Data Template: Order to Cash - Sales Order Processing

The Activity Name describes a step or milestone in the sales order lifecycle, such as 'Sales Order Created', 'Credit Check Performed', or 'Goods Shipped'. Each activity represents a distinct action taken on the sales order, forming the building blocks of the process map.

Analysis heavily relies on this attribute to visualize the process flow, identify common pathways, and discover deviations from the standard procedure. By analyzing the sequence of activities, analysts can pinpoint bottlenecks, rework loops (e.g., repeated 'Sales Order Changed' activities), and non-compliant process variations. It is fundamental to dashboards like 'Process Conformance and Deviations' and KPIs such as 'Sales Order Rework Rate'.

It defines the steps in the process, making it possible to visualize the process map, analyze process flows, and identify rework or deviations.

Often derived from document status changes, event logs, or transaction codes within the source system's sales, delivery, and billing modules.

The Event Time is a timestamp that records the exact moment an activity took place. This attribute provides the temporal context for the process, allowing for the chronological ordering of all events associated with a sales order.

This timestamp is critical for all time-based analysis. It is used to calculate cycle times between any two activities, identify the duration of specific steps, and pinpoint delays or bottlenecks. For example, the 'Order Fulfillment Cycle Time' KPI is calculated as the difference between the Event Time of the final delivery activity and the initial order creation activity. Dashboards like 'Sales Order Cycle Time Overview' are entirely dependent on this attribute to function.

This timestamp is crucial for calculating all performance metrics, such as cycle times and durations, which are essential for identifying bottlenecks.

Typically found alongside each transaction or status update record, often labeled as a creation date, change date, or posting date.

The Sales Order ID is the cornerstone of process mining in Order to Cash, uniquely identifying each instance of the process from creation to closure. It acts as the primary key that links all related activities, events, and data points together, forming a complete end-to-end journey for a single order.

In analysis, this attribute allows for the reconstruction of each sales order's lifecycle. It is used to trace the sequence of events, measure durations between activities, and aggregate metrics at the order level. For example, calculating the 'Order Fulfillment Cycle Time' KPI requires grouping all activities by their Sales Order ID and finding the time difference between the first and last event.

This ID is essential for tracking individual orders through the process, enabling case-level analysis of cycle times, bottlenecks, and deviations.

Typically found in the header table of sales order documents in the source ERP or CRM system.

This attribute provides a timestamp for when the data was last loaded into the process mining environment. It reflects the freshness of the data being analyzed and is distinct from the Event Time, which records when the business activity actually occurred.

While not typically used for direct process flow analysis, this information is vital for data governance and ensuring the reliability of the findings. It allows analysts and business users to understand the timeliness of the insights generated. For instance, if the Last Data Update was a week ago, any conclusions drawn about current performance must be qualified with this fact.

This indicates data freshness, ensuring that analyses are based on up-to-date information and that conclusions are relevant.

This is typically generated and stored by the data extraction (ETL) tool or the process mining platform during data ingestion.

The Source System attribute specifies the system of record where the event data was generated. In modern enterprises, an end-to-end process like Order to Cash often spans multiple applications, for instance, a CRM for order creation and an ERP for fulfillment and invoicing.

In analysis, this attribute is valuable for understanding the technological landscape of the process. It helps in identifying integration points and potential data consistency issues between different systems. Analyzing activities by source system can reveal if certain process steps are handled differently or experience more delays depending on the system they are executed in.

It provides context about data origin, which is crucial in environments with multiple systems to trace data lineage and identify system-specific process variations.

This information is often added during the data extraction (ETL) process or can be a standard field in data warehouses.

This attribute identifies the external party for whom the sales order is being processed. It can be a unique customer number, a company name, or another key that distinguishes one customer from another.

In process mining, the Customer Identifier is a powerful dimension for segmenting the data. Analysts can filter the process map to see how the process behaves for a specific customer or compare process flows between different customer groups, such as strategic accounts versus occasional buyers. This can reveal customized processes or highlight customers who frequently cause process deviations or delays, providing valuable insights for customer relationship management.

