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Your Warehouse Management Data Template

Oracle WMS Cloud

Warehouse Management Attributes (22) Warehouse Management Activities (16) Extraction Guides (2)

Your Warehouse Management Data Template

This template provides a clear guide for collecting the necessary data to analyze your warehouse management processes. It outlines the essential attributes and activities you'll need to track, along with practical guidance on how to extract this information from your source system.

Recommended attributes to collect
Key activities to track for your process
Guidance for data extraction

New to event logs? Learn how to create a process mining event log.

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Warehouse Management Attributes

These are the recommended data fields to include in your event log for comprehensive warehouse management analysis.

5 Required 7 Recommended 10 Optional

	Name	Description
	Activity Name ActivityName	The name of a specific business event or task that occurred within the warehouse management process, such as 'Goods Picked' or 'Shipment Dispatched'.
Description The Activity Name describes a single step or milestone in the warehouse order lifecycle. These activities form the sequential nodes in the process map, allowing for the visualization and analysis of the process flow. Each activity is timestamped, providing the basis for performance measurement and bottleneck analysis. In process mining, this attribute is fundamental for constructing the process model. It is used to analyze activity frequencies, paths, and durations between different steps. Understanding the sequence and occurrence of activities like 'Quality Inspection Performed' or 'Picking Task Created' is key to optimizing resource allocation and improving cycle times. Why it matters This attribute defines the steps in the process map, making it possible to visualize, analyze, and optimize the warehouse workflow. Where to get This information is typically derived from event logs, task status tables, or transaction records in Oracle WMS Cloud that capture process milestones. Examples Goods ArrivedPicking Task CreatedGoods PackedShipment Dispatched
	Event Start Time EventStartTime	The timestamp indicating when a specific warehouse activity or event began.
Description The Event Start Time is the precise date and time that marks the beginning of an activity. It is the primary temporal attribute used in process mining to order events chronologically and to calculate durations and cycle times. This timestamp is essential for building an accurate representation of the process flow as it happened in reality. Analysis based on Event Start Time is critical for performance monitoring. It allows for the calculation of key metrics such as the time between activities, the duration of an entire case, and adherence to service level agreements. Dashboards visualizing cycle times, like 'Goods Receipt to Putaway Cycle Time', rely entirely on this attribute to identify delays. Why it matters This timestamp is crucial for ordering events correctly and calculating all time-based performance metrics, such as cycle times and bottlenecks. Where to get This is typically the creation or start timestamp field associated with a task or event record in Oracle WMS Cloud transaction tables. Examples 2023-10-26T09:00:00Z2023-10-26T10:30:15Z2023-10-27T11:05:00Z
	Warehouse Order WarehouseOrder	The unique identifier for a warehouse order, which serves as the primary case for tracking all related logistical activities from start to finish.
Description The Warehouse Order is the central identifier that groups all events and activities related to a single logistical task within the warehouse, such as an inbound receipt or an outbound shipment. It acts as the case identifier for process mining, allowing for the end-to-end analysis of the entire warehouse process lifecycle for that specific order. Analyzing processes by Warehouse Order enables the visualization of the complete journey, from creation to completion or cancellation. It helps in identifying common process paths, bottlenecks, deviations, and rework loops that affect the efficiency of warehouse operations. This view is critical for understanding the overall performance and adherence to standard procedures for different types of orders. Why it matters This is the essential Case ID that connects all related warehouse activities, enabling a complete, end-to-end process view for each logistical order. Where to get This identifier is typically found in the header level of warehouse order tables within Oracle WMS Cloud, such as the Orders or Tasks modules. Examples WO-0054321ORD-9876543SHIP-2024-1001
	Last Data Update LastDataUpdate	The timestamp indicating when the data for this event was last extracted or refreshed from the source system.
Description Last Data Update specifies the date and time the data was pulled from Oracle WMS Cloud. This metadata is vital for understanding the freshness of the analysis and ensuring that decisions are based on current information. For process mining dashboards, this timestamp informs the user about the recency of the displayed data. It helps manage expectations about whether the analysis reflects real-time operations or a historical snapshot, which is critical for operational monitoring. Why it matters Indicates the freshness of the data, which is essential for users to understand how current the process analysis is. Where to get This timestamp is generated and added during the data extraction, transformation, and loading (ETL) process. Examples 2023-11-01T02:00:00Z2023-11-02T02:00:00Z
	Source System SourceSystem	The system from which the warehouse management data was extracted.
Description This attribute identifies the origin of the data, which in this case is Oracle WMS Cloud. While it may seem static, it is crucial for data governance, traceability, and in scenarios where data from multiple systems is being merged for a broader analysis. In a process mining context, it helps stakeholders trust the data and understand its context. If different warehouses use different systems, this field becomes essential for segmenting and comparing process performance across them. Why it matters It provides crucial context for data origin and governance, ensuring traceability and enabling multi-system analysis. Where to get This is typically a static value added during the data transformation process to label the dataset's origin. Examples Oracle WMS CloudOracle Fusion WMS
	Actual Quantity ActualQuantity	The actual quantity of items counted or handled during an activity, such as goods receipt or picking.
Description The Actual Quantity is the physical count of units processed during a warehouse task. This is often recorded during goods receipt, putaway, picking, or cycle counting activities. It represents the ground truth of the inventory movement. This attribute is critical for the 'Inventory Quantity Discrepancy' dashboard. By comparing the Actual Quantity to the Planned Quantity from the source document, like a purchase order or a shipment order, discrepancies can be immediately identified. Analyzing these differences helps pinpoint sources of inventory inaccuracy, such as supplier errors, receiving mistakes, or picking errors, which is vital for maintaining accurate stock levels. Why it matters It is essential for identifying inventory discrepancies by comparing it to the planned quantity, which helps improve stock accuracy. Where to get Consult Oracle WMS Cloud documentation. This is typically a field in the transaction details or task line item tables. Examples 10098500
	Event End Time EventEndTime	The timestamp indicating when a specific warehouse activity or event was completed.
Description The Event End Time marks the precise date and time that an activity concluded. When available, it provides a more accurate measure of an activity's duration compared to inferring it from the start time of the next activity. This is particularly useful for tasks that have a measurable processing time, like 'Packing' or 'Quality Inspection'. In analysis, having both a start and end time allows for precise calculation of activity processing times. This helps differentiate between the time spent actively working on a task (processing time) and the time spent waiting for the next step to begin (wait time). This distinction is key for resource utilization and efficiency analysis. Why it matters Enables the precise calculation of individual activity durations, which helps differentiate active processing time from idle wait time. Where to get This is typically the completion or end timestamp field in a task or event record in Oracle WMS Cloud. Examples 2023-10-26T09:15:00Z2023-10-26T11:00:45Z2023-10-27T11:20:00Z
	Priority Level PriorityLevel	A classification of the warehouse order's urgency, such as 'High', 'Normal', or 'Low'.
Description The Priority Level is a business-defined attribute that indicates the urgency of a warehouse order. High-priority orders, such as express shipments or stock replenishments for critical shortages, often need to follow a faster process path and require immediate attention from resources. This attribute is essential for the 'Priority Order Fulfillment Performance' dashboard. By filtering and comparing processes based on Priority Level, managers can assess whether high-priority orders are truly being expedited and meeting their stricter SLAs. It helps ensure that resources are allocated effectively to meet the most critical business needs. Why it matters It allows for analysis of whether urgent orders are processed faster than standard ones, ensuring critical SLAs are met. Where to get Consult Oracle WMS Cloud documentation. This is typically a field in the order header data. Examples HighNormalLow
	Requested Completion Date RequestedCompletionDate	The target date by which the warehouse order is expected to be completed or shipped.
Description The Requested Completion Date represents the service level agreement (SLA) or customer-expected deadline for the order. This date is the benchmark against which the actual completion time of the order is measured to determine if it was on-time, early, or late. This attribute is fundamental for performance monitoring dashboards like 'Warehouse Order SLA Adherence' and calculating KPIs such as 'On-Time Shipment Compliance'. By comparing the actual dispatch timestamp with this requested date, businesses can measure their service level performance, identify the root causes of delays, and prioritize orders that are at risk of missing their deadlines. Why it matters This is the primary attribute for measuring on-time performance and SLA compliance, which directly impacts customer satisfaction. Where to get Consult Oracle WMS Cloud documentation. This is typically part of the order header data, often derived from a sales order or purchase order. Examples 2023-10-28T17:00:00Z2023-11-05T23:59:59Z2023-11-15T12:00:00Z
	SLA State SLAState	A calculated status indicating whether the warehouse order was completed on-time, late, or is at risk, based on the Requested Completion Date.
Description SLA State is a derived attribute that provides an immediate classification of an order's performance against its deadline. It is calculated by comparing the timestamp of the completion activity (e.g., 'Shipment Dispatched') with the 'RequestedCompletionDate'. The state can be categorized as 'On Time', 'Late', or potentially 'At Risk' for open orders nearing their deadline. This attribute is purpose-built for the 'Warehouse Order SLA Adherence' dashboard. It simplifies complex date comparisons into an easy-to-understand status, allowing for quick visual assessment of performance. Analysts can use this to filter for all late orders and perform a root cause analysis on why they missed their service level agreement. Why it matters Provides a simple, at-a-glance status of SLA compliance, making it easy to track and analyze on-time performance. Where to get This is calculated by comparing the final activity's timestamp against the RequestedCompletionDate. Examples On TimeLateAt Risk
	User/Operator ID UserOperatorId	The identifier for the user, operator, or employee who performed the warehouse activity.
Description This attribute identifies the person responsible for executing a specific task, such as picking, packing, or putting away goods. It is a critical dimension for analyzing human resource performance, workload distribution, and adherence to standard operating procedures. Analyzing the process by User/Operator ID helps in identifying top-performing employees, those who may require additional training, and imbalances in workload across the team. It is essential for the 'Resource Utilization by Activity' dashboard to understand how different users contribute to overall process efficiency and where bottlenecks might be related to specific user actions. Why it matters This attribute is key for analyzing workforce performance, identifying training needs, and ensuring equitable workload distribution. Where to get This is usually found in transaction or task tables, often linked to the user logged into the system or handheld device when the action was performed. Examples JSMITHBJOHNSONUSER123
