Data Rule Definition

This page is accessed via Logistics Network Modeling > Power Data > Data Rule Definition.

Data rules provide a way to define a change to an existing object in database without copying all the data. Data rules are applied only "in-memory" in a Scenario plan. They do not impact production. Data rule definitions allow you to make modifications to any data involved in a scenario planner. For example, activate/inactivate a rate offering or set of rate offerings.

Data rules have the following components:

• Data Rule Definition: allows you to specify a template or high level definition for a data rule. This allows you to specify what should change.
• Data Rule Instance: allows you to specify what to change (value) and how to apply the new or changed value (using the operand).
• Scenario Rule: This is where the data rule instances are attached to scenarios. In the Modeling Scenario, add a new scenario rule association using the Modeling Scenario Data Rule grid. Here you can specify details such as sequence to run and objects to modify.

Adding a Column Data Rule Definition

1. Enter a Data Rule Definition ID.
2. Optionally, enter a Description.
3. Optionally, enter a Rule Group. A rule group is an optional way to group rules, which can be used to retrieve records in the finder. There is no other significance.
4. Select a Rule Type of Columns.
5. Enter a Table Name. This will filter the columns available to those that are in the table specified.
6. If you select the table name and select the Include All Columns check box, all columns corresponding to the table will be populated in the Data Rule Parameters grid. You can delete any you do not want. Without selecting this check box, you can add as many columns as you wish, but one by one.
7. Enter the Data Rule Parameters:
   1. Enter the Column Name to define the columns of the table, (specified in the Table Name field above) for the values that should be manipulated. Select as many as you need.
   2. Enter a Parameter Name. This can be a more user friendly term. For example, if the column is “Source_Location_Gid”, you could use enter a parameter name such as “Source Location Change”.
   3. You can enter a Description for the data rule parameter.
   4. Enter a Fixed Value. The value fields are populated based on the operand.
      
      The value will be used during the creation of data rule instance to set the value for the column change. On the data rule instance, for a "Clear" operand, a value is not expected so the Value field is hidden when "Clear" operand is selected. A formula is associated with each operand and is defined in the LNM_OPERAND table. For example, an operand INCREASE BY DAYS is available when the column type is a DATE/TIME and the expected value is a number. The fixed values should be provided in comma separated format.
   5. Click Save.
   6. Enter any additional parameters needed. Click Save after each.
8. Click Finished.

Adding a Java Data Rule Definition

1. Enter a Data Rule Definition ID.
2. Optionally, enter a Description.
3. Optionally, enter a Rule Group. A rule group is an optional way to group rules, which can be used to retrieve records in the finder. There is no other significance.
4. Select a Rule Type of Java.
5. Select a Java Plugin ID.
6. Enter the Data Rule Parameters:
   1. The Column Names are defined by the java plugin ID selected above.
   2. Optionally, edit the default Parameter Name. This can be a more user friendly term.
   3. Optionally, edit the default Description for the data rule parameter.
   4. Select Mandatory to require the parameter.
   5. Enter a Default Value. If you do not specify any value this value is used.
   6. Enter a Fixed Value.
      
      The value will be used during the creation of data rule instance to set the value for the column change. On the data rule instance, the valid operands are INCREASE BY DAYS and DECREASE BY DAYS with the column type is a DATE/TIME. The fixed values should be provided in comma separated format.
   7. Click Save.
   8. Enter any additional parameters needed. Click Save after each entry.
7. Click Finished.

Using the UPDATE ORDER RELEASE DATE Java Plugin

OTM comes with a java plugin with the ID of UPDATE ORDER RELEASE DATE. The purpose of this plugin is to update one order release date based on another date of the order release.

To use this plugin,

1. Select a Rule Type of Java.
2. Enter the Java Plugin ID of UPDATE ORDER RELEASE DATE.
   
   The Data Rule Parameters grid populates with data based on the plugin.
3. Keep the Column Name to define the columns as defined in the java plugin of UPDATE ORDER RELEASE DATE. These are:
   1. BASE_COLUMN: Optional. The default value is LATE_DELIVERY_DATE and the fixed values are EARLY_PICKUP_DATE, EARLY_DELIVERY_DATE, LATE_PICKUP_DATE, LATE_DELIVERY_DATE.
   2. CHANGE_TIME: Number of days. Valid operands are "INCREASE BY DAYS" and "DECREASE BY DAYS". This is required.
   3. UPDATE_COLUMN: Valid values are EARLY_PICKUP_DATE, EARLY_DELIVERY_DATE, LATE_PICKUP_DATE, LATE_DELIVERY_DATE

Using the UPDATE ORDER RELEASE DATE Java Plugin

You can use the java plugin UPDATE COMMITMENT ALLOCATION to change the commitment percentage for a particular service provider.

To use this plugin,

1. Select a Rule Type of Java.
2. Enter the Java Plugin ID of UPDATE COMMITMENT ALLOCATION.
   
   The Data Rule Parameters grid populates with data based on the plugin.
3. Keep the Column Name to define the columns as defined in the java plugin of UPDATE COMMITMENT ALLOCATION. These are:
   1. SERVPROV1, SERVPROV2, and SERVPROV3: Valid value is SET.
   2. COMMIT_PERC1, COMMIT_PERC2, and COMMIT_PERC3: Valid operands are INCREASE, DECREASE, and SET. This assumes that the service provider specified in the SERVICE_PROV parameter is matched a service provider in Commitment Allocation Usage.
   • INCREASE adds the value to the existing commitment allocation percentage.
   • DECREASE subtracts the value from existing commitment allocation percentage. 
   • SET: Use to override existing commitment percentage.