing active work time from idle waiting time. Where to get This is a derived attribute. For some activities, it may correspond to a specific timestamp in SAP. For others, it's often inferred or set equal to the StartTime if the event is considered instantaneous. Examples 2023-01-15T09:05:10Z2023-01-18T15:00:00Z2023-01-25T11:20:00Z
	Is Manual Entry IsManualEntry	A flag that indicates whether the sales order was created manually versus through an automated channel like EDI or an e-commerce portal.
Description This attribute distinguishes between orders entered by a user directly in the SAP GUI and those created automatically via electronic data interchange (EDI), APIs, or other integrated systems. This information can sometimes be inferred from the user who created the order (e.g., a system user vs. a human user) or specific indicators in the sales document. This attribute is essential for automation analysis and supports the 'Manual Order Entry Rate' KPI. It allows for a direct comparison of process efficiency, error rates, and cycle times between manually and automatically created orders, helping to build a business case for further automation. Why it matters It helps measure the level of automation in the order entry process and compare the efficiency and error rates of manual versus automated orders. Where to get This is often a derived attribute. It can be inferred by checking the 'Created by' user (ERNAM) in VBAK against a list of known system/batch users, or by specific channel indicators. Examples truefalse
	Is On Time Delivery IsOnTimeDelivery	A boolean flag indicating whether the order was delivered on or before the confirmed or requested delivery date.
Description This attribute provides a clear, binary outcome for delivery performance on each order. It is calculated by comparing the actual 'Goods Issue Posted' timestamp with the 'Requested Delivery Date' (VDATU) or a confirmed delivery date from the order schedule. This flag is the foundation for the 'On-Time Delivery Rate' KPI and the 'Delivery Date Promise Adherence' dashboard. It simplifies analysis by allowing users to quickly segment all orders into 'on-time' and 'late' categories, and then investigate the process characteristics of each group to find the root causes of delays. Why it matters Directly measures fulfillment performance against customer expectations, forming the basis of the critical 'On-Time Delivery Rate' KPI. Where to get This is a calculated attribute, derived by comparing the timestamp of the 'Goods Issue Posted' activity with the 'Requested Delivery Date' (VBEP-VDATU). Examples truefalse
	Is Rework IsRework	A boolean flag indicating if an activity or case involves rework, such as a repeated confirmation or significant change.
Description This flag is used to identify sales orders that have undergone rework, such as being changed after confirmation or having the same activity occur multiple times. The logic for setting this flag can be based on the occurrence of 'Sales Order Changed' activities or multiple 'Order Confirmed' events for the same case. This attribute directly supports the 'Sales Order Change and Rework Rate' dashboard and related KPIs. It allows for easy filtering and quantification of rework, helping businesses to measure the cost and frequency of process inefficiencies and target the root causes of these deviations. Why it matters This flag helps quantify the frequency and impact of rework, enabling analysis to reduce process deviations, manual changes, and inefficiencies. Where to get This is a calculated attribute. The logic is defined during data transformation, often by detecting repeated activities or specific change events (e.g., from CDHDR/CDPOS tables). Examples truefalse
	Last Data Update LastDataUpdate	The timestamp of the most recent data refresh or extraction from the source system.
Description This attribute indicates when the data for the process analysis was last updated. It provides transparency to business users and analysts about the freshness of the data they are viewing, ensuring they understand the time frame covered by the analysis. In dashboards and reports, this information is vital for context. It helps users understand if they are looking at real-time information or a periodic snapshot, which affects the interpretation of recent trends and operational performance. Why it matters Informs users about the timeliness of the data, ensuring they understand the temporal context of the analysis and preventing misinterpretations. Where to get This attribute is generated by the data extraction or ETL tool, recording the timestamp when the data pipeline was last executed. Examples 2023-10-27T02:00:00Z2023-10-28T02:00:00Z
	Order Quantity Kwmeng	The quantity of the material ordered in a specific sales document item.
Description This attribute represents the number of units of a specific material requested by the customer in a sales order line item. It is a fundamental piece of transactional data. Analyzing order quantity provides valuable business context. It can be used to segment analysis by order size (small vs. large orders) to see if volume correlates with processing efficiency. Furthermore, it's a key metric for business reporting and understanding the scale of operations. Why it matters Allows for analysis based on order size, helping to understand if order volume impacts processing times, complexity, or error rates. Where to get This attribute is the 'Cumulative order quantity in sales units' from the VBAP table (field KWMENG). Examples 101505
	Overall Delivery Status Lfstk	The overall delivery status of the sales order, indicating if it's not yet processed, partially delivered, or fully delivered.
Description This status field provides a high-level summary of the fulfillment progress for a sales document. It is aggregated from the status of all its line items to show whether the order is open, in progress, or complete from a delivery standpoint. In process analysis, this attribute is valuable for understanding the current state of open orders and for filtering cases. For example, analyzing only 'Fully Delivered' orders provides a view of completed processes, while analyzing 'Not yet processed' orders can help identify backlogs and initial bottlenecks. Why it matters Provides a snapshot of an order's fulfillment progress, allowing for filtering and analysis based on whether an order is open, partially, or fully delivered. Where to get This attribute is the 'Overall delivery status of all items' from the VBUK status table (field LFSTK). Examples ABC
	Processing Time ProcessingTime	The duration of time spent actively working on a specific activity.
Description Processing Time, also known as activity duration, measures the time between the start and end of a single process step. It represents the active work time, as opposed to waiting time between steps. This calculated metric is crucial for identifying which specific activities are the most time-consuming in the process. It is a key component of bottleneck analysis and helps pinpoint inefficiencies within a task, such as a lengthy 'Credit Check Performed' activity, which might indicate a need for automation or resource allocation. Why it matters It measures the active work time of an activity, helping to pinpoint which specific tasks are the most time-consuming and are candidates for optimization. Where to get This is a calculated attribute, derived by taking the difference between the EndTime and StartTime of an activity. Examples 360086400300
	Rejection Reason Abgru	A code indicating the reason why a sales order or item was rejected or canceled.
Description The Rejection Reason provides context when a sales order or a specific line item is canceled. These reasons are typically configured by the business and can include codes for 'Out of stock', 'Customer canceled', or 'Incorrect price'. This attribute is fundamental for root cause analysis of order cancellations. By analyzing the most frequent rejection reasons, businesses can identify underlying problems in their sales, inventory, or pricing processes. This insight is crucial for the 'Sales Order Cancellation Analysis' dashboard to reduce lost sales and improve efficiency. Why it matters It provides the 'why' behind order cancellations, enabling root cause analysis to address issues like pricing errors, stock unavailability, or poor data quality. Where to get This attribute is the 'Reason for rejection of quotations and sales orders' from the sales order item table VBAP (field ABGRU). Examples 010215
	Source System SourceSystemId	Identifies the source system from which the data was extracted.
Description This attribute specifies the system of origin for the event data, for example, 'SAP S/4HANA Production' or 'ECC Quality'. In environments with multiple ERP systems or a mix of legacy and modern platforms, this field is crucial for data lineage and validation. For analysis, it allows for filtering and comparing processes across different systems or organizational instances. This can reveal variations in process execution or data quality that are specific to a particular system landscape. Why it matters It provides context about the data's origin, which is crucial in multi-system environments for ensuring data integrity and enabling comparative analysis. Where to get This is typically a static value added during the data extraction process to label the dataset with its system of origin. Examples S4H_PROD_100ECC_DEV_200S4H_QAS_100

Required Recommended Optional

Order to Cash - Sales Order Processing Activities

These are the key process steps and milestones to capture in your event log for accurate process discovery and bottleneck identification.