	Warehouse Order Type WarehouseOrderType	Categorizes the warehouse order, for example, as an inbound receipt, outbound shipment, or internal transfer.
Description The Warehouse Order Type provides essential context about the purpose of the order. Common types include customer shipments, purchase order receipts, stock transfers between facilities, or returns. This categorization is fundamental for segmenting process analysis and comparing performance across different workflows. In process mining, filtering by order type allows for the creation of distinct process maps for inbound and outbound flows, which often have very different steps and performance targets. For instance, the KPIs for an outbound shipment are focused on speed and customer delivery, while those for an inbound receipt are focused on inventory availability and accuracy. This attribute is crucial for the 'Picking & Packing Throughput' dashboard to compare different fulfillment processes. Why it matters It allows for the segmentation of analysis into distinct processes like inbound, outbound, or internal, which have different goals and workflows. Where to get Consult Oracle WMS Cloud documentation. This is typically available in the warehouse order header data. Examples Outbound ShipmentInbound ReceiptInternal TransferCustomer Return
	Carrier Carrier	The shipping carrier or transportation provider assigned to handle the outbound shipment.
Description The Carrier attribute identifies the logistics partner responsible for transporting the goods from the warehouse to the final destination. This could be a commercial carrier like FedEx or UPS, a freight company, or an internal fleet. This information is used in the 'Shipment Dispatch Cycle Time' dashboard to analyze and compare the performance of different carriers. By segmenting the time from 'Staged For Shipment' to 'Shipment Dispatched' by carrier, the business can identify which partners are more efficient, which ones cause delays, and use this data for contract negotiations and carrier selection. Why it matters Enables performance comparison between different shipping carriers, helping to optimize outbound logistics and reduce dispatch delays. Where to get Consult Oracle WMS Cloud documentation. This is typically stored in the shipment or load information related to the warehouse order. Examples FedExUPSDHLXPO Logistics
	Equipment Used EquipmentUsed	The identifier for the equipment, such as a forklift or handheld scanner, used to perform a warehouse activity.
Description This attribute specifies the physical asset or equipment utilized during a warehouse task. Tracking equipment usage provides another layer for resource analysis, complementing the view of human operator performance. It can help in understanding equipment utilization rates, identifying maintenance needs, and optimizing the allocation of machinery. For the 'Resource Utilization by Activity' dashboard, analyzing data by Equipment Used is crucial. It can reveal if certain types of equipment are bottlenecks or if there are opportunities to improve task allocation based on equipment availability and efficiency. For example, it might show that a specific forklift model is consistently slower for putaway tasks, prompting an investigation. Why it matters This enables analysis of equipment utilization and efficiency, helping to identify asset-related bottlenecks and optimize resource allocation. Where to get Consult Oracle WMS Cloud documentation. This may be logged in task execution records, especially if operators log in to specific equipment. Examples FORKLIFT-05SCANNER-A12CART-27
	Is Rework IsRework	A boolean flag that indicates if an activity is a repetition of a previous step within the same case, signaling rework or a process loop.
Description Is Rework is a calculated flag that identifies when a process deviates from a linear flow and repeats an activity. For example, if a 'Goods Picked' activity is followed by another 'Goods Picked' activity for the same order, the second instance would be flagged as rework. This often indicates a problem, such as a picking error that needed correction. This attribute is essential for the 'Process Deviation & Rework Analysis' dashboard and the 'Warehouse Rework Rate' KPI. By flagging these events, the analysis can quantify the frequency and impact of rework. Identifying the activities most prone to rework helps pinpoint process weaknesses, quality issues, or training gaps that lead to inefficiency and increased operational costs. Why it matters This flag directly identifies process inefficiencies and loops, helping to quantify the cost and frequency of rework. Where to get This is calculated within the process mining tool by detecting repeated sequences of activities for the same CaseId. Examples truefalse
	Location Identifier LocationIdentifier	The specific physical location within the warehouse where an activity occurred, such as a bin, dock door, or staging area.
Description The Location Identifier specifies the exact place within the warehouse associated with an event. This could be a receiving dock for 'Goods Arrived', a storage bin for 'Goods Put Away', a packing station for 'Goods Packed', or a staging lane for 'Staged For Shipment'. This attribute adds a spatial dimension to the process analysis. It can help identify bottlenecks tied to specific physical areas of the warehouse. For example, analysis might reveal that a particular aisle is consistently slow for picking, or that a specific dock door is a chokepoint for receiving. This insight can inform decisions about warehouse layout, resource allocation, and process design. Why it matters Adds a physical dimension to the analysis, helping to identify bottlenecks related to specific warehouse zones, aisles, or bins. Where to get Consult Oracle WMS Cloud documentation. This information is typically recorded in task-level details. Examples A-01-03-BDOCK-04PACK-STN-02STAGE-LANE-5
	Planned Quantity PlannedQuantity	The expected quantity of items for an activity, based on the source document like a purchase or sales order.
Description The Planned Quantity is the expected number of units for a given task, as specified by the originating document. For an inbound receipt, this would be the quantity on the purchase order. For an outbound shipment, it would be the quantity on the sales order. This attribute serves as the baseline for comparison against the Actual Quantity. The 'Inventory Data Discrepancy Rate' KPI is calculated based on deviations between planned and actual amounts. Analyzing these variances is crucial for supply chain and inventory management to address issues with suppliers, internal processes, or data entry errors. Why it matters Serves as the baseline to measure inventory accuracy and identify discrepancies during receiving or picking processes. Where to get Consult Oracle WMS Cloud documentation. This is usually found on the order line item associated with the warehouse task. Examples 100100500
	Processing Time ProcessingTime	The duration of time spent actively performing a warehouse activity.
Description Processing Time is a calculated metric that measures the time elapsed between the start and end of an activity. It represents the actual 'touch time' or work duration for a task, as opposed to the waiting time between tasks. It is typically calculated as EventEndTime minus EventStartTime. This metric is fundamental for efficiency analysis and is a key component of the 'Resource Utilization by Activity' dashboard. By isolating the time spent actively working, managers can identify which specific tasks are the most time-consuming and where there are opportunities for process improvement or automation. It helps answer questions like 'How long does it actually take to pack an order?' Why it matters This calculated metric measures the active work duration of a task, helping to pinpoint time-consuming activities and analyze resource efficiency. Where to get This is calculated from EventStartTime and EventEndTime. (ProcessingTime = EventEndTime - EventStartTime). Examples 15 minutes45 seconds1 hour 5 minutes
	Product SKU ProductSKU	The Stock Keeping Unit (SKU) or identifier for the product being handled in the warehouse order.
Description The Product SKU is the unique code that identifies a specific product or item. Warehouse orders often contain one or more products, and this attribute allows for analysis to be segmented by the items being processed. Analyzing the process by Product SKU can reveal how different products affect warehouse efficiency. For example, bulky or fragile items may have longer handling times, while fast-moving products might follow a more optimized process path. This information is valuable for slotting strategies, where products are placed in the warehouse to optimize picking and putaway travel times, and for understanding how product characteristics impact overall throughput. Why it matters Allows for analysis based on product characteristics, which can impact handling times and process flows, informing slotting and storage strategies. Where to get Consult Oracle WMS Cloud documentation. This is found at the order line item or task detail level. Examples SKU-100-RED-LGPROD-54321HW-CMP-001A
	Reason Code ReasonCode	A code or description that explains the reason for a specific event, such as an inventory adjustment, a return, or a deviation.
Description A Reason Code provides context for non-standard events or exceptions within the process. For example, if an 'Inventory Adjusted' activity occurs, the reason code might specify 'Damaged Goods', 'Cycle Count Adjustment', or 'Expired Stock'. This is crucial for root cause analysis of process deviations. In process mining, reason codes are invaluable for understanding why exceptions happen. Analyzing the frequency and impact of different reason codes can help identify systemic issues. For instance, a high frequency of 'Damaged Goods' adjustments might trigger a review of handling procedures, while frequent 'Picking Error' codes would point to a need for better training or system checks for pickers. Why it matters Provides critical context for exceptions and deviations, enabling root cause analysis of issues like inventory adjustments or delays. Where to get Consult Oracle WMS Cloud documentation. These codes are typically entered during exception handling transactions. Examples DMG - Damaged in transitQTY_MISMATCH - Supplier ShortageWRONG_ITEM_PICKED
	Shipment ID ShipmentId	The unique identifier for the shipment that groups one or more warehouse orders being transported together.
Description The Shipment ID is a higher-level identifier that can consolidate multiple warehouse orders into a single logistical unit for transportation. For example, several small orders going to the same destination might be grouped into one shipment on the same truck. While the Warehouse Order is the case ID for this analysis, the Shipment ID provides an additional dimension for analyzing outbound logistics. It allows for performance to be assessed at the shipment level, such as the total time to consolidate all orders for a shipment. It can also be used to trace issues that affect an entire shipment rather than just a single order. Why it matters Groups multiple orders into a single transport unit, allowing for analysis of consolidation efficiency and shipment-level performance. Where to get Consult Oracle WMS Cloud documentation. This is typically found in shipment or load management modules. Examples SHP-98765LOAD-A543BOL-123456
	Warehouse Order Status WarehouseOrderStatus	The current or final status of the warehouse order, such as 'Completed' or 'Cancelled'.
Description This attribute indicates the outcome or the final state of a warehouse order. It helps differentiate between orders that were successfully processed and those that were cancelled or are still in progress. This is a key dimension for filtering cases to analyze only completed processes or to investigate the reasons for cancellations. Analyzing cases based on their final status is important for understanding process variations and outcomes. For example, comparing the process flows of 'Completed' versus 'Cancelled' orders can reveal at which stage cancellations typically occur, providing insights into potential issues with inventory, customer requests, or system errors. It's also used to calculate throughput KPIs like 'Daily Warehouse Throughput'. Why it matters It defines the outcome of a case, enabling analysis to focus on successfully completed orders or to investigate exceptions like cancellations. Where to get This is typically the status field on the warehouse order header record in Oracle WMS Cloud. Examples CompletedIn ProgressCancelledOn Hold

