By Sophie Dulhunty at October 08 2018 08:50:11
Knowledge workers carry out these processes by taking into account multiple inputs (generally a wide set of unstructured data and information) to perform difficult tasks and make complex decisions among multiple possible ways of doing the work, each one implying different levels of risk and possible benefits. They are dependent on individuals and it is not possible to automate them. One example of a knowledge process is "Marketing a new product". The same steps are followed each time a new product is launched (benchmarking competitors, deciding pricing strategy, planning promotion, etc...), but it is the experience, knowledge and intuition of the people that drive the process to success.
It is extremely important to continuously improve knowledge processes, by creating an environment through which they can evolve. This can only be achieved through coordination of diverse disciplines such as knowledge management, change management, expectations management, etc... It is crucial to establish an adequate process context (the combination of technologies, procedures, people, etc... that support the processes). The process context must incorporate feedback mechanisms, change evaluation procedures, process improvement methods and techniques and must be flexible, in order to be able to incorporate enhancements in an agile but controlled way.
Diagrams : A diagram can show a process, hierarchy, or other relationships. You can use AutoShapes and arrows, the flowchart shapes with connectors (in the Lines category in PowerPoint 2007; otherwise in the Connectors category), or the SmartArt feature of 2007. Charts/Graphs : Charts (also known as graphs) visually display data, especially data showing a trend. Use only the data that supports your point, not all the data in the Excel spreadsheet where you got the data. If the data is too complex, it won't be comprehensible on a slide. What to do? Print it out and give it to the audience as a handout.
Current research in information processing deals with programs that enable a computer to understand written or spoken information and to produce summaries, answer specific questions, or redistribute information to users interested in specific areas of this information. Essential to such programs is the ability of the system to generate grammatically correct sentences and to establish linkages between words, ideas, and associations with other ideas. Research has shown that whereas the logic of language structure-its syntax-submits to programming, the problem of meaning, or semantics, lies far deeper, in the direction of true AI.