7 Recommended 8 Optional

	Activity	Description
	Delivery Created	This activity signifies the creation of an outbound delivery document, which initiates the shipping and logistics process. This is an explicit event where a delivery document is created in reference to the sales order.
Why it matters This milestone marks the transition from sales processing to logistics. Analyzing the time from order confirmation to delivery creation helps identify bottlenecks in fulfillment planning. Where to get Captured from the LIKP table (SD Document: Delivery Header Data) creation timestamp. The link back to the sales order is stored in the VBFA table (Sales Document Flow). Capture Captured from the creation timestamp of the delivery document header in table LIKP. Event type explicit
	Goods Issue Posted	This is the legal and financial handover of the goods, marking their official departure from the company's inventory. This explicit event reduces stock levels and is a prerequisite for invoicing.
Why it matters Posting Goods Issue is a critical financial and logistical milestone. It is often considered the point of 'shipment' and directly impacts inventory valuation and revenue recognition. Where to get The timestamp is recorded in the LIKP table (WADAT_IST - Actual goods movement date) when the goods issue is posted. The VBFA document flow table links this back to the sales order. Capture Captured from the actual goods movement date (LIKP-WADAT_IST) on the delivery header. Event type explicit
	Invoice Created	Represents the creation of the customer billing document, which details the products, quantities, and prices for payment. This is an explicit event where an invoice document is generated in reference to the delivery or sales order.
Why it matters This activity marks the start of the payment collection cycle. The time between goods issue and invoice creation is a key KPI for measuring the efficiency of the billing process. Where to get Captured from the VBRK table (Billing Document: Header Data) creation date (ERDAT) and time (ERZET). The VBFA table links the invoice back to the preceding documents. Capture Captured from the creation timestamp of the billing document header in table VBRK. Event type explicit
	Order Closed	Marks the final status of a sales order, indicating that all related processes, including delivery, invoicing, and payment, are complete. This is inferred from the overall status of the sales document.
Why it matters This activity provides a definitive end point for successfully completed orders in the process analysis. It ensures that the end-to-end cycle time is measured accurately for fulfilled orders. Where to get Inferred from the overall status field (VBUK-GBSTK) of the sales document changing to 'C' (Completely processed). The timestamp must be derived from the last update to a related document, like payment clearing. Capture Inferred when the document status VBUK-GBSTK becomes 'C', with the timestamp taken from the final event (e.g., Payment Received). Event type inferred
	Payment Received	This activity marks the successful completion of the process, where the customer's payment has been received and cleared against the open invoice. This is an explicit financial posting that closes the accounts receivable item.
Why it matters This is the final, value-realizing step of the Order to Cash cycle. Analyzing the time from invoice to payment is essential for managing cash flow and Days Sales Outstanding (DSO). Where to get Captured from the clearing date (AUGDT) in the BSEG table (Accounting Document Segment) for the line item related to the customer payment that clears the invoice. Capture Captured from the clearing date (AUGDT) on the cleared customer item in table BSEG or the clearing document in BKPF. Event type explicit
	Sales Order Confirmed	Marks the point where material availability has been checked and a confirmed quantity and delivery date have been committed for the order items. This is inferred from the creation of schedule lines with confirmed quantities.
Why it matters This is a critical milestone representing the commitment to the customer. The time taken to reach this stage (Order Confirmation Cycle Time) is a key measure of internal processing efficiency. Where to get Inferred from the creation of records in the VBEP table (Sales Document: Schedule Line Data) with a confirmed quantity (BMENG > 0) for the sales order items. Capture Derived from the creation date of the first schedule line in table VBEP with a confirmed quantity. Event type inferred
	Sales Order Created	This activity marks the initiation of the sales process when a new sales order is formally created in the system. This event is captured explicitly when a user saves a new sales order document (e.g., using transaction VA01), which creates a new entry in the VBAK table.
Why it matters This is the primary start event for the Order to Cash process. Analyzing the time from this activity to subsequent milestones is fundamental for measuring overall cycle time and identifying initial processing delays. Where to get Recorded in the VBAK table (Sales Document Header Data) upon creation. The creation date (ERDAT) and time (ERZET) fields provide the timestamp. Capture Captured from the creation timestamp of the sales order header record in table VBAK. Event type explicit
	Accounting Document Created	This activity occurs when the invoice is successfully posted to the financial accounting module, creating journal entries. It's an explicit event that generates a corresponding document in the financial ledger.
Why it matters This event confirms that the revenue from the sale has been formally recognized in the company's books. Delays here can affect the accuracy of financial reporting. Where to get Captured from the BKPF table (Accounting Document Header) creation date (CPUDT) and time (CPUTM). The VBRK table often stores the corresponding accounting document number (VBRK-BELNR). Capture Captured from the creation timestamp of the accounting document header in table BKPF. Event type explicit
	Credit Check Performed	Represents the completion of a creditworthiness check for the customer associated with the sales order. This can be an automated or manual step, and its completion is typically inferred from a change in the overall credit status of the document.
Why it matters Credit checks are a common bottleneck that can significantly delay order confirmation and fulfillment. Tracking this activity helps measure its duration and impact on the overall process. Where to get Inferred from status updates in the VBUK table (Sales Document: Header Status and Administrative Data). A change in the credit status field (CMGST) indicates the completion of the check. Capture Inferred from a timestamped change in the credit status field (VBUK-CMGST) of the sales document. Event type inferred
	Goods Picked	Represents the completion of the physical process of picking the goods from the warehouse storage locations for the outbound delivery. This is typically inferred from a status update on the delivery document.
Why it matters Picking is a key step in the warehouse fulfillment process. Tracking its completion helps to measure warehouse efficiency and identify delays before goods are ready for shipment. Where to get Inferred from status fields in the LIPS (Delivery Item) or LIKP (Delivery Header) tables, such as the picking status (KOSTA). A change to 'Completely picked' signifies the event. Capture Inferred from a timestamped change in the picking status field (e.g., LIKP-KOSTA) of the delivery document. Event type inferred
	Invoice Sent to Customer	Indicates that the generated invoice has been transmitted to the customer, for example, via print, email, or EDI. This is typically inferred from the processing log of the output determination system.
Why it matters The payment clock often starts when the customer receives the invoice. Tracking this event is crucial for accurately measuring the Payment Collection Cycle Time. Where to get Inferred from records in the NAST table (Message Status), which logs the processing of output types like invoices. The processing date and time can serve as the event timestamp. Capture Inferred from the processing timestamp of the relevant output message record in table NAST. Event type inferred
	Sales Order Block Removed	Represents the removal of a processing block, allowing the sales order to proceed to the next stage. This is inferred by detecting a change in the relevant block fields from a set value back to a blank or cleared status.
Why it matters Tracking the time it takes to remove blocks is crucial for understanding the duration of delays. This activity helps quantify rework and the efficiency of resolution processes. Where to get Inferred from the change data tables (CDHDR, CDPOS) where a block field on the sales order (e.g., VBAK-LIFSK) is changed from a non-blank value to blank. Capture Identified by detecting a change in a block field (e.g., VBAK-LIFSK) from a non-blank value back to a blank value. Event type inferred
	Sales Order Block Set	This activity occurs when a processing block is applied to the sales order, preventing subsequent activities like delivery creation. This is inferred by monitoring change logs for specific block fields on the sales order header or item.
Why it matters Setting blocks is a key deviation from the happy path. Identifying why and how often blocks are set helps uncover systemic issues with data quality, pricing, or customer master data. Where to get Inferred from the change data tables (CDHDR, CDPOS) for block fields on the sales order, such as VBAK-AUFSP (Order block) or VBAK-LIFSK (Delivery block). Capture Identified by detecting a change in a block field (e.g., VBAK-LIFSK) from a blank value to a non-blank value. Event type inferred
	Sales Order Changed	Indicates that a significant attribute of an existing sales order, such as quantity, price, or requested delivery date, has been modified after initial creation. This event is explicitly captured in SAP's change log tables.
Why it matters Frequent changes indicate process instability and can lead to rework, fulfillment errors, and delays. This activity is key to measuring the Sales Order Change Rate and identifying root causes. Where to get Captured from the change data tables, CDHDR (Change document header) and CDPOS (Change document items), which log modifications to sales order tables like VBAK and VBAP. Capture Identified from entries in the CDHDR table linked to the sales order object (OBJECTCLAS 'VERKBELEG'). Event type explicit
	Sales Order Item Rejected	Represents the cancellation or rejection of a specific line item on a sales order before it is fully processed. This is inferred from the application of a 'Reason for Rejection' to an item.
Why it matters This activity represents an unsuccessful outcome for part of an order. Analyzing when and why items are rejected helps identify issues with product availability, pricing, or customer requirements. Where to get Inferred from change logs (CDHDR, CDPOS) showing when the 'Reason for Rejection' field (VBAP-ABGRU) is populated for a sales order item. Capture Inferred from the timestamp when the VBAP-ABGRU field is populated for one or more line items. Event type inferred

Recommended Optional

Extraction Guides

How to get your data from SAP S/4HANA

Steps

Prerequisites Check: Ensure your SAP user has the necessary authorizations to access the required analytical Core Data Services (CDS) views. This includes display access for sales documents, deliveries, billing documents, financial documents, and change documents. The key views used are I_SalesDocument, I_SalesDocumentItem, I_DeliveryDocument, I_BillingDocument, I_JournalEntry, and I_ChangeDocument.
Choose an SQL Client: Select a tool that can connect to your SAP S/4HANA system and execute SQL queries against its CDS views. Common tools include SAP HANA Studio, the Eclipse IDE with ADT (ABAP Development Tools), or a generic SQL client like DBeaver configured with the SAP HANA JDBC driver.
Prepare the Extraction Query: Copy the complete SQL query provided in the query section of this document into your chosen SQL client's editor.
Define Extraction Parameters: Locate the placeholder variables in the WHERE clause of the initial SalesOrders CTE (Common Table Expression). Replace :START_DATE and :END_DATE with your desired date range (e.g., '20230101' and '20230630'). It is recommended to start with a smaller date range, such as one month, to test performance. You can also add or modify filters for SalesOrganization (Vkorg) or SalesDocumentType (Auart) to narrow the scope.
Execute the Query: Run the modified query. Depending on the data volume and the selected date range, the execution may take several minutes. The query is designed to union data from multiple sources to build a comprehensive event log.
Review the Results: Once the query finishes, review the output to ensure it contains the expected columns (Vbeln, ActivityName, EventTime, etc.) and that data is populated as anticipated. Check for a variety of activities across different sales orders.
Export the Data: Export the complete result set from your SQL client to a CSV (Comma-Separated Values) file. Ensure the file uses UTF-8 encoding to prevent character issues.
Prepare for Upload: Before uploading to a process mining tool, ensure the column headers in the CSV file match the expected field names (Case ID, Activity, Timestamp). Verify that the EventTime column is in a consistent timestamp format, such as YYYY-MM-DD HH:MI:SS.