Required Recommended Optional

Warehouse Management Activities

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

7 Recommended 9 Optional

	Activity	Description
	Goods Packed	Represents the completion of the packing process for a shipping container or an entire order. The operator confirms that all items are packed, and the container is sealed and labeled for shipment.
Why it matters This milestone marks the end of the value-adding activities inside the warehouse for an order. The time from picking to packing completion is a key indicator of internal fulfillment speed. Where to get This is typically an explicit transaction, such as 'Close Container' or 'Finish Pack'. The completion timestamp is recorded in the packing or outbound order transaction history. Capture Captured from the completion timestamp of the final packing transaction for the order. Event type explicit
	Goods Picked	This activity indicates that an operator has physically retrieved the items from their storage locations and confirmed the pick in the system. The goods are now ready to be moved to the packing or staging area.
Why it matters This is a major milestone in the order fulfillment process. Analyzing picking times helps identify bottlenecks caused by warehouse layout, picking strategies, or operator performance. Where to get This is captured from the completion timestamp of the picking task in the task history or transaction logs. The confirmation scan by the operator finalizes the transaction. Capture Based on the completion timestamp of the picking task transaction. Event type explicit
	Goods Put Away	This activity signifies the successful completion of the putaway process. An operator has physically moved the goods to the storage bin and confirmed the action in the system, making the inventory available for use.
Why it matters This is a key milestone that marks the end of the inbound process. It is critical for calculating the total 'Goods Receipt to Storage Time' KPI and analyzing putaway efficiency. Where to get This is captured when an operator confirms the putaway task, creating a transaction record with a completion timestamp. It is usually found in the task history or inventory transaction logs. Capture Based on the completion timestamp of the putaway task transaction. Event type explicit
	Goods Received	This activity indicates that the goods have been unloaded, scanned, and formally accepted into the warehouse's accountability. It is a transactional event where quantities are confirmed against the inbound delivery document.
Why it matters This is a critical milestone that marks the official receipt of inventory. The time taken to complete this activity directly impacts how quickly stock becomes available for putaway and fulfillment. Where to get This is captured from the receiving transaction logs in Oracle WMS Cloud. Each scan or confirmation of an item receipt generates a transactional record with a timestamp. Capture Based on the completion timestamp of the 'Receive ASN' or similar receiving transactions. Event type explicit
	Inbound Delivery Created	This activity marks the creation of an Advanced Shipment Notification (ASN) or inbound delivery record in Oracle WMS Cloud. It signifies the start of the inbound process, representing the formal notification that goods are expected to arrive at the warehouse.
Why it matters This is the primary start event for the inbound warehouse process. Analyzing the time from this point to actual goods receipt helps measure supplier reliability and planning accuracy. Where to get This event is typically captured from the transaction history of Inbound Shipment or ASN objects. It corresponds to the creation timestamp of the document. Capture Captured from the creation event of the Inbound Shipment or ASN record. Event type explicit
	Shipment Dispatched	This activity marks the final step where the loaded truck is dispatched and departs from the warehouse. This transaction financially and physically closes the outbound order in the WMS.
Why it matters This is the final outbound milestone and a critical KPI data point for on-time shipment compliance. It signifies the handover of goods to the carrier and the end of warehouse responsibility. Where to get This is a key explicit transaction in Oracle WMS Cloud, often called 'Ship Confirm' or 'Dispatch Load'. It is recorded against the Outbound Load or Shipment record with a precise timestamp. Capture Captured from the 'Ship Confirm' or 'Dispatch Load' transaction timestamp. Event type explicit
	Warehouse Order Completed	This represents the final closure of the warehouse order itself, which may occur at the time of shipment dispatch or slightly after, once all system updates are finalized. This is the successful end event for the process.
Why it matters This activity defines the end of the end-to-end warehouse process lifecycle. It is essential for calculating the total cycle time and throughput of the entire warehouse operation. Where to get This event is typically inferred from the final status change of the warehouse order object to 'Completed' or 'Closed'. The timestamp of this final status update is used. Capture Inferred from the status change of the warehouse order to its terminal success state. Event type inferred
	Goods Arrived	Represents the physical arrival of the truck or carrier at the warehouse dock and the official check-in process. This is often recorded before the unloading and detailed receiving of individual items begins.
Why it matters This milestone helps differentiate between carrier transit time and the warehouse's internal processing time. It is crucial for analyzing dock-door utilization and potential bottlenecks at the receiving area. Where to get This is often captured as a status update on the Inbound Shipment or ASN record, triggered by a dock agent scanning the delivery paperwork or manually updating the system. Capture Logged as a status change event, for example 'Arrived at Check-In', on the Inbound Shipment. Event type explicit
	Inventory Adjusted	Represents a manual or systematic adjustment to the quantity of an item in a specific location. This can occur due to cycle counting, damage, or correction of receiving discrepancies.
Why it matters This activity is crucial for identifying process failures that lead to inventory inaccuracies. Analyzing the frequency and magnitude of adjustments helps pinpoint issues in receiving, picking, or storage. Where to get This is captured from specific inventory adjustment transaction logs within Oracle WMS Cloud. These logs detail the item, location, quantity change, reason code, and timestamp. Capture Captured directly from inventory adjustment transaction records. Event type explicit
	Loading Started	This event represents the start of the physical loading process, where packed goods are moved from the staging area onto the carrier's truck. This is often initiated by a 'Start Load' transaction.
Why it matters This activity provides visibility into the efficiency of the loading process itself. It helps separate staging wait time from the active time spent loading a truck. Where to get This is typically an explicit transaction linked to an Outbound Load record in Oracle WMS Cloud. The user performs a 'Start Load' action which is timestamped. Capture Captured from the 'Start Load' transaction associated with a specific outbound carrier load. Event type explicit
	Packing Started	This activity signifies that picked goods have arrived at a packing station and an operator has started the packing process. This is often an explicit scan that associates the items with a packing container.
Why it matters Tracking this activity helps isolate the packing sub-process from picking and staging. It allows for detailed analysis of packing station efficiency and throughput. Where to get This may be an explicit transaction, or it could be inferred from the creation of a packing container (LPN) and the first item being scanned into it. It is found in packing or shipping transaction logs. Capture Captured from the 'Start Pack' transaction or the timestamp of the first item packed into a container. Event type explicit
	Picking Task Created	This event occurs when the system generates a picking task for an operator to retrieve items from storage to fulfill an outbound order. It marks the beginning of the order fulfillment cycle within the warehouse.
Why it matters This is the trigger for the outbound picking process. The time from this event to picking completion is a key measure of order fulfillment efficiency and resource responsiveness. Where to get This event is recorded in the warehouse task management tables. The creation timestamp of the picking task record is used as the activity time. Capture Captured from the creation timestamp of the system-generated picking task. Event type explicit
	Putaway Task Created	This event marks the system's generation of a task for a warehouse operator to move received goods from the receiving dock to a designated storage location. This is the starting point for the putaway sub-process.
Why it matters This activity initiates the putaway cycle. Analyzing the time between task creation and actual putaway completion helps assess system efficiency and operator response time. Where to get This is typically an explicit event recorded in the warehouse task or transaction tables. The creation timestamp of the putaway task record serves as the event time. Capture Captured from the creation timestamp of the system-generated putaway task. Event type explicit
	Quality Inspection Performed	Represents the completion of a quality control check on the received goods. This may be a standard step for certain materials or suppliers, or it could be triggered on an ad-hoc basis.
Why it matters Tracking the duration and frequency of quality inspections is essential for identifying delays in the inbound process. It helps measure the time goods are held in a quality assurance status before being available. Where to get This event is likely inferred from status changes on the inventory record, moving from a 'QA Hold' status to an 'Available' or 'Putaway' status. There may also be explicit transaction logs from a quality module. Capture Inferred from inventory status changes or completion of a QA transaction linked to the received goods. Event type inferred
	Staged For Shipment	This activity indicates that the packed containers have been moved from the packing station to a designated shipment staging area. The order is now complete and awaiting loading onto a carrier.
Why it matters This marks the transition from processing to the final dispatch stage. The time goods spend in staging can highlight delays in carrier arrival or dock scheduling. Where to get This is usually captured via a location move transaction, where the packed container's location is updated to a staging lane. The timestamp of this move transaction marks the event. Capture Captured from the inventory move transaction that relocates the packed LPN to a staging location. Event type explicit
	Warehouse Order Cancelled	Represents the cancellation of a warehouse order before its completion. This is an alternative, unsuccessful end state for the process.
Why it matters Tracking cancellations is important for understanding demand changes, data entry errors, or other issues causing orders to be aborted. It helps identify sources of process waste. Where to get This event is inferred from the warehouse order's status changing to 'Cancelled' or a similar terminal state. The timestamp of this status update is used. Capture Inferred from the status change of the warehouse order to a 'Cancelled' state. Event type inferred

Recommended Optional

Extraction Guides

How to get your data from Oracle WMS Cloud

Steps

Navigate to Oracle Transactional Business Intelligence (OTBI). Log into your Oracle Cloud Applications environment and use the navigator menu to go to Tools, then select Reports and Analytics.
Click the "Create" button in the toolbar and select "Analysis". This will open the analysis editor, where you will select a data source.
In the "Select Subject Area" dialog, choose the "Warehouse Operations - Real Time" subject area. This subject area contains the necessary data objects for inbound, inventory, and outbound transactions.
After selecting the subject area, you will be taken to the Criteria tab. Instead of dragging and dropping columns, navigate to the "Advanced" tab to directly input the logical SQL query.
Copy the complete logical SQL provided in the Query section of this document and paste it into the "SQL Issued" text area. This query is structured with UNION ALL clauses to combine data from different transactional tables into a single event log format.
Modify the placeholder values in the query. Specifically, update the @{v_start_date} and @{v_end_date} variables with the desired date range for the extraction, for example, 'YYYY-MM-DD'.
Switch to the "Results" tab to execute the query and preview the data. This helps confirm that the query is valid and returns the expected columns and rows.
Save the analysis by clicking the save icon. Provide a descriptive name and save it in a shared or personal folder.
To schedule a recurring export, navigate back to the catalog, find your saved analysis, and click "More", then select "Schedule".
In the schedule configuration, define the frequency and timing for the report to run. In the "Output" tab, specify the export format as CSV. This is the recommended format for ProcessMind.
Configure the delivery method, such as saving to a content server or sending via email, to retrieve the generated CSV file.
Once the scheduled job runs and you receive the CSV file, verify that the column headers match the required attributes for your ProcessMind project. No further data transformation should be necessary.

