Your Credit Management & Collections Data Template

This attribute describes a single step in the invoice lifecycle, such as 'Invoice Generated', 'Dunning Procedure Initiated', or 'Payment Received'. Each activity represents a distinct event that moves the case forward.

Analyzing the sequence and frequency of activities is the core of process mining. It helps uncover the actual process flow, identify bottlenecks where cases get stuck, detect rework loops where activities are repeated, and compare the actual process against the designed or ideal process. The Activity Name is fundamental for building process maps and calculating transition times between steps.

This attribute defines the steps in the process map, allowing for the visualization and analysis of the invoice lifecycle from start to finish.

This is a conceptual field derived from various business events within Oracle Fusion Financials, often constructed by mapping transaction statuses, event dates, or specific actions from modules like Receivables (AR) and Advanced Collections.

The Event Time, or timestamp, records the exact moment an activity took place. It is essential for ordering events chronologically to build an accurate process flow. Without accurate timestamps, the sequence of events cannot be determined correctly.

In analysis, this attribute is used to calculate durations and cycle times between activities, which is critical for performance measurement. For example, it is used to calculate KPIs like Dispute Resolution Cycle Time or Invoice Payment Cycle Time. It also enables the analysis of process performance trends over different time periods.

This timestamp is essential for ordering events, calculating cycle times and durations, and analyzing process performance over time.

Derived from various date fields across Oracle Fusion Financials tables, such as TRX_DATE in RA_CUSTOMER_TRX_ALL for invoice creation or the creation date of a collection action.

The Invoice Number is the central key that links all events and activities related to a single receivable, from its creation to its final settlement or write-off. It allows for a complete, end-to-end view of the invoice lifecycle.

In process mining analysis, this attribute is used to reconstruct the journey of each invoice. By grouping all related activities under a single Invoice Number, analysts can visualize process flows, identify common and deviant paths, and measure cycle times for the entire process or specific stages, such as dispute resolution or payment posting.

This is the essential Case ID that connects all related process steps, enabling the reconstruction and analysis of each invoice's journey from issuance to closure.

This identifier is typically found in the RA_CUSTOMER_TRX_ALL table as TRX_NUMBER in Oracle Fusion Financials.

This attribute marks the date and time of the most recent data extraction. It is a metadata field that is not part of the business process itself but is crucial for understanding the freshness of the data being analyzed.

Analysts use this timestamp to confirm they are working with up-to-date information and to understand the cutoff point for the data. It is essential for data governance and for managing user expectations about data currency in dashboards and reports.

Indicates the freshness of the data, ensuring analysts and stakeholders are aware of the data's timeliness and relevance.

This value is generated and stamped on each record during the data extraction and loading (ETL) process.

This attribute identifies the source application where the event data was recorded. In a complex IT landscape, multiple systems might be involved in a single end-to-end process.

Specifying the source system is important for data governance, troubleshooting, and understanding the context of the data. It helps differentiate events from various systems if they are combined into a single process view, ensuring data lineage is clear.

Provides clarity on data origin, which is crucial for data validation, governance, and understanding the technological context of the process.

This is typically a static value added during data extraction to identify the origin of the records.

The Collector is the individual or team responsible for managing the collection activities for an overdue invoice. This assignment is a key step in the collections workflow.

This attribute is crucial for performance management and resource allocation within the collections department. By analyzing outcomes per collector, managers can assess collector effectiveness, identify training needs, and balance workloads. The Collector Assignment Effectiveness dashboard directly relies on this attribute to compare success rates and cycle times across different collectors.

Enables performance analysis of individual collectors or teams, helping to optimize resource allocation and improve overall collection efficiency.

This information is typically stored in the Oracle Advanced Collections module, often in tables like IEX_CASES_ALL_B or related assignment tables.

The Customer Number links an invoice to a specific customer account. This allows for segmentation and analysis of the credit and collections process based on customer attributes.

By including the Customer Number, analysts can investigate whether certain customers consistently pay late, raise more disputes, or require more collection efforts. This information is vital for creating customer-specific collection strategies, adjusting credit terms, and identifying high-risk customer segments. It directly supports analyses like the Invoice Write-Off Rate Analysis by Customer Segment.

Enables segmentation of the process by customer, helping to identify patterns, risks, and opportunities for tailored collection strategies.

Typically found in the RA_CUSTOMER_TRX_ALL table as BILL_TO_CUSTOMER_ID, which links to HZ_CUST_ACCOUNTS.

Customer Segment is a categorical attribute that groups customers based on shared characteristics. Segments could be defined by factors like 'Strategic', 'SMB', 'Enterprise', or by industry like 'Manufacturing' or 'Retail'.

This attribute is powerful for comparative analysis. It allows analysts to compare process performance across different segments to see, for example, if one segment has a higher rate of disputes or a longer payment cycle. This insight helps tailor credit policies and collection strategies to the specific needs and risks of each segment, supporting dashboards like the Invoice Write-Off Rate Analysis.

Allows for powerful comparative analysis, revealing how process performance and risks vary across different customer groups.

