Best practices in work allocation

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Best practices in work allocation

Overview

Work allocation is the fifth step of the Process automation Wizard where Performers are defined for each Activity of your Process. Performers are the users that have the qualities to be assigned to activities. Each Task created for end user interaction requires definition that will allow Bizagi to allocate the correct users within your organization.

 

Bizagi automatically evaluates the allocation rules defined for each Task and selects one or more users that meet the given conditions from the user's list. Only these users will have access to work on the Activity allocated to them.

 

This section provides some guidelines to properly define these allocations rules.

 

Control the number of users that can be allocated

Allocating a single task to a hundred of thousands of users is a bad practice.

 

Use Everyone assignation method only when needed

When defining the work allocation for your different Activities, avoid using the Everyone assignment method when possible. Using this feature will involve a large group of users and therefore it will demand more resources and create a bigger log. Therefore, it should be only used when strictly required, and ensuring there is use of appropriate filters (i.e., by roles and skills, positions).

Options:

For instance, you may want to evaluate if certain Activities can use the reassign feature from the Activity instead of having assignation available for more than one user from the very beginning.

 

Avoid allocating tasks that might assign to many users (more than 10)

In the Assignation Method Everyone, allocations are given to all users with the characteristics indicated.

This works fine in development environment, where there are 5 to 10 users created, and these allocations will turn to one or two users. However, when a process is deployed to production, projects may have thousands of users. Allocating an activity to thousands of users is a bad practice, and it will increase the time needed to run resulting in performance problems.


Last Updated 1/6/2022 4:24:51 PM