Configuration

Subject Area: The primary data source for this extraction is the "Warehouse Operations - Real Time" subject area. Ensure your user role has the necessary permissions to access this subject area.
Date Range: The query is parameterized with start and end dates. For an initial analysis, it is recommended to extract 3 to 6 months of data. For production, schedule daily or weekly delta extractions.
Key Filters: The provided query filters data based on the transaction creation date. You can add more filters directly in the WHERE clause of each SELECT statement to narrow the scope, for example, by filtering on "Warehouse Details"."Warehouse Code" to limit data to a specific facility.
Performance: Extracting large volumes of data directly from real-time subject areas can impact system performance. Always schedule large extractions to run during off-peak business hours to minimize the impact on operational users.
Prerequisites: The user running the extraction must have a role with the necessary BI privileges, such as "BI Administrator" or "BI Author", to create, edit, and schedule analyses in the OTBI environment.

a Sample Query sql

SET VARIABLE PREFERRED_CURRENCY='USD', LOGLEVEL=0, v_start_date = '2023-01-01', v_end_date = '2024-01-01';

SELECT
    CAST("Inbound Shipment Details"."Shipment Number" AS CHAR) AS "WarehouseOrder",
    'Inbound Delivery Created' AS "ActivityName",
    "Inbound Shipment Details"."Creation Date" AS "EventStartTime",
    "Inbound Shipment Details"."Creation Date" AS "EventEndTime",
    NULL AS "UserOperatorId",
    "Inbound Shipment Header"."Shipment Type" AS "WarehouseOrderType",
    "Inbound Shipment Header"."Expected Delivery Date" AS "RequestedCompletionDate",
    NULL AS "ActualQuantity",
    "Inbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    CASE WHEN "Inbound Shipment Header"."Actual Delivery Date" > "Inbound Shipment Header"."Expected Delivery Date" THEN 'Late' ELSE 'On-Time' END AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Inbound Shipment Details"."Creation Date" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Inbound Shipment Details"."Shipment Number" AS CHAR) AS "WarehouseOrder",
    'Goods Arrived' AS "ActivityName",
    "Appointment Details"."Check In Time" AS "EventStartTime",
    "Appointment Details"."Check In Time" AS "EventEndTime",
    "Appointment Details"."Checked In By User" AS "UserOperatorId",
    "Inbound Shipment Header"."Shipment Type" AS "WarehouseOrderType",
    "Inbound Shipment Header"."Expected Delivery Date" AS "RequestedCompletionDate",
    NULL AS "ActualQuantity",
    "Inbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    CASE WHEN "Inbound Shipment Header"."Actual Delivery Date" > "Inbound Shipment Header"."Expected Delivery Date" THEN 'Late' ELSE 'On-Time' END AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Appointment Details"."Check In Time" IS NOT NULL AND "Appointment Details"."Check In Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Receiving Transaction Details"."Shipment Number" AS CHAR) AS "WarehouseOrder",
    'Goods Received' AS "ActivityName",
    "Receiving Transaction Details"."Transaction Creation Time" AS "EventStartTime",
    "Receiving Transaction Details"."Transaction Creation Time" AS "EventEndTime",
    "Receiving Transaction Details"."Received By User" AS "UserOperatorId",
    NULL AS "WarehouseOrderType",
    NULL AS "RequestedCompletionDate",
    "Receiving Transaction Details"."Received Quantity" AS "ActualQuantity",
    NULL AS "PriorityLevel",
    NULL AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Receiving Transaction Details"."Transaction Creation Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Inventory Quality Inspection Results"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Quality Inspection Performed' AS "ActivityName",
    "Inventory Quality Inspection Results"."Inspection Completion Time" AS "EventStartTime",
    "Inventory Quality Inspection Results"."Inspection Completion Time" AS "EventEndTime",
    "Inventory Quality Inspection Results"."Inspected By User" AS "UserOperatorId",
    NULL AS "WarehouseOrderType",
    NULL AS "RequestedCompletionDate",
    "Inventory Quality Inspection Results"."Inspected Quantity" AS "ActualQuantity",
    NULL AS "PriorityLevel",
    NULL AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Inventory Quality Inspection Results"."Inspection Completion Time" IS NOT NULL AND "Inventory Quality Inspection Results"."Inspection Completion Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST(CASE WHEN "Task Details"."Task Type" = 'Putaway' THEN "Task Details"."Reference Number" ELSE NULL END AS CHAR) AS "WarehouseOrder",
    'Putaway Task Created' AS "ActivityName",
    "Task Details"."Task Creation Time" AS "EventStartTime",
    "Task Details"."Task Completion Time" AS "EventEndTime",
    "Task Details"."Created By User" AS "UserOperatorId",
    "Task Details"."Task Type" AS "WarehouseOrderType",
    NULL AS "RequestedCompletionDate",
    "Task Details"."Task Quantity" AS "ActualQuantity",
    CAST("Task Details"."Task Priority" AS CHAR) AS "PriorityLevel",
    NULL AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Task Details"."Task Type" = 'Putaway' AND "Task Details"."Task Creation Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST(CASE WHEN "Task Details"."Task Type" = 'Putaway' THEN "Task Details"."Reference Number" ELSE NULL END AS CHAR) AS "WarehouseOrder",
    'Goods Put Away' AS "ActivityName",
    "Task Details"."Task Completion Time" AS "EventStartTime",
    "Task Details"."Task Completion Time" AS "EventEndTime",
    "Task Details"."Completed By User" AS "UserOperatorId",
    "Task Details"."Task Type" AS "WarehouseOrderType",
    NULL AS "RequestedCompletionDate",
    "Task Details"."Task Quantity" AS "ActualQuantity",
    CAST("Task Details"."Task Priority" AS CHAR) AS "PriorityLevel",
    NULL AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Task Details"."Task Type" = 'Putaway' AND "Task Details"."Task Status" = 'Completed' AND "Task Details"."Task Completion Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Inventory Transaction Details"."Reference Document Number" AS CHAR) AS "WarehouseOrder",
    'Inventory Adjusted' AS "ActivityName",
    "Inventory Transaction Details"."Transaction Creation Time" AS "EventStartTime",
    "Inventory Transaction Details"."Transaction Creation Time" AS "EventEndTime",
    "Inventory Transaction Details"."Created By User" AS "UserOperatorId",
    "Inventory Transaction Details"."Transaction Type" AS "WarehouseOrderType",
    NULL AS "RequestedCompletionDate",
    "Inventory Transaction Details"."Transaction Quantity" AS "ActualQuantity",
    NULL AS "PriorityLevel",
    NULL AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Inventory Transaction Details"."Transaction Type" IN ('Cycle Count Adjustment', 'Manual Adjustment') AND "Inventory Transaction Details"."Transaction Creation Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Task Details"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Picking Task Created' AS "ActivityName",