Configuration

Target CDS Views: The extraction primarily uses I_SalesDocument, I_SalesDocumentItem, I_DocumentFlow, I_DeliveryDocument, I_BillingDocument, I_JournalEntry, and I_ChangeDocument. Your system must have these standard VDM (Virtual Data Model) views active.
Date Range: The query is filtered by the sales order creation date (CreationDate). It is critical to set the :START_DATE and :END_DATE parameters to define a manageable scope. For initial analysis, a period of 3 to 6 months is recommended.
Document Filters: You can further restrict the data by uncommenting and specifying values for SalesOrganization, SalesDocumentType, or other fields in the initial SalesOrders CTE. This is highly recommended to improve performance and focus the analysis on relevant processes.
Authorizations: The executing user requires read access to all underlying tables and CDS views referenced in the query. This spans sales (SD), logistics (LE), billing (SD), and finance (FI) data. Lack of authorization on any single view may cause the entire query to fail.
Performance: This is a complex query with multiple unions and joins. For very large datasets, execution time can be significant. Running the query during off-peak hours and applying restrictive filters is crucial for managing system load.

a Sample Query sql

/*
-- =============================================================================================
-- Process: Order to Cash - Sales Order Processing
-- System: SAP S/4HANA
-- Method: CDS View Extraction
-- Description: Extracts a detailed event log for the Order to Cash process using standard CDS views.
-- =============================================================================================
*/

WITH SalesOrders AS (
    -- Select the base set of sales orders to be analyzed.
    -- *** Set your extraction parameters here ***
    SELECT SalesDocument, CreationDate, CreationTime, LastChangeDate, SalesDocumentType, SalesOrganization, SoldToParty, LastChangedByUser, RequestedDeliveryDate
    FROM I_SalesDocument
    WHERE CreationDate BETWEEN :START_DATE AND :END_DATE -- Example: '20230101' AND '20230630'
    -- AND SalesOrganization = '[Your Sales Org]'
    -- AND SalesDocumentType = '[Your Order Type]'
),

ChangeDocs AS (
    -- Pre-select change document data for performance.
    SELECT 
        OBJECTCLAS, 
        OBJECTID, 
        CHANGENR, 
        TABNAME, 
        FNAME, 
        CHNGIND, 
        VALUE_NEW, 
        VALUE_OLD,
        CAST(CDHDR_UDATE AS VARCHAR(8)) || CAST(CDHDR_UTIME AS VARCHAR(6)) as EventTimestamp
    FROM I_ChangeDocument
    WHERE OBJECTCLAS = 'VERKBELEG' -- Sales Document Object Class
      AND OBJECTID IN (SELECT SalesDocument FROM SalesOrders)
)

-- 1. Sales Order Created
SELECT
    SD.SalesDocument AS "Vbeln",
    'Sales Order Created' AS "ActivityName",
    TO_TIMESTAMP(SD.CreationDate || LPAD(SD.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    SD.LastChangedByUser AS "Ernam",
    SD.SalesDocumentType AS "Auart",
    SD.SalesOrganization AS "Vkorg",
    SD.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SD.RequestedDeliveryDate AS "Vdatu"
FROM SalesOrders AS SD

UNION ALL

-- 2. Credit Check Performed (Inferred from status change)
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Credit Check Performed' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBAK' AND CD.FNAME = 'CMGST' AND CD.VALUE_NEW <> 'A' -- Status changed to something other than 'Not Performed'

UNION ALL

-- 3. Sales Order Block Set
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Sales Order Block Set' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBAK' AND CD.FNAME IN ('LIFSK', 'FAKSK') AND CD.VALUE_NEW <> ''

UNION ALL

-- 4. Sales Order Block Removed
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Sales Order Block Removed' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBAK' AND CD.FNAME IN ('LIFSK', 'FAKSK') AND CD.VALUE_NEW = '' AND CD.VALUE_OLD <> ''

UNION ALL

-- 5. Sales Order Changed (Significant Fields)
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Sales Order Changed' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME IN ('VBAP', 'VBAK') AND CD.FNAME IN ('KWMENG', 'NETWR', 'VDATU', 'KETDAT')

UNION ALL

-- 6. Sales Order Confirmed
SELECT DISTINCT
    SDI.SalesDocument AS "Vbeln",
    'Sales Order Confirmed' AS "ActivityName",
    TO_TIMESTAMP(SDS.CreationDate || '000000', 'YYYYMMDDHH24MISS') AS "EventTime",
    SD.LastChangedByUser AS "Ernam",
    SD.SalesDocumentType AS "Auart",
    SD.SalesOrganization AS "Vkorg",
    SD.SoldToParty AS "Kunnr",
    SDI.Material AS "Matnr",
    SDI.NetAmount AS "Netwr",
    SD.RequestedDeliveryDate AS "Vdatu"
FROM I_SalesDocumentScheduleLine AS SDS
JOIN I_SalesDocumentItem AS SDI ON SDS.SalesDocument = SDI.SalesDocument AND SDS.SalesDocumentItem = SDI.SalesDocumentItem
JOIN SalesOrders SD ON SDI.SalesDocument = SD.SalesDocument
WHERE SDS.ConfirmedQuantity > 0

UNION ALL

-- 7. Delivery Created
SELECT
    DF.PrecedingDocument AS "Vbeln",
    'Delivery Created' AS "ActivityName",
    TO_TIMESTAMP(DD.CreationDate || LPAD(DD.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    DD.CreatedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_DeliveryDocument AS DD ON DF.SubsequentDocument = DD.DeliveryDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.PrecedingDocumentCategory = 'C' AND DF.SubsequentDocumentCategory = 'J'

UNION ALL

-- 8. Goods Picked (Inferred from Picking Status Completion)
SELECT
    DF.PrecedingDocument AS "Vbeln",
    'Goods Picked' AS "ActivityName",
    TO_TIMESTAMP(DDI.LastChangeDate || '120000', 'YYYYMMDDHH24MISS') AS "EventTime", -- Note: Time is an approximation
    DDI.LastChangedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    DDI.Material AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_DeliveryDocumentItem AS DDI ON DF.SubsequentDocument = DDI.DeliveryDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.PrecedingDocumentCategory = 'C' AND DDI.PickingStatus = 'C' AND DDI.LastChangeDate IS NOT NULL

UNION ALL

-- 9. Goods Issue Posted
SELECT
    DF.PrecedingDocument AS "Vbeln",
    'Goods Issue Posted' AS "ActivityName",
    TO_TIMESTAMP(DD.ActualGoodsMovementDate || LPAD(DD.ActualGoodsMovementTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    DD.LastChangedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_DeliveryDocument AS DD ON DF.SubsequentDocument = DD.DeliveryDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.PrecedingDocumentCategory = 'C' AND DF.SubsequentDocumentCategory = 'R' AND DD.ActualGoodsMovementDate IS NOT NULL

UNION ALL

-- 10. Invoice Created
SELECT
    DF.PrecedingDocument AS "Vbeln",
    'Invoice Created' AS "ActivityName",
    TO_TIMESTAMP(BD.CreationDate || LPAD(BD.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    BD.CreatedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_BillingDocument AS BD ON DF.SubsequentDocument = BD.BillingDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.PrecedingDocumentCategory IN ('C', 'J') AND DF.SubsequentDocumentCategory = 'M'

UNION ALL

-- 11. Accounting Document Created
SELECT
    DF_SO_INV.PrecedingDocument AS "Vbeln",
    'Accounting Document Created' AS "ActivityName",
    TO_TIMESTAMP(JE.CreationDate || LPAD(JE.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    JE.CreatedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF_SO_INV
JOIN I_BillingDocument BD ON DF_SO_INV.SubsequentDocument = BD.BillingDocument
JOIN I_JournalEntry JE ON BD.AccountingDocument = JE.AccountingDocument
JOIN SalesOrders AS SO ON DF_SO_INV.PrecedingDocument = SO.SalesDocument
WHERE DF_SO_INV.PrecedingDocumentCategory = 'C' AND DF_SO_INV.SubsequentDocumentCategory = 'M' AND BD.AccountingDocument IS NOT NULL

UNION ALL

-- 12. Invoice Sent to Customer (Inferred from output request processing)
SELECT 
    DF.PrecedingDocument AS "Vbeln",
    'Invoice Sent to Customer' AS "ActivityName",
    TO_TIMESTAMP(BOR.CreationDate || LPAD(BOR.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    BOR.CreatedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_BillingDocumentOutputRequest AS BOR ON DF.SubsequentDocument = BOR.BillingDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.SubsequentDocumentCategory = 'M' AND BOR.ProcessingStatus = '3' -- Successfully processed

UNION ALL

-- 13. Payment Received (Inferred from FI Clearing Document)
SELECT
    DF_SO_INV.PrecedingDocument AS "Vbeln",
    'Payment Received' AS "ActivityName",
    TO_TIMESTAMP(JEI.ClearingDate || '120000', 'YYYYMMDDHH24MISS') AS "EventTime", -- Note: Time is an approximation
    JEI.LastChangedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF_SO_INV
JOIN I_BillingDocument BD ON DF_SO_INV.SubsequentDocument = BD.BillingDocument
JOIN I_JournalEntryItem JEI ON BD.AccountingDocument = JEI.SourceDocument
JOIN SalesOrders AS SO ON DF_SO_INV.PrecedingDocument = SO.SalesDocument
WHERE DF_SO_INV.PrecedingDocumentCategory = 'C' AND DF_SO_INV.SubsequentDocumentCategory = 'M' AND JEI.ClearingDate IS NOT NULL AND JEI.Customer IS NOT NULL

UNION ALL

-- 14. Sales Order Item Rejected
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Sales Order Item Rejected' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr", -- Note: Can be enhanced to find the specific item material
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBAP' AND CD.FNAME = 'ABGRU' AND CD.VALUE_NEW <> ''

UNION ALL

-- 15. Order Closed (Inferred from Overall Status)
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Order Closed' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBUK' AND CD.FNAME = 'GBSTK' AND CD.VALUE_NEW = 'C' -- Overall status = 'Completed'

Steps

Prerequisites Check: Ensure your SAP user has the necessary authorizations to access the required analytical Core Data Services (CDS) views. This includes display access for sales documents, deliveries, billing documents, financial documents, and change documents. The key views used are I_SalesDocument, I_SalesDocumentItem, I_DeliveryDocument, I_BillingDocument, I_JournalEntry, and I_ChangeDocument.
Choose an SQL Client: Select a tool that can connect to your SAP S/4HANA system and execute SQL queries against its CDS views. Common tools include SAP HANA Studio, the Eclipse IDE with ADT (ABAP Development Tools), or a generic SQL client like DBeaver configured with the SAP HANA JDBC driver.
Prepare the Extraction Query: Copy the complete SQL query provided in the query section of this document into your chosen SQL client's editor.
Define Extraction Parameters: Locate the placeholder variables in the WHERE clause of the initial SalesOrders CTE (Common Table Expression). Replace :START_DATE and :END_DATE with your desired date range (e.g., '20230101' and '20230630'). It is recommended to start with a smaller date range, such as one month, to test performance. You can also add or modify filters for SalesOrganization (Vkorg) or SalesDocumentType (Auart) to narrow the scope.
Execute the Query: Run the modified query. Depending on the data volume and the selected date range, the execution may take several minutes. The query is designed to union data from multiple sources to build a comprehensive event log.
Review the Results: Once the query finishes, review the output to ensure it contains the expected columns (Vbeln, ActivityName, EventTime, etc.) and that data is populated as anticipated. Check for a variety of activities across different sales orders.
Export the Data: Export the complete result set from your SQL client to a CSV (Comma-Separated Values) file. Ensure the file uses UTF-8 encoding to prevent character issues.
Prepare for Upload: Before uploading to a process mining tool, ensure the column headers in the CSV file match the expected field names (Case ID, Activity, Timestamp). Verify that the EventTime column is in a consistent timestamp format, such as YYYY-MM-DD HH:MI:SS.

