The Internet of Things and 'The Process of Everything' Introduces More Complexity
We are fast heading to more inclusive processes — processes that have to be more aware, that must make complex decisions, and that must be able to act both proactively and re-actively. This puts pressure on processes to handle new forms of signals, orchestrations, and participation. To do this in the near future, processes and cases will have to manage across a number of different styles of process actions. I have identified seven so far.
Processes will need to interact with the fastest-growing source of signals and actions — machine-to-machine. This will allow processes to interact more closely with the growing pool of machines (which include devices, controls, sensors, and chips). In addition, there are interacting sub-processes and services in each of these machines. These machines will contain a certain amount of intelligence and data aggregated at a process level to allow for greater organizational and business leverage.
For decades, processes have been heavily involved with system interactions, both inside and surrounding various forms of application integration, but this is now expanding to systems of systems and emergent behavior. Processes will have to deal with these morphing combinations and interactions. Again these system interactions will provide data and aggregated intelligence for leverage.
Processes / cases have been expanding their forms of human interactions around knowledge-heavy tasks. As process technology tries to mimic and support the way humans interact to support organizational events, this will be a growing sector of process activity, as evidenced by the interest in adaptive and emergent case management. Processes will take on better support for these forms of human communications and problem solving.
Some might consider M2M and M/S interactions to be one and the same. After all, one could make the argument that a system is just another machine or that a machine is carrying out the work of a system. However, I consider the set of Machine-to-System interactions to be unique: while the language of Machine-to-System interaction might be the same as that for Machine-to-Machine, the logic surrounding decisions and actions in machines is, so far, more brittle and fixed. This may change over time with the advent of true machine learning, but for now these are different kinds of interactions and separate entities. Processes will have to deal with managing these Machine-to-System interactions to achieve goals.
How humans interact with machines has been a challenge for over a hundred years, but intelligence and process is now being added to the mix, changing this relationship forever. Ergonomics, pre-built configurations, sequences, and machine learning are all influencing these relationships. Processes will have to deal with the outcomes of these interactions and become embedded in these interactions.
The study of human and system interactions has become a great mix of art and science. Semiotics comes from art, and actions and constraints come from the science of systems. Process technology has usually done well in coordinating this area, but again this relationship is changing as role and skill-based contexts emerge as an expected factor to consider in these interactions.
7. Complex Hybrids
The obvious hand grenade under the door is what the various combinations demand from process management and the technologies that support processes. This is a complexity that organizations and process vendors will have to face and learn how to manage. We will see better practice patterns emerge and spread quickly, to the advantage of all parties — process participants, process managers, and stakeholders.
While process can exist in forms of master task control, as a part of an overall end-to-end process, or as an actual task snippet of activity, here I have focused on master task control and orchestration. In future posts I will discuss other forms of control and communication.
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