Your Production Planning Data Template

This attribute records the distinct steps and milestones in the production order lifecycle. Examples include 'Production Order Created', 'Material Availability Checked', 'Production Started', and 'Order Financially Closed'. Each activity represents a specific action or status change documented in the system.

Analyzing the sequence and frequency of these activities is the core of process mining. It helps visualize the process flow, identify deviations from the standard procedure, and pinpoint activities that cause delays or require frequent rework, such as 'Production Plan Adjusted'.

It defines the steps of the process, allowing for the discovery and visualization of the actual production workflow and its variations.

Derived from status changes in tables like JEST and JCDS, transaction codes used (e.g., CO01 for create), or specific confirmation records in AFRU.

The Production Order number is a unique key generated by SAP S/4HANA to manage and track all activities related to the manufacturing of a specific product quantity. It links together all related events, from planning and release to execution and final settlement.

In process mining, this attribute is essential for grouping all related events into a single end-to-end process instance. Analyzing processes by Production Order allows for the measurement of key performance indicators like cycle time, adherence to schedule, and identification of bottlenecks affecting specific production runs.

It is the fundamental attribute that connects all process steps, enabling a complete case-level analysis of the production lifecycle from start to finish.

This is the Production Order number, typically found in SAP tables like AFKO (field AUFNR) and AFPO.

This attribute provides the date and time for every recorded event in the production process. It is the temporal foundation for all time-based process analysis.

The Start Time is crucial for calculating durations between activities, measuring the total cycle time of a production order, and understanding the timing of events. It enables the analysis of bottlenecks, waiting times, and schedule adherence by comparing actual timestamps against planned dates.

It provides the chronological context for all events, making it possible to analyze process performance, durations, and bottlenecks.

This information is typically found in change document tables (CDHDR/CDPOS) for status changes, confirmation tables (AFRU) for execution steps, and header tables (AFKO) for creation dates.

This attribute records the date and time of the most recent data pull. It is a critical piece of metadata that informs users about the freshness of the data they are analyzing.

Knowing the last update time is essential for interpreting the analysis correctly. It helps users understand if they are viewing real-time information or a snapshot from a specific point in time, which affects the relevance of any findings and decisions made based on the data.

It ensures users are aware of the data's timeliness, which is critical for making accurate and relevant business decisions.

This timestamp is generated and added during the data extraction, transformation, and loading (ETL) process.

This attribute identifies the origin of the data, which is essential in environments with multiple integrated systems. For this process, it will typically be the specific SAP S/4HANA instance.

In a broader data analysis context, knowing the source system helps ensure data integrity and allows for proper context when merging data from different sources. It is a fundamental piece of metadata for data governance and traceability.

It provides crucial metadata for data governance, ensuring the origin and context of the process data are clear.

This is typically a static value added during the data extraction process to identify the SAP S/4HANA client and system ID (SID).

The Material Number specifies the item that the production order aims to produce. It links the production process to the master data of the material, including its bill of materials (BOM) and routing information.

Analyzing the process by Material Number helps identify if certain products are more prone to delays, rework, or material shortages. This allows for product-specific process optimization, such as adjusting planning parameters or improving the supply chain for specific components.

It allows for filtering and analysis based on the product being made, revealing product-specific inefficiencies or bottlenecks.

Found in the Production Order item table AFPO (field MATNR).

The Order Status indicates the overall stage of the production order in its lifecycle. It is a summary of the various system and user statuses applied to the order. Common statuses include CRTD (Created), REL (Released), CNF (Confirmed), TECO (Technically Completed), and CLSD (Closed).

Analyzing the current status of orders is useful for understanding the work-in-progress landscape. In process mining, tracking the transitions between these statuses over time is what generates the activity log and allows for a detailed view of the process flow and durations spent in each stage.

It provides a high-level view of an order's lifecycle stage and is fundamental to deriving the sequence of activities for process mining.

Derived from the system status stored in table JEST, linked via the object number in AFKO (field OBJNR).

The Planned End Date is the target date by which all production activities for an order are expected to be finished. This date is determined during the scheduling phase of production planning.

This attribute is essential for measuring schedule adherence. By comparing the Planned End Date with the actual completion timestamp, organizations can calculate the Production Schedule Adherence Rate KPI and identify orders that are late. This analysis is critical for improving planning accuracy and customer satisfaction.

It serves as the baseline for measuring schedule adherence, helping to evaluate the accuracy of planning and the efficiency of execution.

Found in the Production Order header table AFKO (field GLTRP).

The Plant is an organizational unit in SAP representing a production site or facility. Each production order is assigned to a specific plant where the manufacturing activities will take place.

This attribute is critical for comparative analysis across different manufacturing locations. By segmenting the process data by Plant, organizations can benchmark performance, identify site-specific issues or best practices, and understand regional variations in efficiency, capacity, or adherence to standards.

It enables performance comparison between different production sites, helping to identify and share best practices or address location-specific issues.

Found in the Production Order header table AFKO (field DWERK).

A Work Center represents a specific operational unit within a plant where a production step is performed. It can be a single machine, a production line, or a group of employees.

Analyzing process data by Work Center is key to identifying capacity bottlenecks and optimizing resource allocation. It helps answer questions about which work centers are overloaded, which are underutilized, and where delays are most frequently occurring during the production execution phase. This is vital for the Capacity Bottleneck Identification dashboard.

It helps pinpoint specific machines or production lines that are bottlenecks, enabling targeted improvements in capacity and resource utilization.

Found in the operation data of a production order, table AFVC (field ARBPL).

