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By Laura Cleland at November 05 2018 16:34:17

If the process is instantiated frequently and the instances are homegeneous, it is possible to create great process models that dramatically increase the efficiency of the process. The best way to ensure process improvement is to generate an environment in which people are motivated, enthusiastic and passionate about process management. Most of the time, knowledge processes are collaborative. By performing a process collaboratively it is possible that each task is carried out by the most specialised, experienced and knowledgeable worker in that specific area. Having a net of relations within the organization is a very important asset for people executing knowledge processes.

What's a flowchart? A flowchart can be defined as a graphical representation of a sequence of operations or steps. In other words, it's an illustration of the various steps involved in a project or process. Typically, a flowchart consists of a number of boxes, arrows, and text that combine to form a sequence. Why create a flowchart? The purpose of a flowchart is to show the various steps of a process in a snapshot. By looking at the flowchart, the viewer should be able to identify the various steps involved in the process.

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The key to process improvement is to clearly communicate process definitions (the way in which the company wants the processes to be carried out) to the people in charge of their execution (through training, process descriptions publication, etc...). The better process participants understand the process definition, the higher the probability that the process is carried out according to it. They are better implemented through obtaining buy-in than through imposing directives.

In medicine, programs have been developed that analyze the disease symptoms, medical history, and laboratory test results of a patient, and then suggest a diagnosis to the physician. The diagnostic program is an example of so-called expert systems-programs designed to perform tasks in specialized areas as a human would. Expert systems take computers a step beyond straightforward programming, being based on a technique called rule-based inference, in which preestablished rule systems are used to process the data. Despite their sophistication, systems still do not approach the complexity of true intelligent thought.

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