Configuration

Target CDS Views: The extraction primarily uses I_SalesDocument, I_SalesDocumentItem, I_DocumentFlow, I_DeliveryDocument, I_BillingDocument, I_JournalEntry, and I_ChangeDocument. Your system must have these standard VDM (Virtual Data Model) views active.
Date Range: The query is filtered by the sales order creation date (CreationDate). It is critical to set the :START_DATE and :END_DATE parameters to define a manageable scope. For initial analysis, a period of 3 to 6 months is recommended.
Document Filters: You can further restrict the data by uncommenting and specifying values for SalesOrganization, SalesDocumentType, or other fields in the initial SalesOrders CTE. This is highly recommended to improve performance and focus the analysis on relevant processes.
Authorizations: The executing user requires read access to all underlying tables and CDS views referenced in the query. This spans sales (SD), logistics (LE), billing (SD), and finance (FI) data. Lack of authorization on any single view may cause the entire query to fail.
Performance: This is a complex query with multiple unions and joins. For very large datasets, execution time can be significant. Running the query during off-peak hours and applying restrictive filters is crucial for managing system load.

a Sample Query sql

/*
-- =============================================================================================
-- Process: Order to Cash - Sales Order Processing
-- System: SAP S/4HANA
-- Method: CDS View Extraction
-- Description: Extracts a detailed event log for the Order to Cash process using standard CDS views.
-- =============================================================================================
*/

WITH SalesOrders AS (
    -- Select the base set of sales orders to be analyzed.
    -- *** Set your extraction parameters here ***
    SELECT SalesDocument, CreationDate, CreationTime, LastChangeDate, SalesDocumentType, SalesOrganization, SoldToParty, LastChangedByUser, RequestedDeliveryDate
    FROM I_SalesDocument
    WHERE CreationDate BETWEEN :START_DATE AND :END_DATE -- Example: '20230101' AND '20230630'
    -- AND SalesOrganization = '[Your Sales Org]'
    -- AND SalesDocumentType = '[Your Order Type]'
),

ChangeDocs AS (
    -- Pre-select change document data for performance.
    SELECT 
        OBJECTCLAS, 
        OBJECTID, 
        CHANGENR, 
        TABNAME, 
        FNAME, 
        CHNGIND, 
        VALUE_NEW, 
        VALUE_OLD,
        CAST(CDHDR_UDATE AS VARCHAR(8)) || CAST(CDHDR_UTIME AS VARCHAR(6)) as EventTimestamp
    FROM I_ChangeDocument
    WHERE OBJECTCLAS = 'VERKBELEG' -- Sales Document Object Class
      AND OBJECTID IN (SELECT SalesDocument FROM SalesOrders)
)

-- 1. Sales Order Created
SELECT
    SD.SalesDocument AS "Vbeln",
    'Sales Order Created' AS "ActivityName",
    TO_TIMESTAMP(SD.CreationDate || LPAD(SD.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    SD.LastChangedByUser AS "Ernam",
    SD.SalesDocumentType AS "Auart",
    SD.SalesOrganization AS "Vkorg",
    SD.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SD.RequestedDeliveryDate AS "Vdatu"
FROM SalesOrders AS SD

UNION ALL

-- 2. Credit Check Performed (Inferred from status change)
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Credit Check Performed' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBAK' AND CD.FNAME = 'CMGST' AND CD.VALUE_NEW <> 'A' -- Status changed to something other than 'Not Performed'

UNION ALL

-- 3. Sales Order Block Set
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Sales Order Block Set' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBAK' AND CD.FNAME IN ('LIFSK', 'FAKSK') AND CD.VALUE_NEW <> ''

UNION ALL

-- 4. Sales Order Block Removed
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Sales Order Block Removed' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBAK' AND CD.FNAME IN ('LIFSK', 'FAKSK') AND CD.VALUE_NEW = '' AND CD.VALUE_OLD <> ''

UNION ALL

-- 5. Sales Order Changed (Significant Fields)
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Sales Order Changed' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME IN ('VBAP', 'VBAK') AND CD.FNAME IN ('KWMENG', 'NETWR', 'VDATU', 'KETDAT')

UNION ALL

-- 6. Sales Order Confirmed
SELECT DISTINCT
    SDI.SalesDocument AS "Vbeln",
    'Sales Order Confirmed' AS "ActivityName",
    TO_TIMESTAMP(SDS.CreationDate || '000000', 'YYYYMMDDHH24MISS') AS "EventTime",
    SD.LastChangedByUser AS "Ernam",
    SD.SalesDocumentType AS "Auart",
    SD.SalesOrganization AS "Vkorg",
    SD.SoldToParty AS "Kunnr",
    SDI.Material AS "Matnr",
    SDI.NetAmount AS "Netwr",
    SD.RequestedDeliveryDate AS "Vdatu"
FROM I_SalesDocumentScheduleLine AS SDS
JOIN I_SalesDocumentItem AS SDI ON SDS.SalesDocument = SDI.SalesDocument AND SDS.SalesDocumentItem = SDI.SalesDocumentItem
JOIN SalesOrders SD ON SDI.SalesDocument = SD.SalesDocument
WHERE SDS.ConfirmedQuantity > 0

UNION ALL

-- 7. Delivery Created
SELECT
    DF.PrecedingDocument AS "Vbeln",
    'Delivery Created' AS "ActivityName",
    TO_TIMESTAMP(DD.CreationDate || LPAD(DD.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    DD.CreatedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_DeliveryDocument AS DD ON DF.SubsequentDocument = DD.DeliveryDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.PrecedingDocumentCategory = 'C' AND DF.SubsequentDocumentCategory = 'J'

UNION ALL

-- 8. Goods Picked (Inferred from Picking Status Completion)
SELECT
    DF.PrecedingDocument AS "Vbeln",
    'Goods Picked' AS "ActivityName",
    TO_TIMESTAMP(DDI.LastChangeDate || '120000', 'YYYYMMDDHH24MISS') AS "EventTime", -- Note: Time is an approximation
    DDI.LastChangedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    DDI.Material AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_DeliveryDocumentItem AS DDI ON DF.SubsequentDocument = DDI.DeliveryDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.PrecedingDocumentCategory = 'C' AND DDI.PickingStatus = 'C' AND DDI.LastChangeDate IS NOT NULL

UNION ALL

-- 9. Goods Issue Posted
SELECT
    DF.PrecedingDocument AS "Vbeln",
    'Goods Issue Posted' AS "ActivityName",
    TO_TIMESTAMP(DD.ActualGoodsMovementDate || LPAD(DD.ActualGoodsMovementTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    DD.LastChangedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_DeliveryDocument AS DD ON DF.SubsequentDocument = DD.DeliveryDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.PrecedingDocumentCategory = 'C' AND DF.SubsequentDocumentCategory = 'R' AND DD.ActualGoodsMovementDate IS NOT NULL

UNION ALL

-- 10. Invoice Created
SELECT
    DF.PrecedingDocument AS "Vbeln",
    'Invoice Created' AS "ActivityName",
    TO_TIMESTAMP(BD.CreationDate || LPAD(BD.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    BD.CreatedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_BillingDocument AS BD ON DF.SubsequentDocument = BD.BillingDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.PrecedingDocumentCategory IN ('C', 'J') AND DF.SubsequentDocumentCategory = 'M'

UNION ALL

-- 11. Accounting Document Created
SELECT
    DF_SO_INV.PrecedingDocument AS "Vbeln",
    'Accounting Document Created' AS "ActivityName",
    TO_TIMESTAMP(JE.CreationDate || LPAD(JE.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    JE.CreatedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF_SO_INV
JOIN I_BillingDocument BD ON DF_SO_INV.SubsequentDocument = BD.BillingDocument
JOIN I_JournalEntry JE ON BD.AccountingDocument = JE.AccountingDocument
JOIN SalesOrders AS SO ON DF_SO_INV.PrecedingDocument = SO.SalesDocument
WHERE DF_SO_INV.PrecedingDocumentCategory = 'C' AND DF_SO_INV.SubsequentDocumentCategory = 'M' AND BD.AccountingDocument IS NOT NULL

UNION ALL

-- 12. Invoice Sent to Customer (Inferred from output request processing)
SELECT 
    DF.PrecedingDocument AS "Vbeln",
    'Invoice Sent to Customer' AS "ActivityName",
    TO_TIMESTAMP(BOR.CreationDate || LPAD(BOR.CreationTime, 6, '0'), 'YYYYMMDDHH24MISS') AS "EventTime",
    BOR.CreatedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF
JOIN I_BillingDocumentOutputRequest AS BOR ON DF.SubsequentDocument = BOR.BillingDocument
JOIN SalesOrders AS SO ON DF.PrecedingDocument = SO.SalesDocument
WHERE DF.SubsequentDocumentCategory = 'M' AND BOR.ProcessingStatus = '3' -- Successfully processed

