Configuration requirements for optimization

WebSphere Lombardi Edition 7.2 > Simulating and optimizing processes

Configuration requirements for optimization

Use historical data captured by Lombardi Performance Data Warehouse, the Optimizer pinpoints areas in your process models where you can make design changes to help streamline execution and, thus, improve performance. If you are planning to deploy one or more processes and you want to capture the performance data that will enable you to optimize those processes, you must complete the following tasks in the order shown:

Task Description See

Ensure autotracking is enabled With autotracking enabled, Lombardi captures data that automatically includes tracking points at the entry and exit of each item in a process definition (such as activities and gateways). This data enables the Optimizer to analyze run-time task duration as well as compare how a process performs when it follows one path versus another. Tracking performance data for the Optimizer
Specify the business data (variables) to track To capture the value of business data at every point as it flows through the process, specify the variables to track. Doing so ensures that you get the most value out of your process analysis. For example, knowing which of your suppliers is causing the most exceptions in your quality assurance process is valuable information. Tracking performance data for the Optimizer
Send tracking definitions The data is captured to the Performance Data Warehouse only if you send tracking definitions as instructed in the following procedures. Tracking performance data for the Optimizer
Create historical analysis scenarios After your processes have been running for a while and you want to analyze the collected data using the Optimizer, create historical scenarios to specify the process models to include, the business data (variables) by which to filter the analysis results, and whether to include only completed or also currently running process instances. The advantage of historical scenarios is that they enable you to group and compare performance for different sets of processes. Create historical analysis scenarios

Optional configuration for optimization

Lombardi provides the following configuration options for the Optimizer, which may prove useful or helpful in your environment:

Option Description See
Generate historical data You can set up a Simulation Profile and generate historical data based on that profile if you want to run historical analyses based on data that you generate. This option is helpful if you want to simulate your processes using business data versus the timing data that is normally available with simulations. Generating historical data
Analyze data from Performance Data Warehouses in runtime environments You can configure Lombardi to enable the Optimizer to performs its analysis on the data from Performance Data Warehouses in runtime environments. This option is helpful if you want to be able to select a Performance Data Warehouse other than the local warehouser when running an analysis. Analyzing data from Performance Data Warehouses in runtime environments

Tracking performance data for the Optimizer

Create historical analysis scenarios

Analyzing data from Performance Data Warehouses in runtime environments

Generating historical data

Parent topic: Simulating and optimizing processes

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Task	Description	See
Ensure autotracking is enabled	With autotracking enabled, Lombardi captures data that automatically includes tracking points at the entry and exit of each item in a process definition (such as activities and gateways). This data enables the Optimizer to analyze run-time task duration as well as compare how a process performs when it follows one path versus another.	Tracking performance data for the Optimizer
Specify the business data (variables) to track	To capture the value of business data at every point as it flows through the process, specify the variables to track. Doing so ensures that you get the most value out of your process analysis. For example, knowing which of your suppliers is causing the most exceptions in your quality assurance process is valuable information.	Tracking performance data for the Optimizer
Send tracking definitions	The data is captured to the Performance Data Warehouse only if you send tracking definitions as instructed in the following procedures.	Tracking performance data for the Optimizer
Create historical analysis scenarios	After your processes have been running for a while and you want to analyze the collected data using the Optimizer, create historical scenarios to specify the process models to include, the business data (variables) by which to filter the analysis results, and whether to include only completed or also currently running process instances. The advantage of historical scenarios is that they enable you to group and compare performance for different sets of processes.	Create historical analysis scenarios

Option	Description	See
Generate historical data	You can set up a Simulation Profile and generate historical data based on that profile if you want to run historical analyses based on data that you generate. This option is helpful if you want to simulate your processes using business data versus the timing data that is normally available with simulations.	Generating historical data
Analyze data from Performance Data Warehouses in runtime environments	You can configure Lombardi to enable the Optimizer to performs its analysis on the data from Performance Data Warehouses in runtime environments. This option is helpful if you want to be able to select a Performance Data Warehouse other than the local warehouser when running an analysis.	Analyzing data from Performance Data Warehouses in runtime environments