    "Task Details"."Task Creation Time" AS "EventStartTime",
    "Task Details"."Task Completion Time" AS "EventEndTime",
    "Task Details"."Created By User" AS "UserOperatorId",
    "Task Details"."Task Type" AS "WarehouseOrderType",
    NULL AS "RequestedCompletionDate",
    "Task Details"."Task Quantity" AS "ActualQuantity",
    CAST("Task Details"."Task Priority" AS CHAR) AS "PriorityLevel",
    NULL AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Task Details"."Task Type" = 'Picking' AND "Task Details"."Task Creation Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Task Details"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Goods Picked' AS "ActivityName",
    "Task Details"."Task Completion Time" AS "EventStartTime",
    "Task Details"."Task Completion Time" AS "EventEndTime",
    "Task Details"."Completed By User" AS "UserOperatorId",
    "Task Details"."Task Type" AS "WarehouseOrderType",
    NULL AS "RequestedCompletionDate",
    "Task Details"."Task Quantity" AS "ActualQuantity",
    CAST("Task Details"."Task Priority" AS CHAR) AS "PriorityLevel",
    NULL AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Task Details"."Task Type" = 'Picking' AND "Task Details"."Task Status" = 'Completed' AND "Task Details"."Task Completion Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Outbound Shipment Details"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Packing Started' AS "ActivityName",
    "Packing Details"."Packing Start Time" AS "EventStartTime",
    "Packing Details"."Packing End Time" AS "EventEndTime",
    "Packing Details"."Packed By User" AS "UserOperatorId",
    "Outbound Shipment Header"."Order Type" AS "WarehouseOrderType",
    "Outbound Shipment Header"."Requested Ship Date" AS "RequestedCompletionDate",
    "Packing Details"."Packed Quantity" AS "ActualQuantity",
    "Outbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    CASE WHEN "Outbound Shipment Header"."Actual Ship Date" > "Outbound Shipment Header"."Requested Ship Date" THEN 'Late' ELSE 'On-Time' END AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Packing Details"."Packing Start Time" IS NOT NULL AND "Packing Details"."Packing Start Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Outbound Shipment Details"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Goods Packed' AS "ActivityName",
    "Packing Details"."Packing End Time" AS "EventStartTime",
    "Packing Details"."Packing End Time" AS "EventEndTime",
    "Packing Details"."Packed By User" AS "UserOperatorId",
    "Outbound Shipment Header"."Order Type" AS "WarehouseOrderType",
    "Outbound Shipment Header"."Requested Ship Date" AS "RequestedCompletionDate",
    "Packing Details"."Packed Quantity" AS "ActualQuantity",
    "Outbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    CASE WHEN "Outbound Shipment Header"."Actual Ship Date" > "Outbound Shipment Header"."Requested Ship Date" THEN 'Late' ELSE 'On-Time' END AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Packing Details"."Packing End Time" IS NOT NULL AND "Packing Details"."Packing End Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Outbound Shipment Details"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Staged For Shipment' AS "ActivityName",
    "Outbound Load Details"."Staging Time" AS "EventStartTime",
    "Outbound Load Details"."Staging Time" AS "EventEndTime",
    NULL AS "UserOperatorId",
    "Outbound Shipment Header"."Order Type" AS "WarehouseOrderType",
    "Outbound Shipment Header"."Requested Ship Date" AS "RequestedCompletionDate",
    "Outbound Shipment Details"."Shipped Quantity" AS "ActualQuantity",
    "Outbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    CASE WHEN "Outbound Shipment Header"."Actual Ship Date" > "Outbound Shipment Header"."Requested Ship Date" THEN 'Late' ELSE 'On-Time' END AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Outbound Load Details"."Staging Time" IS NOT NULL AND "Outbound Load Details"."Staging Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Outbound Shipment Details"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Loading Started' AS "ActivityName",
    "Outbound Load Details"."Loading Start Time" AS "EventStartTime",
    "Outbound Load Details"."Loading End Time" AS "EventEndTime",
    "Outbound Load Details"."Loaded By User" AS "UserOperatorId",
    "Outbound Shipment Header"."Order Type" AS "WarehouseOrderType",
    "Outbound Shipment Header"."Requested Ship Date" AS "RequestedCompletionDate",
    "Outbound Shipment Details"."Shipped Quantity" AS "ActualQuantity",
    "Outbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    CASE WHEN "Outbound Shipment Header"."Actual Ship Date" > "Outbound Shipment Header"."Requested Ship Date" THEN 'Late' ELSE 'On-Time' END AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Outbound Load Details"."Loading Start Time" IS NOT NULL AND "Outbound Load Details"."Loading Start Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Outbound Shipment Header"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Shipment Dispatched' AS "ActivityName",
    "Outbound Shipment Header"."Actual Ship Date" AS "EventStartTime",
    "Outbound Shipment Header"."Actual Ship Date" AS "EventEndTime",
    NULL AS "UserOperatorId",
    "Outbound Shipment Header"."Order Type" AS "WarehouseOrderType",
    "Outbound Shipment Header"."Requested Ship Date" AS "RequestedCompletionDate",
    "Outbound Shipment Details"."Shipped Quantity" AS "ActualQuantity",
    "Outbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    CASE WHEN "Outbound Shipment Header"."Actual Ship Date" > "Outbound Shipment Header"."Requested Ship Date" THEN 'Late' ELSE 'On-Time' END AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Outbound Shipment Header"."Status" = 'Shipped' AND "Outbound Shipment Header"."Actual Ship Date" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Outbound Shipment Header"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Warehouse Order Completed' AS "ActivityName",
    "Outbound Shipment Header"."Last Update Time" AS "EventStartTime",
    "Outbound Shipment Header"."Last Update Time" AS "EventEndTime",
    "Outbound Shipment Header"."Last Updated By" AS "UserOperatorId",
    "Outbound Shipment Header"."Order Type" AS "WarehouseOrderType",
    "Outbound Shipment Header"."Requested Ship Date" AS "RequestedCompletionDate",
    NULL AS "ActualQuantity",
    "Outbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    CASE WHEN "Outbound Shipment Header"."Actual Ship Date" > "Outbound Shipment Header"."Requested Ship Date" THEN 'Late' ELSE 'On-Time' END AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Outbound Shipment Header"."Status" = 'Delivered' AND "Outbound Shipment Header"."Last Update Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