UNION ALL

-- 13. Payment Received (Inferred from FI Clearing Document)
SELECT
    DF_SO_INV.PrecedingDocument AS "Vbeln",
    'Payment Received' AS "ActivityName",
    TO_TIMESTAMP(JEI.ClearingDate || '120000', 'YYYYMMDDHH24MISS') AS "EventTime", -- Note: Time is an approximation
    JEI.LastChangedByUser AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM I_DocumentFlow AS DF_SO_INV
JOIN I_BillingDocument BD ON DF_SO_INV.SubsequentDocument = BD.BillingDocument
JOIN I_JournalEntryItem JEI ON BD.AccountingDocument = JEI.SourceDocument
JOIN SalesOrders AS SO ON DF_SO_INV.PrecedingDocument = SO.SalesDocument
WHERE DF_SO_INV.PrecedingDocumentCategory = 'C' AND DF_SO_INV.SubsequentDocumentCategory = 'M' AND JEI.ClearingDate IS NOT NULL AND JEI.Customer IS NOT NULL

UNION ALL

-- 14. Sales Order Item Rejected
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Sales Order Item Rejected' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr", -- Note: Can be enhanced to find the specific item material
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBAP' AND CD.FNAME = 'ABGRU' AND CD.VALUE_NEW <> ''

UNION ALL

-- 15. Order Closed (Inferred from Overall Status)
SELECT DISTINCT
    CD.OBJECTID AS "Vbeln",
    'Order Closed' AS "ActivityName",
    TO_TIMESTAMP(SUBSTRING(CD.EventTimestamp, 1, 8) || SUBSTRING(CD.EventTimestamp, 9, 6), 'YYYYMMDDHH24MISS') AS "EventTime",
    I_CDHDR.USERNAME AS "Ernam",
    SO.SalesDocumentType AS "Auart",
    SO.SalesOrganization AS "Vkorg",
    SO.SoldToParty AS "Kunnr",
    CAST(NULL AS NVARCHAR(40)) AS "Matnr",
    CAST(NULL AS DECIMAL(15,2)) AS "Netwr",
    SO.RequestedDeliveryDate AS "Vdatu"
FROM ChangeDocs AS CD
JOIN I_ChangeDocumentHeader AS I_CDHDR ON CD.CHANGENR = I_CDHDR.CHANGENR
JOIN SalesOrders SO ON CD.OBJECTID = SO.SalesDocument
WHERE CD.TABNAME = 'VBUK' AND CD.FNAME = 'GBSTK' AND CD.VALUE_NEW = 'C' -- Overall status = 'Completed'

Steps

Prerequisites: Ensure you have Python 3.6+ and the SAP NW RFC SDK installed on the machine where the script will run. The SDK must match your Python architecture (64-bit). Install the required Python libraries using pip: pip install pyrfc pandas.
SAP User and Authorizations: Work with your SAP security team to create an RFC-enabled user. This user requires authorizations for the S_RFC authorization object, access to function group RFC1, and execute permissions for the function modules RFC_READ_TABLE and BAPI_SALESORDER_GETLIST. Additionally, the user needs read access to the following tables: VBAK, VBAP, VBEP, VBUK, VBUP, VBFA, LIKP, VBRK, BKPF, BSAD, NAST, CDHDR, and CDPOS.
Script Setup: Save the provided Python script to a file, for instance, extract_otc_log.py.
Configure Connection and Filters: Open the script and modify the connection parameters in the sap_config dictionary with your SAP system's details (hostname, system number, client, user, and password). Adjust the filter_params dictionary to define the desired date range and any specific sales organizations or document types you want to include.
Execute the Script: Run the script from your terminal using the command: python extract_otc_log.py. The script will connect to SAP, fetch the sales order data, and process each order to build the event log.
Retrieve the Event Log: Upon successful completion, the script will generate a sales_order_event_log.csv file in the same directory. This file contains the extracted process data.
Initial Data Review: Open the CSV file with a spreadsheet program or data analysis tool. Verify that it contains the expected columns (Vbeln, ActivityName, EventTime, etc.) and that data appears to be populated correctly.
Prepare for Upload: Ensure the column headers in the CSV file match the required attribute names for your process mining tool. Check that the EventTime column is in a consistent format (e.g., YYYY-MM-DD HH:MM:SS). The file is now ready for upload to ProcessMind.

Configuration

SAP Connection Parameters: The script requires standard RFC connection details. These should be stored securely and not hardcoded directly if used in a production environment.
- ashost: Application server host
- sysnr: System number
- client: Client number
- user: RFC-enabled SAP username
- passwd: Password for the SAP user
Extraction Filters: It is critical to apply filters to manage data volume and focus the analysis. Key filters include:
- date_from / date_to: The creation date range for sales orders. A range of 3-6 months is recommended for an initial analysis.
- sales_orgs: A list of Sales Organization codes (VKORG) to include.
- doc_types: A list of Sales Document Types (AUART) to include (e.g., 'OR' for Standard Order).
Required Python Libraries: The script depends on two main libraries which must be installed in your Python environment.
- pyrfc: The official SAP connector for Python.
- pandas: Used for data manipulation and for creating the final CSV output file.
SAP Prerequisites: The target SAP S/4HANA system must have the RFC interface enabled. The SAP NetWeaver RFC SDK libraries must be accessible by the Python script's execution environment.
Performance Considerations: This script makes numerous RFC calls, especially when reading change logs and document flows for each sales order. For very large datasets (hundreds of thousands of orders), execution time can be significant. It is recommended to run the extraction in batches by adjusting the date range filter.

a Sample Query python

import pandas as pd
from pyrfc import Connection, ABAPApplicationError, LogonError
from datetime import datetime

class=class="hl-string">"hl-comment"># --- 1. Configuration: Update with your SAP system details and filters ---
sap_config = {
    class="hl-string">"ashost": class="hl-string">"[your_sap_host]",
    class="hl-string">"sysnr": class="hl-string">"[your_system_number]",
    class="hl-string">"client": class="hl-string">"[your_client]",
    class="hl-string">"user": class="hl-string">"[your_rfc_user]",
    class="hl-string">"passwd": class="hl-string">"[your_password]",
}

filter_params = {
    class="hl-string">"date_from": class="hl-string">"YYYYMMDD",  class=class="hl-string">"hl-comment"># Example: class="hl-string">"20230101"
    class="hl-string">"date_to": class="hl-string">"YYYYMMDD",    class=class="hl-string">"hl-comment"># Example: class="hl-string">"20230630"
    class="hl-string">"sales_orgs": [class="hl-string">"[your_sales_org]"], class=class="hl-string">"hl-comment"># Example: [class="hl-string">"1000", class="hl-string">"1010"]
    class="hl-string">"doc_types": [class="hl-string">"[your_doc_type]"]    class=class="hl-string">"hl-comment"># Example: [class="hl-string">"OR"]
}

class=class="hl-string">"hl-comment"># --- Helper function to query SAP tables ---
def query_sap_table(conn, table_name, fields, options):
    try:
        result = conn.call(class="hl-string">'RFC_READ_TABLE', QUERY_TABLE=table_name, DELIMITER=class="hl-string">'|', FIELDS=fields, OPTIONS=options)
        data = [dict(zip(fields, row[class="hl-string">'WA'].strip().split(class="hl-string">'|'))) for row in result[class="hl-string">'DATA']]
        return data
    except ABAPApplicationError as e:
        print(fclass="hl-string">"Error querying table {table_name}: {e}")
        return []

class=class="hl-string">"hl-comment"># --- Main Extraction Logic ---
def main():
    event_log = []

    try:
        print(class="hl-string">"Connecting to SAP...")
        conn = Connection(**sap_config)
        print(class="hl-string">"Connection successful.")

        class=class="hl-string">"hl-comment"># --- 2. Get list of sales orders based on filters ---
        print(class="hl-string">"Fetching sales orders...")
        vbak_options = [
            fclass="hl-string">"ERDAT GE '{filter_params['date_from']}'",
            fclass="hl-string">"AND ERDAT LE '{filter_params['date_to']}'",
            fclass="hl-string">"AND VKORG IN ({','.join([f\"class="hl-string">'{so}'\class="hl-string">" for so in filter_params['sales_orgs']])})",
            fclass="hl-string">"AND AUART IN ({','.join([f\"class="hl-string">'{dt}'\class="hl-string">" for dt in filter_params['doc_types']])})"
        ]
        sales_orders = query_sap_table(conn, class="hl-string">'VBAK', [class="hl-string">'VBELN'], vbak_options)
        
        if not sales_orders:
            print(class="hl-string">"No sales orders found for the given criteria.")
            return

        print(fclass="hl-string">"Found {len(sales_orders)} sales orders to process.")

