Your Production Planning Data Template

The Activity Name describes a specific task, status change, or event that happens during the lifecycle of a production order. These activities form the sequential steps of the process, such as 'Production Order Created', 'Materials Issued', or 'Production Completed'.

In process mining, activities are the nodes in the process map. Analyzing the sequence and frequency of these activities reveals the actual workflow, deviations from the standard process, and areas of rework or inefficiency. Different activities can be used to define milestones for KPI calculations, like measuring the time between 'Order Released' and 'Production Started'.

Activities define the steps of the process. Analyzing their sequence, duration, and frequency is the core of process mining.

Activity names are often derived from system status changes, transaction codes, or event logs related to production order objects.

Event Time records the exact moment an activity took place. This timestamp is crucial for ordering events chronologically and for calculating durations between different steps in the process. It serves as the primary temporal data point for process analysis.

Accurate timestamps are the foundation for all time-based analysis in process mining. They are used to build the process map, calculate cycle times between activities, measure waiting times, and identify bottlenecks. For instance, the difference between the Event Time of 'Production Started' and 'Production Completed' provides the actual production duration for an order.

This timestamp is essential for ordering events chronologically and calculating all time-based metrics, such as cycle times and lead times.

Timestamps are typically stored alongside transaction or status change records in the source system's event logs or document change history.

The Production Order ID is the primary key that uniquely identifies a single manufacturing job or work order from its creation to its completion. It serves as the case identifier for process mining, linking all related activities, timestamps, and attributes together to form a complete end-to-end process view.

In analysis, this ID is fundamental for tracking the lifecycle of each production order. It allows analysts to trace the path of an order through various stages such as planning, material checking, release, execution, and closure. By grouping all events by the Production Order ID, it becomes possible to calculate case durations, identify common process variants, and pinpoint bottlenecks affecting specific orders.

This is the essential case identifier that connects all related events, making it possible to reconstruct and analyze the end-to-end production planning process.

This identifier is typically found in the header table or primary document for production or work orders in the source system.

The Last Data Update timestamp marks the point in time when the data was last extracted from the source system. This is a technical attribute used to understand the freshness and timeliness of the data being analyzed.

This attribute is primarily used for data management and monitoring. It helps ensure that analyses are based on up-to-date information and allows data engineers to track the recency of the dataset. It is not typically used for direct process analysis but is critical for maintaining data integrity and trust in the results.

This technical field is vital for data governance, helping to track data freshness and ensure analyses are based on current information.

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

The Source System attribute specifies the originating application or platform, such as an ERP or MES, where the event data was generated. In environments with multiple integrated systems, this field helps distinguish the origin of different process steps.

Understanding the source system is important for data validation, troubleshooting, and governance. It provides context for the data, as different systems may have unique ways of capturing and defining events. In a complex landscape, analyzing data from different source systems can reveal integration delays or process fragmentation between platforms.

Provides crucial context about data origin, which is essential for data governance and for analyzing processes that span multiple systems.

This information may be available as a standard field in data extracts or can be added as a static value during the data transformation process.

The Planned End Date is the target timestamp for completing all production activities for an order. It represents the commitment date from production and is used to calculate the planned lead time.

Similar to the planned start date, this attribute is crucial for schedule adherence and on-time delivery performance analysis. Comparing the Planned End Date with the actual completion date reveals delivery variance and helps quantify the impact of production delays. Analyzing orders that frequently miss their planned end dates can highlight systemic issues in capacity planning, material supply, or production efficiency.

Acts as the key baseline for measuring on-time completion performance and understanding the drivers of production lead time variance.

This is a standard planning date found in the production order header or scheduling details.

The Planned Quantity is the amount of the product that the production order is intended to yield. This value is set during the planning phase based on demand from sales orders, forecasts, or stock replenishment policies.

This attribute provides context to the scale of each production order. It can be used to analyze if larger or smaller orders are more prone to delays or quality issues. Furthermore, comparing the Planned Quantity to the final completed quantity helps in calculating yield rates, scrap rates, and production efficiency, which are key performance indicators for any manufacturing operation.

Provides the target production volume, which is essential for analyzing yield, scrap rates, and the impact of order size on process performance.

The planned or target quantity is a fundamental field located in the header or item details of the production order.

The Planned Start Date is the target timestamp for commencing production activities for a given order. It is a key output of the scheduling process and serves as a baseline against which actual performance is measured.

This date is fundamental for schedule adherence analysis. By comparing the Planned Start Date with the actual start of production, companies can measure start-time variance and identify the root causes of delays. This analysis is critical for improving planning accuracy, managing shop floor capacity, and ensuring timely delivery to customers.

Serves as the baseline for measuring schedule adherence and analyzing the causes of delays between planning and execution.

This is a standard planning date found in the production order header or scheduling details.

The Plant attribute identifies the physical location where the production activities take place. It provides geographical or organizational context for the production order.

This attribute is crucial for comparative analysis between different manufacturing sites. By segmenting the process data by Plant, organizations can benchmark performance, identify best practices at high-performing locations, and uncover systemic issues at underperforming ones. It helps answer questions like, 'Which plant has the best schedule adherence?' or 'Are material availability issues concentrated in a specific location?'.