Often managed in customer master data (HZ_CUST_ACCOUNTS or related tables) or derived from customer attributes like revenue or industry.

The Due Date is a critical date attribute contractually agreed upon for payment. It is the baseline against which timeliness of payment is measured.

This attribute is fundamental for identifying overdue invoices and calculating the number of days an invoice is past due. It is the primary input for determining when dunning procedures should be initiated and is used in calculating KPIs like Days Sales Outstanding (DSO). It is also essential for creating aging reports that classify outstanding debt.

Acts as the baseline for determining if an invoice is overdue, triggering collection activities and enabling aging analysis.

Available in the AR_PAYMENT_SCHEDULES_ALL table as DUE_DATE.

Dunning Level indicates the intensity of the collection reminder, which typically escalates over time. For example, Level 1 might be a gentle email reminder, while Level 3 could be a formal letter or a phone call.

Analyzing the process by Dunning Level helps assess the effectiveness of the dunning strategy. The Dunning Effectiveness Dashboard uses this attribute to visualize conversion rates from each dunning step to payment. This allows the business to determine which dunning actions are most effective and to fine-tune the timing and content of reminders to maximize collections.

Tracks the escalation stage of collection efforts, which is critical for evaluating the effectiveness of the dunning strategy.

This data is managed within the Oracle Advanced Collections module. It can be found in tables related to dunning history, such as IEX_DUNNINGS.

The Invoice Amount represents the total value of the goods or services billed to the customer. This is a critical financial attribute for understanding the monetary impact of the process.

In analysis, Invoice Amount is used to prioritize collection efforts, focusing on high-value overdue invoices. It is also used to analyze payment behaviors based on transaction value and to calculate the financial impact of write-offs. Dashboards like the Invoice Write-Off Rate Analysis rely on this value to assess the magnitude of financial losses.

Provides financial context to the process, enabling prioritization of high-value invoices and analysis of the monetary impact of process inefficiencies.

This information can be derived from the AR_PAYMENT_SCHEDULES_ALL table, which stores the amount due for an invoice.

This attribute identifies the specific employee or automated system user responsible for executing an activity, such as approving a credit limit, posting a payment, or resolving a dispute.

Analyzing activities by user is essential for understanding workload distribution, individual performance, and compliance. For automated activities, it helps track the involvement of system processes. It can also be used to identify training needs or potential fraudulent activity by monitoring user behavior.

Attributes process activities to specific individuals or automated systems, enabling performance tracking, workload analysis, and auditing.

Sourced from 'CREATED_BY' or 'LAST_UPDATED_BY' columns in various transaction and history tables throughout Oracle Fusion Financials.

In large organizations, operations are often divided into multiple business units. This attribute identifies which business unit is associated with the invoice.

Analyzing the process by Business Unit enables comparison of performance across different parts of the organization. It can highlight inconsistencies in how credit and collections policies are applied and reveal which business units are more effective at managing their receivables. This helps in sharing best practices and standardizing processes where needed.

Enables performance comparison across different organizational units, helping to identify best practices and areas for improvement.

Available in the RA_CUSTOMER_TRX_ALL table via the ORG_ID field, which links to the organization structure.

The Credit Limit Amount is the total credit exposure a company is willing to have with a particular customer. This is determined during the credit review process.

This attribute is essential for the Credit Limit Decision Impact dashboard. By correlating the approved credit limit with subsequent payment behavior and write-offs, the business can assess the effectiveness of its credit risk policies. Analysis may reveal if excessively high credit limits are contributing to higher rates of bad debt, helping to refine the credit approval process.

Crucial for assessing the effectiveness of credit risk policies by correlating the approved credit limit with payment outcomes and write-offs.

This is managed in Oracle Credit Management and is typically stored in tables related to customer credit profiles, such as HZ_CUST_PROFILE_AMTS.

This calculated metric quantifies how late an unpaid invoice is. It is calculated as the difference between the current date (for open invoices) or the payment date (for closed invoices) and the due date.

Days Overdue is a critical measure for aging analysis and prioritizing collection efforts. It is the primary metric in the Overdue Invoice Aging & Status dashboard, where invoices are grouped into aging buckets (e.g., 1-30 days, 31-60 days). This helps the collections team focus on the oldest and highest-risk debts.

Quantifies the extent of payment delays, serving as a core metric for prioritizing collections and conducting aging analysis.

This is a calculated field. The logic is: CurrentDate - DueDate for open invoices, or PaymentDate - DueDate for closed invoices.

When a customer disputes an invoice, they typically provide a reason, such as 'Incorrect Pricing', 'Damaged Goods', or 'Duplicate Invoice'. This attribute captures that reason.

Analyzing dispute reasons is key to root cause analysis. It helps identify recurring problems in upstream processes like order management or billing that lead to payment delays. By categorizing and tracking the frequency of different dispute reasons, a business can take targeted actions to fix these root causes, which supports the goal of shortening the Dispute Resolution Cycle Time.

Helps identify the root causes of invoice disputes, enabling proactive improvements to upstream processes to prevent future disputes.

This information is typically captured in the Oracle Advanced Collections or Oracle Channel Revenue Management modules if dispute management is formalized. It may reside in tables like AR_DISPUTE_HISTORY.