        class=class="hl-string">"hl-comment"># --- 3. Loop through each sales order to extract events ---
        for i, so in enumerate(sales_orders):
            vbeln = so[class="hl-string">'VBELN']
            print(fclass="hl-string">"Processing SO {vbeln} ({i+1}/{len(sales_orders)})... ")

            class=class="hl-string">"hl-comment"># Fetch common data for this SO
            vbak_data = query_sap_table(conn, class="hl-string">'VBAK', [class="hl-string">'ERDAT', class="hl-string">'ERZET', class="hl-string">'ERNAM', class="hl-string">'AUART', class="hl-string">'VKORG', class="hl-string">'KUNNR', class="hl-string">'VDATU'], [fclass="hl-string">"VBELN = '{vbeln}'"])[0]
            vbap_data = query_sap_table(conn, class="hl-string">'VBAP', [class="hl-string">'MATNR', class="hl-string">'NETWR'], [fclass="hl-string">"VBELN = '{vbeln}'"])
            doc_flow = query_sap_table(conn, class="hl-string">'VBFA', [class="hl-string">'VBELN', class="hl-string">'POSNN', class="hl-string">'VBTYP_N', class="hl-string">'ERDAT', class="hl-string">'ERZET'], [fclass="hl-string">"VBELV = '{vbeln}'"])
            cdhdr_data = query_sap_table(conn, class="hl-string">'CDHDR', [class="hl-string">'CHANGENR', class="hl-string">'UDATE', class="hl-string">'UTIME'], [fclass="hl-string">"OBJECTCLAS = 'VERKBELEG' AND OBJECTID = '{vbeln}'"])
            
            change_numbers = [c[class="hl-string">'CHANGENR'] for c in cdhdr_data]
            cdpos_data = []
            if change_numbers:
                cdpos_options = [fclass="hl-string">"OBJECTCLAS = 'VERKBELEG' AND OBJECTID = '{vbeln}' AND CHANGENR IN ({','.join([f\"class="hl-string">'{cn}'\class="hl-string">" for cn in change_numbers])})"]
                cdpos_data = query_sap_table(conn, class="hl-string">'CDPOS', [class="hl-string">'CHANGENR', class="hl-string">'TABNAME', class="hl-string">'TABKEY', class="hl-string">'FNAME', class="hl-string">'VALUE_NEW', class="hl-string">'VALUE_OLD'], cdpos_options)

            class=class="hl-string">"hl-comment"># Helper to create a base event dictionary
            def create_event(activity, timestamp_str, user=vbak_data[class="hl-string">'ERNAM']):
                return {
                    class="hl-string">'Vbeln': vbeln,
                    class="hl-string">'ActivityName': activity,
                    class="hl-string">'EventTime': timestamp_str,
                    class="hl-string">'Ernam': user,
                    class="hl-string">'Auart': vbak_data[class="hl-string">'AUART'],
                    class="hl-string">'Vkorg': vbak_data[class="hl-string">'VKORG'],
                    class="hl-string">'Kunnr': vbak_data[class="hl-string">'KUNNR'],
                    class="hl-string">'Matnr': class="hl-string">",".join(set(item[class="hl-string">'MATNR'] for item in vbap_data if class="hl-string">'MATNR' in item)),
                    class="hl-string">'Netwr': sum(float(item[class="hl-string">'NETWR']) for item in vbap_data if item.get(class="hl-string">'NETWR') and item[class="hl-string">'NETWR'].strip()),
                    class="hl-string">'Vdatu': vbak_data[class="hl-string">'VDATU']
                }

            class=class="hl-string">"hl-comment"># --- Activity: Sales Order Created ---
            created_ts = fclass="hl-string">"{vbak_data['ERDAT']} {vbak_data['ERZET']}"
            event_log.append(create_event(class="hl-string">'Sales Order Created', datetime.strptime(created_ts, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')))

            class=class="hl-string">"hl-comment"># --- Activities from Change Logs (CDHDR/CDPOS) ---
            change_log_map = {c[class="hl-string">'CHANGENR']: c for c in cdhdr_data}
            for change in cdpos_data:
                change_header = change_log_map.get(change[class="hl-string">'CHANGENR'])
                if not change_header: continue
                
                ts_str = fclass="hl-string">"{change_header['UDATE']} {change_header['UTIME']}"
                event_ts = datetime.strptime(ts_str, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')

                class=class="hl-string">"hl-comment"># Sales Order Block Set/Removed
                if change[class="hl-string">'FNAME'] in [class="hl-string">'FAKSK', class="hl-string">'LIFSK']:
                    if change[class="hl-string">'VALUE_NEW'].strip():
                        event_log.append(create_event(class="hl-string">'Sales Order Block Set', event_ts))
                    else:
                        event_log.append(create_event(class="hl-string">'Sales Order Block Removed', event_ts))
                class=class="hl-string">"hl-comment"># Credit Check Performed (status change)
                if change[class="hl-string">'TABNAME'] == class="hl-string">'VBUK' and change[class="hl-string">'FNAME'] == class="hl-string">'CMGST' and change[class="hl-string">'VALUE_NEW'].strip() in [class="hl-string">'B', class="hl-string">'C', class="hl-string">'D']:
                     event_log.append(create_event(class="hl-string">'Credit Check Performed', event_ts))
                class=class="hl-string">"hl-comment"># Sales Order Changed (e.g., quantity)
                if change[class="hl-string">'FNAME'] == class="hl-string">'KWMENG':
                    event_log.append(create_event(class="hl-string">'Sales Order Changed', event_ts))
                class=class="hl-string">"hl-comment"># Sales Order Item Rejected
                if change[class="hl-string">'FNAME'] == class="hl-string">'ABGRU' and change[class="hl-string">'VALUE_NEW'].strip():
                    event_log.append(create_event(class="hl-string">'Sales Order Item Rejected', event_ts))
                class=class="hl-string">"hl-comment"># Order Closed
                if change[class="hl-string">'TABNAME'] == class="hl-string">'VBUK' and change[class="hl-string">'FNAME'] == class="hl-string">'GBSTK' and change[class="hl-string">'VALUE_NEW'].strip() == class="hl-string">'C':
                    event_log.append(create_event(class="hl-string">'Order Closed', event_ts))

            class=class="hl-string">"hl-comment"># --- Activity: Sales Order Confirmed ---
            vbep_data = query_sap_table(conn, class="hl-string">'VBEP', [class="hl-string">'EDATU', class="hl-string">'EZEIT'], [fclass="hl-string">"VBELN = '{vbeln}' AND BMENG > 0"])
            if vbep_data:
                confirmed_item = vbep_data[0] class=class="hl-string">"hl-comment"># Take the first confirmed schedule line
                ts_str = fclass="hl-string">"{confirmed_item['EDATU']} {confirmed_item['EZEIT']}"
                event_ts = datetime.strptime(ts_str, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
                event_log.append(create_event(class="hl-string">'Sales Order Confirmed', event_ts))

            class=class="hl-string">"hl-comment"># --- Activities from Document Flow (VBFA) ---
            delivery_docs = [d for d in doc_flow if d[class="hl-string">'VBTYP_N'] == class="hl-string">'J']
            invoice_docs = [d for d in doc_flow if d[class="hl-string">'VBTYP_N'] == class="hl-string">'M']

            if delivery_docs:
                delivery_vbeln = delivery_docs[0][class="hl-string">'VBELN']
                class=class="hl-string">"hl-comment"># Activity: Delivery Created
                likp_data = query_sap_table(conn, class="hl-string">'LIKP', [class="hl-string">'ERDAT', class="hl-string">'ERZET'], [fclass="hl-string">"VBELN = '{delivery_vbeln}'"])
                if likp_data:
                    ts_str = fclass="hl-string">"{likp_data[0]['ERDAT']} {likp_data[0]['ERZET']}"
                    event_ts = datetime.strptime(ts_str, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
                    event_log.append(create_event(class="hl-string">'Delivery Created', event_ts))

                class=class="hl-string">"hl-comment"># Activity: Goods Picked (inferred from picking status on delivery change log)
                del_cdhdr = query_sap_table(conn, class="hl-string">'CDHDR', [class="hl-string">'CHANGENR', class="hl-string">'UDATE', class="hl-string">'UTIME'], [fclass="hl-string">"OBJECTCLAS = 'LIEFERUNG' AND OBJECTID = '{delivery_vbeln}'"])
                if del_cdhdr:
                    del_cnrs = [c[class="hl-string">'CHANGENR'] for c in del_cdhdr]
                    del_cdpos = query_sap_table(conn, class="hl-string">'CDPOS', [class="hl-string">'CHANGENR', class="hl-string">'FNAME', class="hl-string">'VALUE_NEW'], [fclass="hl-string">"OBJECTCLAS = 'LIEFERUNG' AND OBJECTID = '{delivery_vbeln}' AND FNAME = 'KOSTA' AND VALUE_NEW = 'C' AND CHANGENR IN ({','.join([f\"class="hl-string">'{cn}'\class="hl-string">" for cn in del_cnrs])})"])
                    if del_cdpos:
                        change_header = [c for c in del_cdhdr if c[class="hl-string">'CHANGENR'] == del_cdpos[0][class="hl-string">'CHANGENR']][0]
                        ts_str = fclass="hl-string">"{change_header['UDATE']} {change_header['UTIME']}"
                        event_ts = datetime.strptime(ts_str, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
                        event_log.append(create_event(class="hl-string">'Goods Picked', event_ts))

                class=class="hl-string">"hl-comment"># Activity: Goods Issue Posted
                gi_doc = [d for d in doc_flow if d[class="hl-string">'VBTYP_N'] == class="hl-string">'R' and d[class="hl-string">'VBELN'] == delivery_vbeln]
                if gi_doc:
                    ts_str = fclass="hl-string">"{gi_doc[0]['ERDAT']} {gi_doc[0]['ERZET']}"
                    event_ts = datetime.strptime(ts_str, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
                    event_log.append(create_event(class="hl-string">'Goods Issue Posted', event_ts))

            if invoice_docs:
                invoice_vbeln = invoice_docs[0][class="hl-string">'VBELN']
                class=class="hl-string">"hl-comment"># Activity: Invoice Created
                vbrk_data = query_sap_table(conn, class="hl-string">'VBRK', [class="hl-string">'ERDAT', class="hl-string">'ERZET'], [fclass="hl-string">"VBELN = '{invoice_vbeln}'"])
                if vbrk_data:
                    ts_str = fclass="hl-string">"{vbrk_data[0]['ERDAT']} {vbrk_data[0]['ERZET']}"
                    event_ts = datetime.strptime(ts_str, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
                    event_log.append(create_event(class="hl-string">'Invoice Created', event_ts))

                    class=class="hl-string">"hl-comment"># Activity: Accounting Document Created
                    bkpf_data = query_sap_table(conn, class="hl-string">'BKPF', [class="hl-string">'BELNR', class="hl-string">'CPUDT', class="hl-string">'CPUTM'], [fclass="hl-string">"AWKEY LIKE '{invoice_vbeln}%' AND AWTYP = 'VBRK'"])
                    if bkpf_data:
                        ac_doc_belnr = bkpf_data[0][class="hl-string">'BELNR']
                        ts_str = fclass="hl-string">"{bkpf_data[0]['CPUDT']} {bkpf_data[0]['CPUTM']}"
                        event_ts = datetime.strptime(ts_str, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
                        event_log.append(create_event(class="hl-string">'Accounting Document Created', event_ts))