UNION ALL

SELECT
    CAST("Outbound Shipment Header"."Order Number" AS CHAR) AS "WarehouseOrder",
    'Warehouse Order Cancelled' AS "ActivityName",
    "Outbound Shipment Header"."Last Update Time" AS "EventStartTime",
    "Outbound Shipment Header"."Last Update Time" AS "EventEndTime",
    "Outbound Shipment Header"."Last Updated By" AS "UserOperatorId",
    "Outbound Shipment Header"."Order Type" AS "WarehouseOrderType",
    "Outbound Shipment Header"."Requested Ship Date" AS "RequestedCompletionDate",
    NULL AS "ActualQuantity",
    "Outbound Shipment Header"."Shipment Priority" AS "PriorityLevel",
    NULL AS "SLAState",
    'Oracle WMS Cloud' AS "SourceSystem",
    CURRENT_TIMESTAMP AS "LastDataUpdate"
FROM "Warehouse Operations - Real Time"
WHERE "Outbound Shipment Header"."Status" = 'Cancelled' AND "Outbound Shipment Header"."Last Update Time" BETWEEN TIMESTAMP '@{v_start_date}' AND TIMESTAMP '@{v_end_date}'

Steps

Prepare Python Environment: Ensure you have Python 3.6 or newer installed. Install the necessary libraries using pip: pip install requests pandas.
Gather Oracle WMS Cloud Credentials: Obtain the API Base URL, a dedicated API user account username, password, and the relevant Facility ID for the warehouse you want to extract data from.
Configure the Python Script: Open the provided Python script. Locate the configuration section at the top and replace the placeholder values for BASE_URL, FACILITY_ID, USERNAME, and PASSWORD with your actual credentials. Also, set the START_DATE and END_DATE to define the desired extraction period.
Understand API Endpoints: The script queries several key Oracle WMS Cloud REST API endpoints. The primary source of event data is the inventory_history endpoint, which is filtered by different transaction types (tran_type) to identify specific activities like receiving, picking, and packing.
Execute the Script: Run the script from your command line using python your_script_name.py. The script will authenticate, then sequentially query the APIs for data related to each of the 16 required activities within the specified date range.
Handle Pagination: The script includes a helper function to automatically handle API pagination. It repeatedly calls each endpoint, incrementing the offset parameter until all relevant records for the date range have been retrieved.
Map and Transform Data: For each record retrieved from the API, the script maps the JSON fields to the standardized event log columns (WarehouseOrder, ActivityName, EventStartTime, etc.). It assigns the correct ActivityName based on the source endpoint and transaction type.
Consolidate Event Data: All extracted events are appended to a single list. After all API queries are complete, this list is converted into a pandas DataFrame, providing a structured, tabular view of the entire process.
Timestamp and System Data: The script enriches the data by adding the SourceSystem (hardcoded as 'Oracle WMS Cloud') and LastDataUpdate (the timestamp when the script was run) to each event record.
Export the Event Log: The final pandas DataFrame is sorted by the warehouse order ID and event start time to ensure proper sequencing. It is then saved as a CSV file named oracle_wms_event_log.csv in the same directory where the script is run. This file is ready for upload to ProcessMind.

