As processes become more intelligent, we will likely like to measure the level of intelligence http://jimsinur.blogspot.com/2013/05/how-smart-is-your-business-only-as_9.html This will give organizations an idea where they are in a continuum in trying to becoming a smarter business over time. This posting will cover the first "A" portion "ISAA" http://jimsinur.blogspot.com/2013/05/should-we-measure-how-smart-processes.html
I propose the following five levels of process agility that build on each other:
Where process/logic volatility can be planned ahead of time and represented by external data, explicit parameters can be leveraged. The parameters are usually bound into the logic at the very last second allowing for up to the last second change(explicit). This allows for a basic level of agility and can be made handed over to business professionals for change (usually via forms/screens).
Where process/logic volatility can be planned ahead of time and be represented by decision tables, decision trees, visual logic flows or linguistics form, business rules can be leveraged. The rules are bound into the logic at the very last second. In some instances the rules can be used to not only induce, but to deduce logic. This is a higher level of intelligence and agility that generally leverages a business friendly development environment.
Dynamic Sequencing of Services(logic):
While adding agility within a fixed process model is a good start, not all processes paths can be modeled. In this situation, sequences work and process activity can be dynamically arranged and completed. While common patterns can be identified and modeled over time, this approach is aimed at variable work sequences. This can be accomplished by aggregating fixed process snippets (small -modeled sub-processes) guided by rules or case management guided by milestones(mini completion points).
In completely unstructured processes that are milestone driven, changes in priorities can be accomplished by changing the milestones, in flight. This approach is particularly useful for cases that have emerging new outcomes to handle where the work sequences are highly variable. This is often leveraged by adaptable case management technologies.
The ultimate in agility is where processes reconfigure themselves around new set of goals or goal weightings. This can be accomplished by having goal models that can change through a business friendly development environment or the dynamic/real time setting of goals/weightings leveraging analytics. These kind of processes generally are getting real time feedback from the Internet of things or other real time sensors.
There are definite levels of change intelligence that processes can enable. We
will need learn
to utilize various levels of change agility over the coming years