                        class=class="hl-string">"hl-comment"># Activity: Payment Received
                        bsad_data = query_sap_table(conn, class="hl-string">'BSAD', [class="hl-string">'AUGDT'], [fclass="hl-string">"BELNR = '{ac_doc_belnr}' AND KUNNR = '{vbak_data['KUNNR']}'"])
                        if bsad_data:
                            event_ts = datetime.strptime(bsad_data[0][class="hl-string">'AUGDT'], class="hl-string">'%Y%m%d').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
                            event_log.append(create_event(class="hl-string">'Payment Received', event_ts))

                class=class="hl-string">"hl-comment"># Activity: Invoice Sent to Customer
                nast_data = query_sap_table(conn, class="hl-string">'NAST', [class="hl-string">'DATVR', class="hl-string">'UHRVR'], [fclass="hl-string">"OBJKY = '{invoice_vbeln}' AND VSTAT = '1' AND KSCHL LIKE '[your_output_type]'"])
                if nast_data and nast_data[0][class="hl-string">'DATVR'] != class="hl-string">'00000000':
                    ts_str = fclass="hl-string">"{nast_data[0]['DATVR']} {nast_data[0]['UHRVR']}"
                    event_ts = datetime.strptime(ts_str, class="hl-string">'%Y%m%d %H%M%S').strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
                    event_log.append(create_event(class="hl-string">'Invoice Sent to Customer', event_ts))

        conn.close()
        print(class="hl-string">"Connection closed.")

        class=class="hl-string">"hl-comment"># --- 4. Create and save the event log ---
        if event_log:
            print(class="hl-string">"Creating DataFrame and saving to CSV...")
            df = pd.DataFrame(event_log)
            df[class="hl-string">'EventTime'] = pd.to_datetime(df[class="hl-string">'EventTime'])
            df = df.sort_values(by=[class="hl-string">'Vbeln', class="hl-string">'EventTime'])
            df.to_csv(class="hl-string">'sales_order_event_log.csv', index=False)
            print(class="hl-string">"Extraction complete. File 'sales_order_event_log.csv' created.")
        else:
            print(class="hl-string">"No events were generated.")

    except (LogonError, ABAPApplicationError) as e:
        print(fclass="hl-string">"An SAP error occurred: {e}")

if __name__ == class="hl-string">"__main__":
    main()

Steps

Scope and Design: Define the precise scope of the extraction. Finalize the list of sales organizations, document types, and the date range for the data pull. Document the specific logic required for each activity, especially for inferred events based on status changes or change logs.
Program Creation: In the SAP GUI, navigate to the ABAP Editor using transaction code SE38. Enter a name for your custom program in the Z-namespace (e.g., Z_PM_O2C_EXTRACTOR) and click 'Create'. Provide a descriptive title, set the Type to 'Executable Program', and save it to a package.
Define Selection Screen: In the program, define a selection screen using PARAMETERS and SELECT-OPTIONS statements. This allows users to specify the date range for sales order creation, sales organizations, and sales document types to make the extraction flexible and reusable.
Data Declarations: Define the internal tables and data structures needed. Create a final structure for the event log that includes all required and recommended attributes (Vbeln, ActivityName, EventTime, Ernam, etc.). Also, declare internal tables for the main SAP tables you will read from, such as VBAK, VBAP, CDHDR, CDPOS, LIKP, VBRK, and BKPF.
Select Base Data: Write the initial SELECT statement to retrieve the primary sales order headers (VBAK) and items (VBAP) based on the user's input on the selection screen. This forms the core dataset of sales orders to be analyzed.
Extract Activities Sequentially: For each of the 15 required activities, write a specific ABAP logic block. For explicit events like 'Sales Order Created', select directly from the base tables. For inferred events like 'Sales Order Block Set', select from change log tables (CDHDR, CDPOS), joining back to your base data. Append the results of each block to the final event log internal table.
Transform Data: During the extraction logic for each activity, ensure data is correctly formatted. Concatenate date and time fields (e.g., ERDAT and ERZET) into a single EventTime timestamp field. Map technical codes to human-readable activity names (e.g., 'Sales Order Created').
Implement File Export: After all activity data has been collected in the final internal table, use the OPEN DATASET, LOOP AT ... TRANSFER, and CLOSE DATASET statements. This writes the contents of the internal table to a flat file (e.g., a comma-separated values file) on the SAP application server directory, which can be viewed via transaction AL11.
Execution and Monitoring: Execute the program. For large data volumes, schedule it as a background job using transaction SM36. Monitor the job's progress and check for completion or errors using transaction SM37.
Retrieve and Finalize: Once the program finishes, use transaction CG3Y to download the generated file from the application server to your local machine. Verify the file contents, headers, and encoding before providing it for upload into the process mining tool.

Configuration

Date Range: Define a SELECT-OPTIONS for the sales order creation date (VBAK-ERDAT). A range of 3-6 months is typically recommended for an initial analysis to ensure a manageable data volume while capturing enough process variations.
Organizational Filters: It is critical to include SELECT-OPTIONS for Sales Organization (VBAK-VKORG) and Sales Document Type (VBAK-AUART). This allows you to focus the extraction on specific business units or process variants (e.g., standard orders vs. returns) and is essential for performance.
Program Execution: For any significant amount of data, the program must be run in the background. Foreground execution will likely result in a timeout. Schedule the program via transaction SM36.
Change Log Reading: The logic for reading change documents (CDHDR, CDPOS) can be performance-intensive. Ensure the selection on these tables is as restrictive as possible, using the object class 'VERKBELEG' and the specific sales order numbers gathered in the initial step.
Authorizations: The user creating the program requires a developer key and ABAP development authorizations (S_DEVELOP). The user executing the program needs authorization to run reports (S_PROGRAM), access the specified application server directory (S_DATASET), and read all underlying SAP tables (VBAK, LIPS, VBRK, BKPF, CDPOS, etc.).

a Sample Query abap

REPORT Z_PM_O2C_EXTRACTOR.

" ====================================================================
" 1. SELECTION SCREEN
" ====================================================================
SELECT-OPTIONS: s_erdat FOR vbak-erdat OBLIGATORY, " Creation Date
                  s_vkorg FOR vbak-vkorg, " Sales Organization
                  s_auart FOR vbak-auart. " Sales Document Type

PARAMETERS: p_file TYPE string DEFAULT '/usr/sap/trans/tmp/o2c_extract.csv'.

" ====================================================================
" 2. DATA DECLARATIONS
" ====================================================================
TYPES: BEGIN OF ty_event_log,
         vbeln TYPE vbeln_va, " Sales Order
         activityname TYPE char50,
         eventtime TYPE string,
         ernam TYPE ernam,
         auart TYPE auart,
         vkorg TYPE vkorg,
         kunnr TYPE kunnr,
         matnr TYPE matnr,
         netwr TYPE netwr_ak,
         vdatu TYPE vdatu,
       END OF ty_event_log.

DATA: lt_event_log TYPE TABLE OF ty_event_log,
      ls_event_log LIKE LINE OF lt_event_log.

DATA: lt_vbak TYPE TABLE OF vbak,
      lt_vbap TYPE TABLE OF vbap.

" ====================================================================
" 3. MAIN PROGRAM LOGIC
" ====================================================================
START-OF-SELECTION.

  " --- Get Base Sales Orders ---
  SELECT * FROM vbak INTO TABLE lt_vbak
    WHERE erdat IN s_erdat
    AND vkorg IN s_vkorg
    AND auart IN s_auart.

  IF lt_vbak IS NOT INITIAL.
    SELECT * FROM vbap INTO TABLE lt_vbap
      FOR ALL ENTRIES IN lt_vbak
      WHERE vbeln = lt_vbak-vbeln.
  END IF.

  " --- Loop through base data to extract events ---
  LOOP AT lt_vbak ASSIGNING FIELD-SYMBOL(<fs_vbak>).
    DATA(lv_vbeln) = <fs_vbak>-vbeln.

    " --- 1. Sales Order Created ---
    ls_event_log-vbeln        = lv_vbeln.
    ls_event_log-activityname = 'Sales Order Created'.
    CONCATENATE <fs_vbak>-erdat <fs_vbak>-erzet INTO ls_event_log-eventtime.
    ls_event_log-ernam        = <fs_vbak>-ernam.
    ls_event_log-auart        = <fs_vbak>-auart.
    ls_event_log-vkorg        = <fs_vbak>-vkorg.
    ls_event_log-kunnr        = <fs_vbak>-kunnr.
    ls_event_log-netwr        = <fs_vbak>-netwr.
    ls_event_log-vdatu        = <fs_vbak>-vdatu.
    CLEAR ls_event_log-matnr.
    APPEND ls_event_log TO lt_event_log.

    " --- Extract other events using SELECTs inside the loop ---
    " NOTE: In a real-world scenario, you would optimize by selecting data
    " in bulk before the loop. This simplified example uses selects inside
    " the loop for clarity on a per-activity basis.

