To understand the future of processes, you must dig a little deeper than many people do.
Process thinking goes back well over a 100 years, to the origin of modern iron and automobile production. The raw materials and finished goods of such manufacturing and production processes are literally spatial – 3-dimensional. What can you do to significantly improve productivity in a 3-dimensional world? The answer these days is simple: You build robots. Robotization has literally changed the world during the past 30-40 years.
Rather than manufacturing and production processes, however, the world is now increasingly focused on white-collar and digital processes. What 3-dimensional presence do the raw materials and finished goods of these processes have?
Well, exactly none. The raw materials and finished goods of these processes aren’t physical and simply have no spatial presence whatsoever (except maybe for paper artifacts). Robots (at least physical ones) aren’t an option. That fact of life makes a huge difference in how you have to think about automation for such processes.
Instead, the raw materials and finished goods of such processes are all about your operational business knowledge – your intellectual capital – and your capacity to express and apply it. That capability, in turn, depends directly on your business terminology and business language. For white-collar processes you have no choice – the world is semantic. So you must deal with the subject matter semantically.
That takes us in a very different direction than most professionals currently foresee. For one thing it takes us toward natural language and away from diagrams-for-everything. That’s a huge shift in mindset. Imagine having a business conversation with your smart phone about gaps and ambiguities in business policies and in the meanings of the vocabulary you use to talk about subject matter knowledge. Don’t think that’s possible? Have you watched your kids talking to their smart phones lately?
Sooner or later businesses will realize that operational business knowledge differentiates their product/services and enables their ever-more-automated processes to function. Capturing, managing and re-using that intellectual capital puts a premium on structured business vocabulary (concept models) and on business rules expressed in structured natural language. Those business rules are the only way you have to ensure quality from white-collar and digital processes.
Read more on this topic:
Are Processes and BPM Relevant in the Digital Economy? http://www.brsolutions.com/2015/10/19/are-processes-and-bpm-relevant-in-the-digital-economy/
Measuring Quality and Defects in the Knowledge Economy: http://www.brsolutions.com/2015/10/27/measuring-quality-and-defects-in-the-knowledge-economy/
Quality and Tolerances in the Knowledge Economy: http://www.brsolutions.com/2015/10/29/quality-and-tolerances-in-the-knowledge-economy/
I was reading a fascinating article in The Economist about how robots, including military drones and driverless automobiles, increasingly need ethical guidance. What does that have to do with business rules, you ask? Read on …In the next five years, software systems will begin to appear that bypass programming going more or less straight from regulations, contracts, agreements, deals, certifications, warranties, etc. (written in English or other natural language) to executing code. Think about the economics of the equation! If for no other reason (and there are many others), you’ll quickly see the why a snowballing migration to such platforms is inevitable. And these tools will do the same for business rules based on business policies.I said more or ‘more or less’ above because the tool will have to make certain assumptions about the meaning of what it ‘reads’. For example, if I say, “a person must not be married to more than one other person” most of us would probably assume that means “at a given point in time”. But automated tools could easily be held responsible for making the wrong interpretation. It should therefore err on the safe side, and at the very least, log all its reasoning.That’s where the article comes in. Concerning robots that make liability-laden decisions, it contends that principles are needed …
“… to determine whether the designer, the programmer, the manufacturer or the operator is at fault if an autonomous drone strike goes wrong or a driverless car had an accident. In order to allocate responsibility, autonomous systems must keep detailed logs so that they can explain the reasoning behind their decisions when necessary.” [emphasis added]
That explanation better be in a form that humans (and lawyers too) can actually read. That means structured natural language.The article went on to make the following astute observation …
“This has implications for system design: it may, for example, rule out the use of artificial neural networks … decision-making systems that learn from example rather than obeying predefined rules.”
Right! Where there is social liability, there will always be natural language.P.S. To vendors: If your meaning of ‘business rule’ doesn’t compel you toward this debate, then you’re simply not really doing ‘business rules’(!).
 “Morals and the Machine”, The Economist, June 2, 2012, p. 15
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