Configuration

API Credentials: A valid Oracle WMS Cloud user with API access is required. This includes the username and password.
Base URL and Facility ID: You must provide the specific base URL for your Oracle WMS Cloud instance (e.g., https://{your_instance_id}.wms.ocs.oraclecloud.com) and the target facility_id.
Date Range: The script requires a START_DATE and END_DATE in 'YYYY-MM-DD' format. For initial analysis, a range of 3 to 6 months is recommended to balance data volume and insight. Be aware that very large date ranges can lead to long script execution times.
Pagination Limit: The LIMIT parameter in the script is set to 500 records per API request. This is generally a safe value to avoid timeouts. You can adjust this based on your system's performance, but values over 1000 are not recommended.
API Permissions: The API user must have at least read permissions for the following entities: inbound_shipment, inventory_history, task, outbound_load, and order. Consult your Oracle WMS administrator to ensure proper roles are assigned.

a Sample Query python

import requests
import pandas as pd
from datetime import datetime
import base64
import time

class=class="hl-string">"hl-comment"># --- Configuration ---
class=class="hl-string">"hl-comment"># Replace with your Oracle WMS Cloud instance details
BASE_URL = class="hl-string">'https://{your_instance_id}.wms.ocs.oraclecloud.com/wms/api/v11'
FACILITY_ID = class="hl-string">'[Your Facility ID]'
USERNAME = class="hl-string">'[Your API Username]'
PASSWORD = class="hl-string">'[Your API Password]'

class=class="hl-string">"hl-comment"># Set the date range for extraction
START_DATE = class="hl-string">'YYYY-MM-DD' class=class="hl-string">"hl-comment"># e.g., class="hl-string">'2023-01-01'
END_DATE = class="hl-string">'YYYY-MM-DD'   class=class="hl-string">"hl-comment"># e.g., class="hl-string">'2023-06-30'

class=class="hl-string">"hl-comment"># --- End Configuration ---

LIMIT = 500
SOURCE_SYSTEM = class="hl-string">'Oracle WMS Cloud'
LAST_DATA_UPDATE = datetime.utcnow().isoformat() + class="hl-string">'Z'

class=class="hl-string">"hl-comment"># Function to perform paginated GET requests
def get_paginated_data(endpoint, params={}):
    all_items = []
    offset = 0
    auth_header = class="hl-string">'Basic ' + base64.b64encode(fclass="hl-string">'{USERNAME}:{PASSWORD}'.encode(class="hl-string">'utf-8')).decode(class="hl-string">'utf-8')
    headers = {
        class="hl-string">'Authorization': auth_header,
        class="hl-string">'Accept': class="hl-string">'application/json'
    }
    
    while True:
        paginated_params = params.copy()
        paginated_params[class="hl-string">'offset'] = offset
        paginated_params[class="hl-string">'limit'] = LIMIT
        
        try:
            response = requests.get(fclass="hl-string">'{BASE_URL}/facility/{FACILITY_ID}/{endpoint}', headers=headers, params=paginated_params)
            response.raise_for_status()
            data = response.json()
            items = data.get(class="hl-string">'items', [])
            if not items:
                break
            all_items.extend(items)
            offset += len(items)
            print(fclass="hl-string">'Fetched {len(all_items)} records from {endpoint}...')
            class=class="hl-string">"hl-comment"># Respect potential rate limits
            time.sleep(0.5)
        except requests.exceptions.RequestException as e:
            print(fclass="hl-string">'Error fetching data from {endpoint}: {e}')
            break
    return all_items

def main():
    events = []
    date_filter = fclass="hl-string">"create_ts > '{START_DATE}T00:00:00Z' and create_ts < '{END_DATE}T23:59:59Z'"

    class=class="hl-string">"hl-comment"># 1. Inbound Delivery Created (from ASN/Inbound Shipments)
    asn_data = get_paginated_data(class="hl-string">'inbound_shipment', {class="hl-string">'q': date_filter})
    for item in asn_data:
        events.append({
            class="hl-string">'WarehouseOrder': item.get(class="hl-string">'shipment_nbr'),
            class="hl-string">'ActivityName': class="hl-string">'Inbound Delivery Created',
            class="hl-string">'EventStartTime': item.get(class="hl-string">'create_ts'),
            class="hl-string">'EventEndTime': None,
            class="hl-string">'UserOperatorId': item.get(class="hl-string">'user_id'),
            class="hl-string">'WarehouseOrderType': class="hl-string">'Inbound',
            class="hl-string">'RequestedCompletionDate': item.get(class="hl-string">'required_ship_date'),
            class="hl-string">'ActualQuantity': None,
            class="hl-string">'PriorityLevel': item.get(class="hl-string">'priority'),
            class="hl-string">'SLAState': None
        })

    class=class="hl-string">"hl-comment"># 2-7, 9-14: Most activities are in Inventory History
    inv_history_filter = fclass="hl-string">"tran_create_ts > '{START_DATE}T00:00:00Z' and tran_create_ts < '{END_DATE}T23:59:59Z'"
    inv_history_data = get_paginated_data(class="hl-string">'inventory_history', {class="hl-string">'q': inv_history_filter})
    
    activity_map = {
        class="hl-string">'ARV': class="hl-string">'Goods Arrived',
        class="hl-string">'REC': class="hl-string">'Goods Received',
        class="hl-string">'QCH': class="hl-string">'Quality Inspection Performed',
        class="hl-string">'MVL': class="hl-string">'Goods Put Away', class=class="hl-string">"hl-comment"># Move to LPN
        class="hl-string">'ADJ': class="hl-string">'Inventory Adjusted',
        class="hl-string">'PCK': class="hl-string">'Goods Picked',
        class="hl-string">'PAK': class="hl-string">'Goods Packed', class=class="hl-string">"hl-comment"># Often part of a packing transaction
        class="hl-string">'LOD': class="hl-string">'Loading Started', class=class="hl-string">"hl-comment"># Often a move to a shipping door location
        class="hl-string">'SHP': class="hl-string">'Shipment Dispatched'
    }

    for item in inv_history_data:
        tran_type = item.get(class="hl-string">'tran_type')
        if tran_type in activity_map:
            class=class="hl-string">"hl-comment"># Use order_nbr for outbound, shipment_nbr for inbound if available
            order_id = item.get(class="hl-string">'order_nbr') or item.get(class="hl-string">'shipment_nbr') or class="hl-string">'[Unknown]'
            events.append({
                class="hl-string">'WarehouseOrder': order_id,
                class="hl-string">'ActivityName': activity_map[tran_type],
                class="hl-string">'EventStartTime': item.get(class="hl-string">'tran_create_ts'),
                class="hl-string">'EventEndTime': None,
                class="hl-string">'UserOperatorId': item.get(class="hl-string">'user_id'),
                class="hl-string">'WarehouseOrderType': class="hl-string">'Inbound' if item.get(class="hl-string">'shipment_nbr') else class="hl-string">'Outbound',
                class="hl-string">'RequestedCompletionDate': None,
                class="hl-string">'ActualQuantity': item.get(class="hl-string">'tran_qty'),
                class="hl-string">'PriorityLevel': None,
                class="hl-string">'SLAState': None
            })

    class=class="hl-string">"hl-comment"># 8, 5: Task Creation Events
    task_filter = fclass="hl-string">"create_ts > '{START_DATE}T00:00:00Z' and create_ts < '{END_DATE}T23:59:59Z'"
    task_data = get_paginated_data(class="hl-string">'task', {class="hl-string">'q': task_filter})
    for item in task_data:
        task_type = item.get(class="hl-string">'task_type')
        activity_name = None
        if task_type in (class="hl-string">'PUT', class="hl-string">'RPL'):
            activity_name = class="hl-string">'Putaway Task Created'
        elif task_type in (class="hl-string">'PCK', class="hl-string">'WAV'):
            activity_name = class="hl-string">'Picking Task Created'
        
