The Industrial Revolution brought about mass production of parts and products. The concept behind mass production is: break the job into a series of well defined components (interchangeable parts), and set up to produce those parts in large quantities to get economy of scale. Millions of identical parts can bring the price down of a completed product. The cost of setting up a factory is high, but is recouped through small savings multiplied by many instances.
Fredrick Winslow Taylor applied these mass production ideas to work and called it “Scientific Management“. He performed time and motion studies to determine exactly the most efficient way to perform a particular piece of work, and got workers to do the same thing over and over very repeatably. Again, economy from large runs of identical work.
Workflow and BPM (and software applications in general) comes from this school of Scientific Management. The idea is for process discovery (time and motion studies) to determine the best and most efficient way to do one specific process, and then implement a program that enforces that process, which recoups costs over a number of instances.
Scientific management can only be applied to processes which are very repeatable / predictable. A process or job that is done only once, or is unpredictable, would never see any benefit. Clearly the up-front analysis cost is high, and can only be recovered if the resulting process is repeated a number of times. This is the same as setting up a factory to produce a single unit: it would be more effective to simply custom build the single unit, because you would not incur the overhead of setting up the factory.
This leads to an interesting “blindness”: As people analyze their workplace with scientific management, they look for predictable / repeatable processes to improve. Non repeated or non predictable activities are often ignoredfor the same reason that you would never consider building a factory for a one-off custom job. Human activities that can not be analyzed with scientific management are often called “overhead” or “putting out fires”.
These kinds of activities are not even considered “work” to some people. Does an executive do “work”? Many would say that the executive spends all their time making decisions, not doing work. It is not that people don’t think that making decisions takes effort, it is just that that kind of effort does not fall into the category of “work”. OK, I have stretched the idea a bit far. We do call this “Knowledge Work” and that is a category of work, but I have found that there is a bias among people who specialize in “work processes” to be blind to considering knowledge work to be a work process, and thus falls outside of the category of work.
Since mass production, we have seen a lot of movement to “mass customization” and “lean production”. Toyota has shown that small lot sizes and the ability to change the production quickly and often can be very effective. The “Just In Time” movement is a rejection of mass delivery and mass production in favor of producing or delivering just what you need for the immediate time period.For this to work, the set-up costs have to be suitably modest, so that you can pay for the setup with a smaller run.
I believe it is fair to say that current process technology (Workflow and BPM) is based on mass production Taylorist Scientific Management principles. This is not bad. It will work well for processes which are predictable and repeatable, and companies today are seeing significant payback from these investments.
However, there is a lot of work which is not predictable, and not repeated. For example the doctor’s job of diagnosing a rare disease; the negotiation of a treaty or a corporate merger; the investigation of a crime; or the prosecution of a court case. These are jobs that can not predicted at the time the job is started. It is not simply that we have not gone to the trouble of mapping the process, but the process is not knowable, because the details that effect the course are not yet discovered. A “super process” which encompasses all possible outcomes, and uses branches at the times that the details become clear, is not possible because of the “butterfly effect”: the number of different possible effecting factors is so huge that it would never be economically feasible to track them all. For the example of the doctor, the number of treatments is always expanding, and information about the success of treatment is always expanding, that the doctor’s own experience and intuiting becomes critically important, and could never be externalized as a process. We call this “Knowledge Work” and it is distinct from “Routine Work” which is predictable and repeatable.
All hope is not lost. There are techniques which organizations can use to support knowledge work. Those techniques are a radical departure from process technology today. This non-repeated, non-predictable work can not be effectively analyzed with Scientific Management. It will not be effectively supported with technology based on Scientific Management. Knowledge work requires an approach that does not assume that there is one optimal process, but instead assumes that every case will have a different process. Instead of “building a factory” for identical processes, the use will be empowered to extend and adapt the process as a normal part of work in small lots. Processes are designed “just in time” when they are needed, and not before hand.
This is the concept behind Adaptive Case Management. It is not simply a new kind of BPM or an extension of BPM. It comes from a completely different theory of supporting work. It is a “Non-Taylorist” process technology.