For activities that have a distinct start and end, this attribute captures the completion time. While many events in process mining are instantaneous, some, like 'Dispute Investigation', can span a period of time.

Having a separate End Time allows for the precise calculation of activity processing times. This is more accurate than inferring duration from the start time of the next activity, especially when there are idle periods. It is crucial for analyzing resource utilization and identifying which specific steps are taking the most time within the process.

Enables accurate calculation of how long specific activities take, providing deeper insight into bottlenecks and resource utilization.

This is often a conceptual attribute. It may be sourced from a 'last updated' timestamp or a specific 'close date' field in the source tables corresponding to the activity.

This attribute specifies the currency of the invoice, such as USD, EUR, or GBP. In multinational organizations, invoices are often issued in various currencies.

Analyzing data with multiple currencies requires careful handling. This attribute allows for filtering the process view by currency or for applying the correct exchange rates for consolidated financial reporting. It ensures that monetary values are interpreted correctly and that comparisons of amounts are made on a like-for-like basis.

Essential for correctly interpreting financial data in a multi-currency environment and ensuring accurate financial analysis.

Typically found in the RA_CUSTOMER_TRX_ALL table as INVOICE_CURRENCY_CODE.

Invoice Status provides a snapshot of where the invoice currently stands in the process. Common statuses include 'Open', 'Paid', 'Disputed', 'Past Due', or 'Written Off'. This attribute provides a high-level overview of the state of receivables.

In process mining, this attribute is useful for filtering cases to focus on specific populations, such as all open overdue invoices. It is a key dimension in the Overdue Invoice Aging & Status dashboard, providing immediate visibility into the current state of the invoice portfolio and helping to prioritize collection activities.

Provides a quick overview of the current state of an invoice, allowing for easy filtering and prioritization of collection efforts.

Typically available in the AR_PAYMENT_SCHEDULES_ALL table in a field named STATUS.

This is a derived attribute that provides a simple true or false indication of an invoice's overdue status. It is typically calculated by comparing the current date (or the payment date) with the invoice's due date.

This flag is extremely useful for filtering and segmentation in analysis. It allows analysts to quickly isolate the population of overdue invoices to study their process paths, the effectiveness of collection activities, and other characteristics. It simplifies the creation of dashboards and KPIs focused on managing overdue debt, such as the Overdue Invoice Aging & Status dashboard.

Provides a simple, clear flag for identifying and analyzing all overdue invoices, which is the primary focus of the collections process.

This is a calculated field. The logic is: IF CurrentDate > DueDate AND Status != 'Paid' THEN True ELSE False.

This is a derived flag that identifies invoices that the company has deemed uncollectible and has removed from its active receivables. This is typically the final, and undesirable, outcome for an invoice.

This attribute is essential for calculating the Invoice Write-Off Rate KPI and for the associated analysis dashboard. It allows analysts to isolate the population of failed collections to identify common characteristics, such as customer segment or invoice value, that may be associated with a higher risk of write-off. This insight is used to improve credit policies and collection strategies.

Clearly identifies cases of collection failure, which is essential for analyzing root causes of bad debt and calculating write-off rates.

This is a calculated field, derived by checking if an 'Invoice Written Off' activity exists for the case or if the invoice status is 'Written Off'.

Payment Terms define the conditions under which a customer is expected to pay, for example, 'Net 30' or 'Net 60'. These terms are used to calculate the invoice due date.

Analyzing payment performance by payment terms can reveal interesting patterns. For instance, customers with shorter terms might be more likely to pay late. This information can be used to review and optimize credit policies and to segment customers for different collection strategies. It provides valuable context for understanding why certain invoices become overdue.

Provides context on the agreed payment schedule, enabling analysis of payment behavior across different credit terms.

This is stored in the RA_TERMS table and linked to the invoice transaction.

Processing time measures the active work time for a specific task, excluding any waiting or idle time. It is calculated as the difference between an activity's End Time and Start Time.

This metric is invaluable for performance analysis, as it helps distinguish between time spent actively working on a case versus time spent waiting for something else to happen. For example, it can highlight inefficiencies in the 'Dispute Resolution' activity itself, separate from the time the dispute was waiting to be assigned. This supports dashboards like Collections Workflow Efficiency.

Measures the actual work duration of activities, helping to pinpoint inefficiencies within specific tasks rather than just the time between them.

This is a calculated metric, derived by subtracting the StartTime from the EndTime (EndTime - StartTime).

During collection activities, a customer may commit to making a payment on a future date. This 'Promise to Pay Date' is recorded to track this commitment.

This attribute is important for managing collection workflows and evaluating the reliability of customer commitments. By comparing the Promise to Pay Date with the actual Payment Received date, collectors can assess the success rate of these promises. It helps in forecasting cash flow more accurately and in deciding when to escalate collection efforts if a promise is broken.

Tracks customer payment commitments, helping to forecast cash inflows and manage the effectiveness of collection negotiations.

Stored within the Oracle Advanced Collections module, likely in tables such as IEX_PROMISES_T.