        if activity_name:
            order_id = item.get(class="hl-string">'order_nbr') or item.get(class="hl-string">'shipment_nbr') or class="hl-string">'[Unknown]'
            events.append({
                class="hl-string">'WarehouseOrder': order_id,
                class="hl-string">'ActivityName': activity_name,
                class="hl-string">'EventStartTime': item.get(class="hl-string">'create_ts'),
                class="hl-string">'EventEndTime': None,
                class="hl-string">'UserOperatorId': item.get(class="hl-string">'assigned_user_id'),
                class="hl-string">'WarehouseOrderType': class="hl-string">'Inbound' if activity_name == class="hl-string">'Putaway Task Created' else class="hl-string">'Outbound',
                class="hl-string">'RequestedCompletionDate': None,
                class="hl-string">'ActualQuantity': item.get(class="hl-string">'task_qty'),
                class="hl-string">'PriorityLevel': item.get(class="hl-string">'priority'),
                class="hl-string">'SLAState': None
            })
            
    class=class="hl-string">"hl-comment"># Additional specific events if not in inventory history
    class=class="hl-string">"hl-comment"># 10. Packing Started, 12. Staged For Shipment - These can be complex and may require logic based on location moves or container status changes. We use placeholders from Inventory History as a starting point.
    class=class="hl-string">"hl-comment"># For this script, class="hl-string">'PAK' from inventory_history implies both started and completed for simplicity.
    for item in inv_history_data:
        if item.get(class="hl-string">'tran_type') == class="hl-string">'PAK':
             order_id = item.get(class="hl-string">'order_nbr') or class="hl-string">'[Unknown]'
             events.append({
                class="hl-string">'WarehouseOrder': order_id,
                class="hl-string">'ActivityName': class="hl-string">'Packing Started',
                class="hl-string">'EventStartTime': item.get(class="hl-string">'tran_create_ts'), class=class="hl-string">"hl-comment"># Assuming start is same as completion
                class="hl-string">'EventEndTime': item.get(class="hl-string">'tran_create_ts'),
                class="hl-string">'UserOperatorId': item.get(class="hl-string">'user_id'),
                class="hl-string">'WarehouseOrderType': class="hl-string">'Outbound',
                class="hl-string">'RequestedCompletionDate': None,
                class="hl-string">'ActualQuantity': item.get(class="hl-string">'tran_qty'),
                class="hl-string">'PriorityLevel': None,
                class="hl-string">'SLAState': None
            })
        class=class="hl-string">"hl-comment"># Staging is a move to a staging location type
        if item.get(class="hl-string">'tran_type') == class="hl-string">'MVL' and item.get(class="hl-string">'dest_locn_type') == class="hl-string">'STG':
             order_id = item.get(class="hl-string">'order_nbr') or class="hl-string">'[Unknown]'
             events.append({
                class="hl-string">'WarehouseOrder': order_id,
                class="hl-string">'ActivityName': class="hl-string">'Staged For Shipment',
                class="hl-string">'EventStartTime': item.get(class="hl-string">'tran_create_ts'),
                class="hl-string">'EventEndTime': None,
                class="hl-string">'UserOperatorId': item.get(class="hl-string">'user_id'),
                class="hl-string">'WarehouseOrderType': class="hl-string">'Outbound',
                class="hl-string">'RequestedCompletionDate': None,
                class="hl-string">'ActualQuantity': item.get(class="hl-string">'tran_qty'),
                class="hl-string">'PriorityLevel': None,
                class="hl-string">'SLAState': None
            })

    class=class="hl-string">"hl-comment"># 15, 16. Warehouse Order Completed / Cancelled
    order_filter = fclass="hl-string">"mod_ts > '{START_DATE}T00:00:00Z' and mod_ts < '{END_DATE}T23:59:59Z'"
    order_data = get_paginated_data(class="hl-string">'order', {class="hl-string">'q': order_filter})
    for item in order_data:
        status = str(item.get(class="hl-string">'status', class="hl-string">''))
        activity_name = None
        if status == class="hl-string">'90': class=class="hl-string">"hl-comment"># Shipped / Delivered status code
            activity_name = class="hl-string">'Warehouse Order Completed'
        elif status == class="hl-string">'99': class=class="hl-string">"hl-comment"># Cancelled status code
            activity_name = class="hl-string">'Warehouse Order Cancelled'
        
        if activity_name:
            events.append({
                class="hl-string">'WarehouseOrder': item.get(class="hl-string">'order_nbr'),
                class="hl-string">'ActivityName': activity_name,
                class="hl-string">'EventStartTime': item.get(class="hl-string">'mod_ts'),
                class="hl-string">'EventEndTime': item.get(class="hl-string">'mod_ts'),
                class="hl-string">'UserOperatorId': item.get(class="hl-string">'mod_user_id'),
                class="hl-string">'WarehouseOrderType': class="hl-string">'Outbound', class=class="hl-string">"hl-comment"># Assuming order endpoint is for outbound
                class="hl-string">'RequestedCompletionDate': item.get(class="hl-string">'required_ship_date'),
                class="hl-string">'ActualQuantity': item.get(class="hl-string">'shipped_qty'),
                class="hl-string">'PriorityLevel': item.get(class="hl-string">'priority'),
                class="hl-string">'SLAState': None
            })

    class=class="hl-string">"hl-comment"># Final processing
    if not events:
        print(class="hl-string">'No events found for the given criteria.')
        return

    df = pd.DataFrame(events)

    class=class="hl-string">"hl-comment"># Add standard columns
    df[class="hl-string">'SourceSystem'] = SOURCE_SYSTEM
    df[class="hl-string">'LastDataUpdate'] = LAST_DATA_UPDATE

    class=class="hl-string">"hl-comment"># Clean up and order columns
    df = df[[class="hl-string">'WarehouseOrder', class="hl-string">'ActivityName', class="hl-string">'EventStartTime', class="hl-string">'EventEndTime', class="hl-string">'UserOperatorId', class="hl-string">'WarehouseOrderType', class="hl-string">'RequestedCompletionDate', class="hl-string">'ActualQuantity', class="hl-string">'PriorityLevel', class="hl-string">'SLAState', class="hl-string">'SourceSystem', class="hl-string">'LastDataUpdate']]
    df.sort_values(by=[class="hl-string">'WarehouseOrder', class="hl-string">'EventStartTime'], inplace=True)

    class=class="hl-string">"hl-comment"># Save to CSV
    output_filename = class="hl-string">'oracle_wms_event_log.csv'
    df.to_csv(output_filename, index=False, date_format=class="hl-string">'%Y-%m-%dT%H:%M:%S.%fZ')
    print(fclass="hl-string">'Successfully created event log: {output_filename}')

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

Your Warehouse Management Data Template

Your Warehouse Management Data Template

Warehouse Management Attributes

Warehouse Management Activities

Extraction Guides

Oracle Transactional Business Intelligence (OTBI) Export

Steps

Configuration

a Sample Query sql

Python Script Extraction via Oracle WMS REST APIs

Steps

Configuration

a Sample Query python

Ready to Get Started?

Optimize Warehouse Management, Boost Oracle WMS Cloud Efficiency

Your Warehouse Management Data Template

Your Warehouse Management Data Template

Warehouse Management Attributes

Warehouse Management Activities

Extraction Guides

Oracle Transactional Business Intelligence (OTBI) Export

Steps

Configuration

a Sample Query sql

Python Script Extraction via Oracle WMS REST APIs

Steps

Configuration

a Sample Query python

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Ready to Get Started?

Optimize Warehouse Management, Boost Oracle WMS Cloud Efficiency