Your Inventory Management Data Template

The Activity Name describes a single step or event within the inventory management process. These activities represent the discrete tasks performed on an inventory batch, such as quality inspections, internal movements, counting, picking, and shipping.

Analyzing activities is the core of process mining. It allows for the visualization of the process flow, identification of common and alternative paths, and measurement of the frequency of each step. Understanding the sequence of activities helps pinpoint inefficiencies, rework loops, and non-compliant process variations.

It defines the individual steps of the process, which is fundamental for discovering the actual process flow and identifying areas for improvement.

Often derived from transaction types, movement types, or event log descriptions in the source system's inventory or warehouse management modules.

The Inventory Batch/Lot is a unique identifier assigned to a specific quantity of a product received or produced at the same time. It allows for the tracking of a cohesive group of items throughout its entire lifecycle within the warehouse, from receiving to shipping or disposal.

In process mining, this ID is crucial as it defines the case. Each case represents the journey of one specific inventory batch or lot. By analyzing activities grouped by this identifier, businesses can understand the end-to-end flow, identify bottlenecks in specific batch handling, and track the lifecycle duration for different products or suppliers.

This is the essential link that connects all inventory-related activities into a single, traceable process, enabling end-to-end analysis of the batch or lot lifecycle.

Typically found in inventory transaction tables or material master data, often linked to goods movement records.

The Start Time, also known as the event time, is the precise date and time an activity was initiated or logged in the system. It provides the chronological context for every event in the inventory lifecycle.

This timestamp is essential for process mining as it establishes the sequence of events and enables the calculation of process metrics. It is used to calculate cycle times between activities, total case durations, and waiting times. Analyzing these time-based metrics is key to identifying delays and bottlenecks in the inventory handling process.

This timestamp is critical for ordering events chronologically and calculating all time-related performance metrics, such as cycle times and durations.

This is a standard field in most transaction or event log tables, often labeled as creation date, posting date, or event time.

This attribute records the date and time of the most recent data extraction or refresh from the source system. It is a metadata field that reflects the timeliness of the data being analyzed.

In process mining, the Last Data Update timestamp is vital for understanding the currency of the analysis. It helps users know if they are looking at real-time information or a snapshot from a specific point in time. This is critical for operational monitoring and ensuring that decisions are based on up-to-date information.

It informs users about the freshness of the data, ensuring they understand the time frame of the analysis and the relevance of the insights.

This is typically metadata generated and stored by the data extraction, transformation, and loading (ETL) tool or process.

The Source System attribute specifies the originating application or platform for the event data. In complex IT landscapes, inventory data may come from multiple systems, such as a Warehouse Management System (WMS) for operational data and an Enterprise Resource Planning (ERP) system for financial data.

This attribute is important for data validation, troubleshooting, and understanding the context of the data. It allows analysts to trace data back to its origin and can be used to compare processes or data quality across different systems or company subsidiaries.

It provides context about the data's origin, which is crucial for data governance, validation, and in environments with multiple interacting systems.

This information can be a static value added during data extraction or a field within the source data tables that identifies the system instance.

The End Time marks the precise date and time that an activity concluded. While some activities are instantaneous and only have a single timestamp (StartTime), others have a measurable duration, like a quality inspection or a put-away task.

Having both a Start Time and an End Time is crucial for detailed performance analysis. It allows for the direct calculation of activity processing times, which is a key input for identifying bottlenecks. Analyzing the duration of specific tasks helps in understanding resource efficiency, workload distribution, and areas where process steps are taking longer than expected.

It enables the precise calculation of activity processing times, which is essential for identifying bottlenecks and measuring operational efficiency.

Found in event or transaction logs where activities have a defined start and finish, common in Warehouse Management Systems (WMS).

The Movement Reason attribute provides context for why an inventory transaction occurred, especially for non-standard movements like adjustments, returns, or scraps. It captures the business justification behind the activity.

This is a critical attribute for root cause analysis. By analyzing the frequency of different reason codes, a business can identify the primary drivers of inventory discrepancies, such as damage, obsolescence, or data entry errors. This information is invaluable for developing targeted process improvements to enhance inventory accuracy and reduce waste.

It explains the 'why' behind inventory adjustments and movements, enabling root cause analysis of issues like stock discrepancies, damages, or scrap.

Found in transaction data for inventory adjustments, scraps, or other non-standard movements.

The Product Category is a higher-level grouping of products based on shared characteristics. This classification helps in organizing and analyzing inventory performance across broad segments rather than individual items.

In process mining, this attribute allows for aggregated analysis to identify trends and patterns at a strategic level. For instance, an organization can compare the inventory turnover rates or quality inspection failure rates between different categories like 'High-Value Electronics' and 'Consumables'. Such insights are valuable for category management, strategic sourcing, and optimizing overall inventory policy.

It allows for high-level, aggregated analysis to compare process performance across different product groups and inform strategic decisions.

Typically found in the material or item master data, linked via the Product ID.

The Product ID, often called an SKU or Material Number, is the unique code assigned to a specific item in the inventory. It distinguishes one product from another.

