Process Management Analytics

[EricSchles]

For a while I've been kicking around the idea of a process management analytics platform. The goal of this project would be to create a general purpose tool for process management analytics in general. The system would be general purpose enough while allowing for customization in specific.

Here are the explicit assumptions that all process management systems require:

1. discrete components for types of tasks that are recorded when they are completed
2. IDs for each ticket or claim
3. timestamps for when a ticket or claim moved from work queue to work queue

Using these invariants we can model process management:

Using Probabilistic Graphical Models:

• create shortest paths to determine which parts of the process are working efficiently
• create longest paths to determine which parts of the process aren't working well
• predict which paths are most likely to be taken after each subprocess

Using Collaborative Filtering:

• parameterizing ticket or claim information as taste information allows for clustering of ticket or claim information into categories so that we can classify problem tickets

K-Nearest-Neighbor Paths:

• Clustering paths to understand how work is accomplished and to understand average time to completion, based on certain parameters