Enables performance benchmarking and comparison across different manufacturing locations, helping to identify site-specific issues and best practices.

The plant or location is a fundamental attribute of a production order, typically defined at the order header level.

The Product ID specifies the item that is the target of the production order. This could be a finished good, a sub-assembly, or a component. It links the production planning process to the specific material being produced.

Analyzing the process by Product ID is essential for understanding product-specific variations. It can help identify if certain products have longer lead times, require more rework, or follow different production paths. This type of analysis enables targeted improvements, such as optimizing the planning process for high-volume products or addressing issues with complex, low-volume items.

Allows for filtering and comparing process performance across different products, revealing product-specific bottlenecks or inefficiencies.

This identifier is a key piece of information on the production order and is typically found in the order header or item details.

The Production Order Status reflects the state of the order within its lifecycle, such as 'Created', 'Released', 'In Progress', 'Completed', or 'Cancelled'. This status provides a snapshot of where the order is in the overall process.

This attribute is highly valuable for root cause analysis. By filtering for orders with a 'Cancelled' status, analysts can investigate the reasons for cancellation. Comparing the process flow of orders that were completed on time versus those that were delayed can reveal patterns related to status changes. It also helps in identifying orders that get stuck in a particular status for too long.

Provides critical context about the order's lifecycle stage, which is essential for analyzing process deviations, delays, and outcomes like cancellations.

This is a standard field on the production order header that is updated as the order progresses through its lifecycle.

The User ID identifies the person or, in some cases, the system user, who executed a particular step in the process. This could be the planner who created the order, the manager who approved it, or the supervisor who confirmed a production step.

Analyzing the process by User ID can help in understanding workload distribution, identifying training needs, and ensuring compliance. For instance, it can reveal if certain planners consistently create orders that require frequent adjustments or if approval steps are frequently delayed by specific individuals. This human-centric analysis provides valuable insights for performance management and resource optimization.

Attributes process activities to specific individuals, enabling analysis of user performance, workload, and adherence to procedures.

User information is often recorded in the change logs or transaction history for production order events, linking a user to a specific timestamp and action.

The Completed Quantity represents the final, confirmed amount of goods produced by the order that meets quality standards. This is the actual output of the manufacturing process.

This attribute is critical for performance measurement. By comparing it against the Planned Quantity, analysts can calculate key metrics like order fulfillment rate, yield, and scrap. Analyzing discrepancies between planned and completed quantities can uncover issues related to production quality, machine performance, or material problems. It is a direct measure of the effectiveness of the production process.

Measures the actual output of the production process, enabling the calculation of critical KPIs like yield, scrap, and fulfillment rates.

This value is derived from goods receipt transactions or production confirmations that record the quantity of finished goods from the order.

The End Time represents the completion timestamp of an activity. While many activities are instantaneous and only have a Start Time, some have a measurable duration. For these activities, the End Time marks their conclusion.

When available, the End Time allows for a more precise analysis of activity durations. This is particularly useful for long-running tasks like 'Quality Inspection' or a specific production operation. By calculating the difference between End Time and Start Time, analysts can measure the exact processing time of individual steps, separating it from the waiting time between steps.

Enables the precise calculation of activity durations for tasks that are not instantaneous, helping to distinguish processing time from waiting time.

This is often available for activities that have distinct start and stop events logged in the system, such as production confirmations or inspection records.

The Material Availability Status is a flag or indicator that signals whether the necessary raw materials and components are physically available to start production. This check is a critical step before releasing an order to the shop floor.

This attribute is key to analyzing the impact of material shortages on production schedules. By correlating material unavailability with delays in order release or production start, organizations can quantify the cost of poor material planning. This analysis can drive improvements in inventory management, procurement processes, and supplier collaboration to ensure materials are available when needed, preventing costly disruptions on the production line.

Directly measures the impact of material shortages on production delays, helping to identify and address issues in procurement and inventory management.

This status is often the result of a material availability check transaction or batch job that runs against production orders before their release.

The Production Order Type categorizes orders based on their business purpose. Common types include standard production to fulfill regular demand, rework orders to fix defective items, prototype orders for new product development, or special orders for custom requests.

Analyzing the process by order type is extremely insightful. It allows for comparing the process flows and performance of different types of work. For example, rework orders are expected to follow a different path and have different cycle times than standard orders. Understanding the volume and process efficiency of each order type helps in resource planning and process optimization efforts tailored to specific business needs.

Allows for segmenting analysis by the order's business purpose, revealing different process behaviors for standard, rework, or special orders.

This is a configuration field on the production order, often selected at the time of order creation to control how it is processed.

The Work Center identifies the specific resource, such as a machine, assembly line, or group of employees, responsible for carrying out a production step. A production order may pass through multiple work centers during its lifecycle.

This attribute enables a detailed, resource-level analysis of the production process. By analyzing the data by Work Center, companies can measure resource utilization, identify capacity bottlenecks, and compare the performance of similar machines or lines. It helps answer critical questions like, 'Which work center is the primary bottleneck?' or 'Is there a high rework rate associated with a specific machine?'.

Enables resource-level analysis to identify capacity bottlenecks, measure utilization, and track the performance of specific machines or production lines.

Work center information is typically found at the operation or routing level of the production order.