By Summer Gatenby at December 05 2018 02:11:32
Process definitions are high level descriptions instead of rigid workflows : Processes can only be defined up to a certain level of detail, and it is difficult to provide low level work instructions or to automate decisions. Because they cannot be formalised in detail, process simulation is rarely possible. Decisions are highly subjective and too complex to be expressed in a formal language, as they are taken based on intuition and not on rigid business rules.
Only if you know what your retirement plan is all about, you can say that it is exactly the right plan for you. You also know precisely when you need to adjust it. Everyone needs one if they want to have a nice future. One should know how it works and what benefits you will get in the end. You should ask yourself these questions because they are too important not to be answered. Most of the employers these days offer some sort of retirement plan for their staff, this also means that someone is or some people are responsible for the management of these plans. There are a lot of rules that need to be followed and someone needs to keep the oversight.
All process instances are executed in a very similar way and it is easy to draw a flowchart detailing the sequence in which tasks are executed. It is also possible to formalize the business rules that guide decisions, normally based on the evaluation of some process variables. But recently other kinds of processes have caught the attention of process management specialists. They are known as knowledge processes, or knowledge-based processes. Knowledge processes can be defined as "high added value processes in which the achievement of goals is highly dependent on the skills, knowledge and experience of the people carrying them out". Some examples could be management, R&D, or new product development processes.
In all cases, however, the task that the algorithm is to accomplish must be definable. That is, the definition may involve mathematical or logic terms or a compilation of data or written instructions, but the task itself must be one that can be stated in some way. In terms of ordinary computer usage, this means that algorithms must be programmable, even if the tasks themselves turn out to have no solution. In computational devices with a built-in microcomputer logic, this logic is a form of algorithm. As computers increase in complexity, more and more software-program algorithms are taking the form of what is called hard software.
The possibility of developing some such artifact has intrigued human beings since ancient times. With the growth of modern science, the search for AI has taken two major directions: psychological and physiological research into the nature of human thought, and the technological development of increasingly sophisticated computing systems. In the latter sense, the term AI has been applied to computer systems and programs capable of performing tasks more complex than straightforward programming, although still far from the realm of actual thought. The most important fields of research in this area are information processing, pattern recognition, game-playing computers, and applied fields such as medical diagnosis.
They are more difficult to implement through discipline than administrative human-centric processes (although some discipline is needed). It is better to focus on obtaining buy-in from the people affected by the processes through early involvement, communication and expectations management. It is a known fact that knowledge workers are reluctant to change their habits. Some say knowledge workers don't like following procedures because they feel it limits their creativity; but most of the time they will be happy to follow a procedure as long as they see value in it, perceiving that it helps them work better and produce a better process output.