Overview
The Add Days to a Date enrichment creates a new timestamp attribute by adding a specified number of days to an existing date attribute in your dataset. This enrichment is essential for calculating future dates, deadlines, and expected milestones based on your process data. By using a numeric attribute to specify the number of days to add, you can dynamically calculate dates that vary by case - for example, adding different payment terms to invoice dates based on customer agreements, or calculating expected delivery dates based on service level agreements. This capability is particularly valuable for deadline monitoring, SLA compliance tracking, and predictive process analytics where you need to project future dates based on current process state.
The enrichment supports flexible date calculations by accepting the number of days from any numeric attribute in your dataset. This means you can use calculated fields, lookup values, or imported data to determine how many days to add, making it powerful for complex business scenarios where the time offset varies based on case characteristics.
Common Uses
- Payment Due Date Calculation: Add payment terms (30, 60, 90 days) to invoice dates to determine when payments are due
- SLA Deadline Tracking: Calculate service level agreement deadlines by adding contractual response times to ticket creation dates
- Expected Delivery Dates: Add standard shipping times to order dates to predict when customers will receive their products
- Contract Renewal Dates: Calculate renewal dates by adding contract duration periods to start dates
- Warranty Expiration: Determine warranty end dates by adding warranty periods to purchase or installation dates
- Project Milestone Planning: Calculate expected milestone dates by adding planned durations to project start dates
- Regulatory Compliance Deadlines: Add regulatory response periods to submission dates to track compliance windows
Settings
New Attribute Name: The name for the new date attribute that will be created in your dataset. This attribute will contain the calculated future date. Choose a descriptive name that clearly indicates what the date represents, such as "Payment_Due_Date", "SLA_Deadline", or "Expected_Delivery_Date". This new attribute will be available for use in filters, dashboards, and other enrichments.
Attribute Name: Select the existing date/timestamp attribute that serves as your starting point for the calculation. This must be a DateTime type attribute in your case table. Common examples include "Invoice_Date", "Order_Date", "Ticket_Created", or any timestamp attribute from your process. The enrichment will use this date as the base and add the specified number of days to it.
Attribute Add Days: Select the numeric attribute that contains the number of days to add to your base date. This must be a numeric attribute (Integer, Double, or Float) from your case table. The value can be positive (to calculate future dates) or negative (to calculate past dates). Examples include "Payment_Terms_Days", "SLA_Response_Hours" (which would need to be converted to days), "Shipping_Days", or any calculated numeric field. Each case can have a different value, allowing for case-specific date calculations.
Examples
Example 1: Invoice Payment Due Dates
Scenario: A company needs to track payment due dates for invoices. Different customers have different payment terms - some pay in 30 days, others in 60 or 90 days. The payment terms are stored as a numeric attribute based on customer contracts.
Settings:
- New Attribute Name:
Payment_Due_Date - Attribute Name:
Invoice_Date - Attribute Add Days:
Customer_Payment_Terms
Output: For a case where:
- Invoice_Date = 2024-03-01
- Customer_Payment_Terms = 30
The enrichment creates:
- Payment_Due_Date = 2024-03-31
This new attribute can be used to create dashboards showing upcoming payment dues, identify overdue invoices, and analyze payment behavior patterns.
Insights: By having calculated due dates, the finance team can proactively follow up on payments, prioritize collection efforts, and accurately forecast cash flow based on expected payment dates.
Example 2: SLA Deadline Monitoring
Scenario: An IT service desk needs to track SLA deadlines for different ticket priorities. High priority tickets must be resolved within 1 day, medium within 3 days, and low within 7 days. The SLA days are stored as an attribute based on ticket priority.