Allows for filtering and comparing processes across different customers or customer groups to identify tailored processes or problematic accounts.

Found in the sales order header data, linked to the customer master data in the source ERP or CRM system.

Order Value represents the total financial worth of the sales order. This is a critical financial metric that quantifies the magnitude of each case instance.

This attribute is invaluable for value-based process analysis. It allows for the prioritization of issues by focusing on high-value orders. For example, analysts can investigate if high-value orders experience longer cycle times or more rework than low-value orders. It's also used to calculate the financial impact of process inefficiencies, such as the total value of orders delayed by a specific bottleneck. This creates a powerful business case for process improvement initiatives.

Enables value-based analysis, helping to prioritize process improvements by focusing on high-value orders and quantifying the financial impact of delays.

Available in the sales order header data, often calculated as the sum of all line item net values.

The Product Identifier, such as a material number or SKU, specifies what is being sold. While a sales order can contain multiple products, this attribute often represents the primary product or can be aggregated into a product category for high-level analysis.

This attribute allows for a product-centric view of the Order to Cash process. Analysis can reveal if certain products are associated with longer fulfillment times, more frequent delivery issues, or higher rates of cancellation. This insight is critical for supply chain planning, inventory management, and product portfolio strategy. For example, discovering that a specific product line consistently faces delays in the 'Released To Warehouse' step can trigger an investigation into its stock levels or warehouse placement.

Enables analysis of process performance for different products or product groups, helping to identify product-specific bottlenecks or issues.

Found at the line-item level of a sales order. For case-level analysis, it might be represented by the most significant line item or a derived product category.

The Sales Channel indicates the origin or method by which an order was placed. This could be an online portal, a direct sales team, an EDI connection with a partner, or a retail store.

Analyzing the process by Sales Channel can reveal significant variations in efficiency and conformance. For instance, orders from the web channel might be highly automated and fast, while orders from direct sales may involve more manual changes and longer approval cycles. This analysis helps businesses optimize each channel's specific process flow and allocate resources more effectively. It provides a key dimension for dashboards like 'Order Fulfillment Bottlenecks'.

Allows for comparison of process performance across different channels, revealing variations in efficiency, automation, and conformance.

This information is usually stored in the sales order header data and is often a required field during order entry.

The User Name attribute identifies the individual or automated agent responsible for performing a given activity. This could be a sales representative who created the order, a credit manager who approved it, or a system user that automatically posted a payment.

This attribute enables a human-centric analysis of the process. It is used to analyze workload distribution, compare performance between teams or individuals, and identify training opportunities. It's also key for compliance and audit trail purposes. Analyzing activities by user helps uncover who is involved in rework loops or non-compliant behavior and is fundamental to calculating the 'Manual Intervention Rate' KPI.

Identifies the person or system performing an activity, enabling analysis of workload, team performance, automation levels, and compliance.

Commonly found in transaction logs or document change histories, often labeled as 'Created By' or 'Changed By'.

The Actual Delivery Date is the timestamp that records the successful delivery of the goods to the customer. This is often based on proof of delivery from the shipping carrier.

This attribute is the definitive measure for fulfillment success. It is the final data point used to calculate the 'On-Time Delivery Rate' by comparing it against both the Requested and Confirmed Delivery Dates. Analyzing the time gap between the 'Goods Shipped' activity and the Actual Delivery Date can also provide insights into the performance of logistics partners and shipping methods.

This is the final proof of fulfillment and is essential for accurately calculating the On-Time Delivery Rate and the total Order Fulfillment Cycle Time.

Often comes from an external logistics or shipping system and is integrated back into the ERP. It may be derived from the 'Goods Delivered' activity's timestamp.

After checking inventory and production schedules, the company provides a Confirmed Delivery Date. This represents the organization's commitment to the customer and is the internal benchmark for measuring fulfillment performance.

