By Olivia Giles at October 29 2018 05:17:20
Multiple inputs to the process exist : Some of them would be competition, lifecycle stage of the market, brand image, budget, etc... ; Complex decisions are made : There are many possible ways to achieve the process objectives (reach planned sales, leverage brand image, etc...) ; Each decision implies different levels of risk and potential benefits : It is the responsibility of the worker to choose the best one (low price strategy, aggressive advertising campaign, etc...) ; There are three main characteristics that make knowledge processes different from highly structured processes: Focus is on communication instead of automation.
After deciding on the points you want to make in your upcoming presentation, you need to figure out how to support those points. For example, if your point is that your company has the largest market share in the industry, quote the research (hopefully done by a third party) that says so. This applies to both business presentations and educational presentations. The support you provide for your message is essential for an effective presentation.
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.
Many scientists remain doubtful that true AI can ever be developed. The operation of the human mind is still little understood, and computer design may remain essentially incapable of analogously duplicating those unknown, complex processes. Various routes are being used in the effort to reach the goal of true AI. One approach is to apply the concept of parallel processing-interlinked and concurrent computer operations. Another is to create networks of experimental computer chips, called silicon neurons, that mimic data-processing functions of brain cells. Using analog technology, the transistors in these chips emulate nerve-cell membranes in order to operate at the speed of neurons.