Settings:
- New Attribute Name:
SLA_Resolution_Deadline - Attribute Name:
Ticket_Created_Date - Attribute Add Days:
SLA_Days_Required
Output: For a high-priority ticket:
- Ticket_Created_Date = 2024-03-15 09:00:00
- SLA_Days_Required = 1
- SLA_Resolution_Deadline = 2024-03-16 09:00:00
For a low-priority ticket:
- Ticket_Created_Date = 2024-03-15 09:00:00
- SLA_Days_Required = 7
- SLA_Resolution_Deadline = 2024-03-22 09:00:00
Insights: Service managers can now create real-time dashboards showing which tickets are approaching their SLA deadlines, enabling proactive resource allocation and preventing SLA breaches.
Example 3: Expected Delivery Date Calculation
Scenario: An e-commerce company wants to calculate expected delivery dates based on shipping method. Standard shipping adds 5 days, express adds 2 days, and overnight adds 1 day to the ship date.
Settings:
- New Attribute Name:
Expected_Delivery_Date - Attribute Name:
Order_Shipped_Date - Attribute Add Days:
Shipping_Days
Output: For an express shipment:
- Order_Shipped_Date = 2024-03-20 14:00:00
- Shipping_Days = 2
- Expected_Delivery_Date = 2024-03-22 14:00:00
This enables customer service to provide accurate delivery expectations and identify shipments that may be delayed.
Insights: Operations teams can analyze actual delivery performance against expected dates, identify carriers or routes that consistently miss expectations, and improve customer communication about delivery timelines.
Example 4: Contract Renewal Management
Scenario: A software company needs to track when customer contracts are up for renewal. Contracts have different durations - monthly (30 days), quarterly (90 days), or annual (365 days) subscriptions.
Settings:
- New Attribute Name:
Contract_Renewal_Date - Attribute Name:
Contract_Start_Date - Attribute Add Days:
Contract_Duration_Days
Output: For an annual contract:
- Contract_Start_Date = 2024-01-15
- Contract_Duration_Days = 365
- Contract_Renewal_Date = 2025-01-15
For a monthly contract:
- Contract_Start_Date = 2024-03-01
- Contract_Duration_Days = 30
- Contract_Renewal_Date = 2024-03-31
Insights: Sales teams can proactively reach out to customers before renewal dates, account managers can plan renewal negotiations in advance, and revenue forecasting becomes more accurate with clear renewal timelines.
Example 5: Manufacturing Lead Time Planning
Scenario: A manufacturing company needs to calculate expected completion dates for production orders based on standard lead times for different product types, which vary from 7 to 45 days.
Settings:
- New Attribute Name:
Expected_Completion_Date - Attribute Name:
Production_Start_Date - Attribute Add Days:
Product_Lead_Time_Days
Output: For a complex product order:
- Production_Start_Date = 2024-03-10 08:00:00
- Product_Lead_Time_Days = 21
- Expected_Completion_Date = 2024-03-31 08:00:00
Insights: Production planners can optimize scheduling, communicate realistic delivery dates to customers, and identify orders at risk of missing their target completion dates.
Output
The Add Days to a Date enrichment creates a new case attribute with the following characteristics:
Attribute Type: DateTime - The new attribute is created as a timestamp/datetime field that preserves the time component from the original date attribute.
Attribute Naming: The new attribute uses the name specified in "New Attribute Name" and appears in your case table immediately after enrichment execution.
Value Calculation: For each case, the enrichment takes the base date from "Attribute Name" and adds the number of days specified in "Attribute Add Days". The calculation preserves the original time component, so if your base date includes hours and minutes, these are maintained in the calculated date.
Null Handling: If either the base date attribute or the days-to-add attribute is null for a particular case, the new calculated date attribute will also be null for that case. This ensures data integrity and makes it easy to identify cases with missing information.
Negative Values: The enrichment supports negative values in the "Attribute Add Days" field, allowing you to calculate dates in the past. This is useful for calculating dates like "Review Required By" (which might be X days before a deadline).
Integration with Other Features:
- The new date attribute can be used immediately in filters to select cases based on calculated dates
- It can be used in other enrichments that require date inputs
- It appears in all visualizations and can be used for time-based analysis
- It can be exported with your enriched dataset
- It can be used in calculated attributes for further date manipulations
This documentation is part of the mindzie Studio process mining platform.