This attribute is crucial for evaluating internal operational efficiency. It is used in the 'On-Time Delivery Rate' KPI, where it is compared to the Actual Delivery Date to determine if the company met its own commitment. Significant discrepancies between the Requested and Confirmed Delivery Dates across many orders can signal systemic issues with available-to-promise (ATP) calculations or capacity planning.

Represents the company's commitment to the customer and is the internal benchmark for measuring on-time delivery and fulfillment reliability.

Found in the sales order schedule line data, which is often updated after an availability check or production planning run.

This boolean attribute distinguishes between tasks executed by human users and those performed by system automation, such as background jobs, APIs, or RPA bots. For example, a credit check could be an automated step, while resolving a credit block is typically manual.

Analyzing the process through the lens of automation is critical for digital transformation initiatives. This flag is the primary data point for calculating the 'Manual Intervention Rate' KPI. It helps identify which parts of the process are highly automated and which are still reliant on manual work. This analysis can highlight opportunities for further automation to reduce costs, minimize errors, and accelerate cycle times.

Distinguishes between manual and automated tasks, which is key to measuring automation levels and identifying opportunities for process improvement.

This information can be derived from the 'User Name' attribute (e.g., identifying system users like 'BATCH_USER') or from specific fields in event logs that track the execution context.

The Order Status provides a snapshot of where the sales order is in its lifecycle at a specific point in time. It's a categorical label that summarizes the current state of the order.

While the sequence of activities provides a detailed process map, the Order Status attribute is useful for creating a simplified, high-level view of the process. It can be used to filter for all orders currently in a specific state, for example, all orders 'On Credit Hold'. Analyzing the time spent in different statuses can also reveal bottlenecks, for instance, orders spending too much time in a 'Waiting for Approval' status.

Provides a high-level summary of an order's state, useful for filtering, status analysis, and identifying orders stuck in a particular phase.

This is a standard field in the header of most sales order documents in ERP and CRM systems.

The Payment Due Date is calculated based on the invoice date and the customer's agreed-upon payment terms. It sets the deadline for timely payment and is a key element of the accounts receivable process.

This attribute is fundamental for analyzing the financial portion of the Order to Cash cycle. It is the benchmark used to determine if a payment was on time, which is a direct input for the 'On-Time Payment Rate' KPI. The 'Invoice to Payment Cycle' dashboard heavily relies on this date to analyze payment behaviors and manage working capital effectively. Delays between invoice creation and payment can be benchmarked against this date to identify slow-paying customers.

Crucial for financial analysis, this date is the baseline for calculating the On-Time Payment Rate and managing accounts receivable.

Typically found on the customer invoice document and is derived from the invoice date and the payment terms specified in the customer master data or sales order.

When a sales order is cancelled or an item is rejected, the Rejection Reason provides the business context for this negative outcome. Reasons can range from 'Customer Canceled' and 'Incorrect Price' to 'Out of Stock'.

This attribute is essential for root cause analysis of process failures. By analyzing the frequency of different rejection reasons, a business can identify systemic problems. For example, a high number of cancellations due to 'Incorrect Price' might point to issues in the quoting or master data processes. This analysis directly supports efforts to improve the 'First-Time Right Rate' and reduce process waste.

Explains why orders fail, enabling root cause analysis to address underlying issues in pricing, inventory, or customer communication.

Typically found at the sales order line item level and is selected from a predefined list of codes when an item is cancelled.

This date represents the customer's desired delivery timeline. It is a critical piece of information captured at the beginning of the process and serves as the primary benchmark for customer satisfaction regarding delivery timeliness.

In process analysis, the Requested Delivery Date is compared against other key dates, like the Confirmed and Actual Delivery Dates, to measure service levels. It is a key input for the 'On-Time Delivery Performance' dashboard and is used to calculate whether a delivery was on time from the customer's point of view. Analyzing gaps between requested and confirmed dates can also highlight issues in planning and scheduling.

Serves as the customer's expectation for delivery, forming a baseline for measuring on-time delivery performance and customer satisfaction.

Typically located in the sales order header or line item details, entered during the order creation process.