This attribute represents the cumulative quantity of finished or semi-finished goods that have been reported through production confirmations. It tracks the progress of the order toward its completion target.

Comparing the confirmed quantity against the planned quantity helps in monitoring production progress and identifying yield issues or discrepancies. It is a fundamental measure of output and is used in various performance calculations, including scrap rates and efficiency.

It tracks the actual output of the production order, which is essential for monitoring progress, calculating yield, and identifying discrepancies.

Aggregated from confirmation records in AFRU (field LMNGA for yield quantity).

This attribute provides the completion date and time for every recorded event. It complements the Start Time to define the duration of activities.

End Time is crucial for calculating the precise processing time of individual activities, which is a key input for capacity and resource utilization analysis. It helps differentiate between active work time and idle or wait time, leading to more accurate bottleneck identification.

It enables the calculation of precise activity durations, which is essential for analyzing resource efficiency and identifying process bottlenecks.

Found in confirmation tables (AFRU) for execution steps. For other events, it might be the same as the Start Time if the event is instantaneous.

This calculated boolean attribute directly measures schedule adherence by comparing the actual completion date with the planned end date. It provides a clear, binary outcome for each production order's timeliness.

This attribute is the basis for the Production Schedule Adherence Rate KPI. It simplifies analysis by allowing for easy segmentation of on-time versus late orders, helping to identify common characteristics or process paths associated with delays.

It provides a clear and simple measure of schedule adherence for each order, facilitating analysis of the root causes of delays.

Calculated field. Set to true if the timestamp of the 'Order Technically Completed' activity is less than or equal to the 'Planned End Date' attribute.

This boolean attribute is derived to identify production orders that underwent corrective actions or plan changes after production was already underway. This could be triggered by an explicit rework activity or a 'Production Plan Adjusted' event occurring after 'Production Started'.

This flag is crucial for calculating the Production Rework Rate KPI and for the Production Rework and Revisions dashboard. It allows for easy filtering and analysis of problematic cases, helping to uncover the root causes of quality issues or process deviations that lead to costly rework.

It isolates cases with rework, enabling targeted analysis to understand and reduce quality issues, process deviations, and associated costs.

Calculated field. Set to true if a 'Production Plan Adjusted' activity occurs after a 'Production Started' activity within the same case, or if a specific rework order type is used.

This status reflects the result of the material availability check performed for a production order. It can indicate that all materials are available, some are missing, or the check has not been performed. A status of 'shortage' is a key trigger for potential delays.

This attribute is critical for the Material Shortage Impact Analysis dashboard. It helps quantify the delays caused by material unavailability by correlating a shortage status with the time between order release and production start. Improving this metric is key to a smoother production flow.

It directly explains delays between order release and production start, helping to quantify the impact of supply chain issues on manufacturing.

This is a status, often derived from the collective status of material components. It can be found in the system status (JEST) with statuses like 'MSPT' (Material shortage).

The Order Type is a key configuration element in SAP PP that determines how a production order is handled by the system. It controls number ranges, master data selection, costing parameters, and settlement rules. Examples include standard production orders, rework orders, or prototype orders.

Analyzing the process by Order Type allows for comparing the performance and flow of different kinds of production processes. This can reveal if rework orders take significantly longer or if certain order types are more prone to planning adjustments, providing valuable insights for targeted process improvement.

It allows for the segmentation of analysis by the order's business purpose, enabling comparison between standard production, rework, and other processes.

Found in the Production Order header table AFKO (field AUART).

The Planned Start Date is the target date by which production activities for an order are expected to begin. This is a key output of the scheduling process.

This attribute provides the starting baseline for schedule adherence analysis. Comparing the Planned Start Date to the actual start time helps in understanding front-end delays, such as delays in material staging or order release, which can have a cascading effect on the entire production timeline.

It provides a baseline for measuring start-time adherence, which is crucial for identifying delays in pre-production stages like order release and material availability.

Found in the Production Order header table AFKO (field GSTRP).

This calculated metric measures the end-to-end duration of a production order's lifecycle in execution. It is a key performance indicator that reflects the overall efficiency of the production process.

This attribute is the primary measure for the Production Order Lead Time Overview dashboard and the Average Production Order Cycle Time KPI. Analyzing its components, such as wait times versus processing times, helps identify the biggest opportunities for process acceleration and lead time reduction.

This is a critical KPI for measuring overall production efficiency and identifying opportunities to accelerate order fulfillment.

Calculated by finding the duration between the 'Production Order Released' activity and the 'Order Technically Completed' activity for each Production Order.

Production Priority is used by planners and schedulers to sequence and prioritize orders, especially when resources are constrained. A higher priority order should ideally be processed before a lower priority one.

Analyzing this attribute helps to assess whether the assigned priorities are being followed on the shop floor. The Production Prioritization Consistency dashboard compares the processing sequence against the assigned priority to identify inconsistencies, which can lead to improved scheduling discipline and better alignment between planning and execution.

It helps determine if production scheduling follows business priorities, ensuring that critical orders are expedited as intended.

This is often a custom field or based on other order parameters. A specific location is configuration-dependent.

This attribute captures the SAP user ID associated with a specific transaction or status change, such as releasing an order or entering a confirmation. It provides traceability for actions taken within the system.

Analyzing activities by User helps in understanding workload distribution, identifying training needs, and ensuring compliance with procedures. For example, it can highlight if certain users are frequently involved in plan adjustments or if delays are associated with specific teams.

It provides accountability and allows for analysis of workload, user-specific behavior, and potential training opportunities.

Typically found in change document headers (CDHDR, field UNAME) or confirmation records (AFRU, field PERNR for personnel number).