This attribute is essential for product-centric analysis. It allows businesses to filter the process for specific items or groups of items to understand how their handling differs. For example, one can compare the put-away times for fragile vs. durable goods, or the inspection rates for different product lines. This helps in optimizing warehouse layout, handling procedures, and inventory strategy based on product characteristics.

It enables product-level analysis, allowing teams to compare process performance for different items and tailor inventory strategies accordingly.

A core field in inventory transaction tables, material master data, or item master records.

Quantity represents the amount of stock being handled in a given activity, such as the number of items received, moved, or picked. It is a fundamental measure of the scale of each transaction.

Analyzing the quantity is vital for understanding the operational workload and identifying potential issues. For example, large-quantity movements may be correlated with longer processing times. It is also used to calculate inventory accuracy by comparing physical counts to system records. Furthermore, tracking quantities in adjustment activities helps quantify the scale of inventory discrepancies.

It provides a measure of the transaction's magnitude, which is crucial for workload analysis, calculating inventory levels, and quantifying discrepancies.

A standard field in almost all inventory transaction records.

The User attribute identifies the person or system agent responsible for executing an inventory transaction. This could be a warehouse operator, a quality inspector, or an automated system user for robotic processes.

Analyzing activities by user is fundamental for performance management and identifying training needs. It can reveal which users or teams are most efficient, who might be deviating from the standard process, or which tasks are most prone to human error. This analysis helps in resource allocation, workload balancing, and ensuring process compliance across the organization.

It provides accountability and allows for performance analysis by employee or team, helping to identify top performers and opportunities for training.

Commonly available in transaction data, linked to the user account that created or modified the record, such as 'Created By' or 'User ID' fields.

The Warehouse attribute identifies the physical facility, such as a distribution center or plant, where the inventory is stored and handled. It represents a key organizational and geographical dimension of the inventory process.

This attribute is essential for location-based performance analysis. It allows organizations to compare efficiency, accuracy, and cycle times across different sites. For example, a company can identify which warehouses have the fastest put-away times or the highest inventory accuracy, then investigate best practices at top-performing locations to replicate them elsewhere.

It enables site-by-site performance comparison, helping to identify best practices at high-performing locations and areas needing improvement at others.

A standard organizational data element found in nearly all inventory transaction records.

Activity Duration is a calculated metric that measures the processing time for a single activity. It is computed as the difference between the End Time and the Start Time.

This metric is a cornerstone of performance analysis, providing direct insight into the efficiency of individual process steps. By aggregating and comparing activity durations, businesses can identify the most time-consuming tasks in the inventory lifecycle. This information can be used to set performance benchmarks, monitor operational efficiency, and focus improvement efforts on the activities that create the most significant delays.

This calculated metric directly measures the efficiency of individual tasks, making it easy to spot the most time-consuming steps in the process.

Calculated by subtracting the StartTime from the EndTime. This requires both timestamps to be available for an activity.

The Stock Status describes the usability or availability of the inventory. Common statuses include 'Unrestricted' (available for use), 'Quality Inspection' (pending quality checks), 'Blocked' (not available for use), or 'In Transit'. An activity like 'Inventory Status Changed' directly modifies this attribute.

Analyzing the time spent in different statuses is crucial for understanding inventory flow and availability. It helps quantify how long inventory is tied up in non-productive states, such as quality inspection or being blocked. This analysis can highlight delays in the quality process or issues with stock that prevent it from being used, directly impacting inventory carrying costs and service levels.

It tracks the availability of inventory, helping to analyze how long stock remains in non-productive states like quality inspection or being blocked.

Typically found in inventory balance or stock level tables, and recorded during specific status-changing transactions.

The Storage Location provides a more granular level of detail than the Warehouse attribute. It specifies the exact area, such as a bin, aisle, or zone, where an inventory activity took place. This could be a receiving dock, a quality inspection area, a specific storage bin, or a packing station.

Analyzing processes at the storage location level can uncover inefficiencies in warehouse layout and material flow. For example, it can highlight excessive travel time for internal movements between distant locations or identify congestion in certain zones. These insights are valuable for optimizing warehouse layout, slotting strategies, and picking paths.

It allows for granular analysis of intra-warehouse movements, helping to optimize layout, reduce travel time, and identify congested areas.

Common in Warehouse Management Systems (WMS), found in transaction data as fields like 'Bin', 'Location', or 'Storage Bin'.

The Unit of Measure (UoM) provides context for the Quantity attribute. It specifies the standard unit used to count or measure the inventory item in a particular transaction.

While seemingly simple, the UoM is critical for data accuracy and meaningful analysis. Without it, comparing quantities can be misleading, for example, '10' could mean 10 individual items or 10 pallets of items. This attribute ensures that analyses are performed on a consistent basis, often by converting different UoMs to a standard or base unit for accurate comparisons and aggregations.

It provides essential context to the 'Quantity' attribute, ensuring accurate comparisons and calculations across different types of products and transactions.

Usually located alongside the quantity field in transaction data or in the item master data.