    " --- 2. Credit Check Performed (Example using CDHDR/CDPOS on Status) ---
    SELECT h~udate, h~utime, h~username
      FROM cdhdr AS h INNER JOIN cdpos AS p ON h~changenr = p~changenr
      INTO TABLE @DATA(lt_credit)
      WHERE h~objectclas = 'VERKBELEG'
      AND h~objectid = @lv_vbeln
      AND p~tabname = 'VBUK'
      AND p~fname = 'CMGST'
      AND p~value_new <> p~value_old.
    LOOP AT lt_credit INTO DATA(ls_credit).
      ls_event_log-activityname = 'Credit Check Performed'.
      CONCATENATE ls_credit-udate ls_credit-utime INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ls_credit-username.
      APPEND ls_event_log TO lt_event_log.
    ENDLOOP.

    " --- 3. & 4. Sales Order Block Set / Removed (Example for Delivery Block) ---
    SELECT h~udate, h~utime, h~username, p~value_new, p~value_old
      FROM cdhdr AS h INNER JOIN cdpos AS p ON h~changenr = p~changenr
      INTO TABLE @DATA(lt_block)
      WHERE h~objectclas = 'VERKBELEG'
      AND h~objectid = @lv_vbeln
      AND p~tabname = 'VBAK'
      AND p~fname = 'LIFSK'.
    LOOP AT lt_block INTO DATA(ls_block).
      IF ls_block-value_new IS NOT INITIAL AND ls_block-value_old IS INITIAL.
        ls_event_log-activityname = 'Sales Order Block Set'.
      ELSEIF ls_block-value_new IS INITIAL AND ls_block-value_old IS NOT INITIAL.
        ls_event_log-activityname = 'Sales Order Block Removed'.
      ELSE.
        CONTINUE.
      ENDIF.
      CONCATENATE ls_block-udate ls_block-utime INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ls_block-username.
      APPEND ls_event_log TO lt_event_log.
    ENDLOOP.

    " --- 5. Sales Order Changed (Example for Item Quantity Change) ---
    SELECT h~udate, h~utime, h~username
      FROM cdhdr AS h INNER JOIN cdpos AS p ON h~changenr = p~changenr
      INTO TABLE @DATA(lt_change)
      WHERE h~objectclas = 'VERKBELEG'
      AND h~objectid = @lv_vbeln
      AND p~tabname = 'VBAP'
      AND p~fname = 'KWMENG'.
    LOOP AT lt_change INTO DATA(ls_change).
      ls_event_log-activityname = 'Sales Order Changed'.
      CONCATENATE ls_change-udate ls_change-utime INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ls_change-username.
      APPEND ls_event_log TO lt_event_log.
    ENDLOOP.

    " --- 6. Sales Order Confirmed (Based on Schedule Line Creation) ---
    SELECT erdat, erzet, ernam FROM vbep INTO TABLE @DATA(lt_conf)
      WHERE vbeln = @lv_vbeln AND bmeng > 0.
    LOOP AT lt_conf INTO DATA(ls_conf).
      ls_event_log-activityname = 'Sales Order Confirmed'.
      CONCATENATE ls_conf-erdat ls_conf-erzet INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ls_conf-ernam.
      APPEND ls_event_log TO lt_event_log.
    ENDLOOP.

    " --- 7. Delivery Created ---
    SELECT DISTINCT b~erdat, b~erzet, b~ernam
      FROM lips AS a INNER JOIN likp AS b ON a~vbeln = b~vbeln
      INTO TABLE @DATA(lt_deliv)
      WHERE a~vgbel = @lv_vbeln.
    LOOP AT lt_deliv INTO DATA(ls_deliv).
      ls_event_log-activityname = 'Delivery Created'.
      CONCATENATE ls_deliv-erdat ls_deliv-erzet INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ls_deliv-ernam.
      APPEND ls_event_log TO lt_event_log.
    ENDLOOP.

    " --- 8. & 9. Goods Picked & Goods Issue Posted ---
    SELECT a~vbeln, b~wadat_ist, b~wazei_ist, b~ernam
      FROM lips AS a INNER JOIN likp AS b ON a~vbeln = b~vbeln
      INTO TABLE @DATA(lt_gi)
      WHERE a~vgbel = @lv_vbeln.
    LOOP AT lt_gi INTO DATA(ls_gi).
      " Check change logs for Picking status on LIPS-KOSTA going to 'C'
      " ... (logic similar to blocks) ... Append 'Goods Picked' event
      IF ls_gi-wadat_ist IS NOT INITIAL.
        ls_event_log-activityname = 'Goods Issue Posted'.
        CONCATENATE ls_gi-wadat_ist ls_gi-wazei_ist INTO ls_event_log-eventtime.
        ls_event_log-ernam        = ls_gi-ernam.
        APPEND ls_event_log TO lt_event_log.
      ENDIF.
    ENDLOOP.

    " --- 10. Invoice Created ---
    SELECT DISTINCT b~erdat, b~erzet, b~ernam, b~belnr
      FROM vbrp AS a INNER JOIN vbrk AS b ON a~vbeln = b~vbeln
      INTO TABLE @DATA(lt_inv)
      WHERE a~aubel = @lv_vbeln.
    LOOP AT lt_inv INTO DATA(ls_inv).
      ls_event_log-activityname = 'Invoice Created'.
      CONCATENATE ls_inv-erdat ls_inv-erzet INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ls_inv-ernam.
      APPEND ls_event_log TO lt_event_log.

      " --- 11. Accounting Document Created ---
      SELECT cpudt, cputm, usnam FROM bkpf INTO @DATA(ls_bkpf)
        WHERE awkey = @ls_inv-belnr AND awsys = @sy-sysid.
      IF sy-subrc = 0.
        ls_event_log-activityname = 'Accounting Document Created'.
        CONCATENATE ls_bkpf-cpudt ls_bkpf-cputm INTO ls_event_log-eventtime.
        ls_event_log-ernam        = ls_bkpf-usnam.
        APPEND ls_event_log TO lt_event_log.

        " --- 13. Payment Received ---
        SELECT augdt FROM bsad INTO @DATA(lv_augdt)
          WHERE belnr = @ls_inv-belnr AND bukrs = @<fs_vbak>-bukrs.
        IF sy-subrc = 0 AND lv_augdt IS NOT INITIAL.
          ls_event_log-activityname = 'Payment Received'.
          CONCATENATE lv_augdt '000000' INTO ls_event_log-eventtime.
          ls_event_log-ernam        = ''. " Clearing user often not relevant
          APPEND ls_event_log TO lt_event_log.
        ENDIF.
      ENDIF.
    ENDLOOP.

    " --- 12. Invoice Sent to Customer (from NAST) ---
    SELECT erdat, erzet FROM nast INTO TABLE @DATA(lt_nast)
      WHERE kappl = 'V3' AND objky = @lv_vbeln AND vstat = '1'.
    LOOP AT lt_nast INTO DATA(ls_nast).
      ls_event_log-activityname = 'Invoice Sent to Customer'.
      CONCATENATE ls_nast-erdat ls_nast-erzet INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ''.
      APPEND ls_event_log TO lt_event_log.
    ENDLOOP.

    " --- 14. Sales Order Item Rejected ---
    SELECT h~udate, h~utime, h~username
      FROM cdhdr AS h INNER JOIN cdpos AS p ON h~changenr = p~changenr
      INTO TABLE @DATA(lt_reject)
      WHERE h~objectclas = 'VERKBELEG'
      AND h~objectid = @lv_vbeln
      AND p~tabname = 'VBAP'
      AND p~fname = 'ABGRU'
      AND p~value_new IS NOT INITIAL.
    LOOP AT lt_reject INTO DATA(ls_reject).
      ls_event_log-activityname = 'Sales Order Item Rejected'.
      CONCATENATE ls_reject-udate ls_reject-utime INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ls_reject-username.
      APPEND ls_event_log TO lt_event_log.
    ENDLOOP.

    " --- 15. Order Closed ---
    SELECT h~udate, h~utime, h~username
      FROM cdhdr AS h INNER JOIN cdpos AS p ON h~changenr = p~changenr
      INTO TABLE @DATA(lt_closed)
      WHERE h~objectclas = 'VERKBELEG'
      AND h~objectid = @lv_vbeln
      AND p~tabname = 'VBUK'
      AND p~fname = 'GBSTK'
      AND p~value_new = 'C'.
    LOOP AT lt_closed INTO DATA(ls_closed).
      ls_event_log-activityname = 'Order Closed'.
      CONCATENATE ls_closed-udate ls_closed-utime INTO ls_event_log-eventtime.
      ls_event_log-ernam        = ls_closed-username.
      APPEND ls_event_log TO lt_event_log.
    ENDLOOP.

  ENDLOOP.

  " --- Write to file ---
  OPEN DATASET p_file FOR OUTPUT IN TEXT MODE ENCODING UTF-8.
  IF sy-subrc = 0.
    " Header Row
    DATA(lv_header) = 'SalesOrder,ActivityName,EventTime,UserName,DocumentType,SalesOrg,Customer,Material,NetAmount,RequestedDeliveryDate'.
    TRANSFER lv_header TO p_file.

    LOOP AT lt_event_log INTO ls_event_log.
      " Create CSV line
      CONCATENATE ls_event_log-vbeln
                  ls_event_log-activityname
                  ls_event_log-eventtime
                  ls_event_log-ernam
                  ls_event_log-auart
                  ls_event_log-vkorg
                  ls_event_log-kunnr
                  ls_event_log-matnr
                  ls_event_log-netwr
                  ls_event_log-vdatu
        INTO DATA(lv_line) SEPARATED BY ','.
      TRANSFER lv_line TO p_file.
    ENDLOOP.
    CLOSE DATASET p_file.
  ENDIF.

Data Template: Order to Cash - Sales Order Processing

Your Order to Cash - Sales Order Processing Data Template

Order to Cash - Sales Order Processing Attributes

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