By Laura Cleland at December 07 2018 02:41:37
It is usual that knowledge processes take the form of projects to manage their execution. If the output of the process is a unique product, managing work as a project will result in obvious advantages. There are certain guidelines that can help an organization willing to improve their knowledge processes: Provide process description on how to approach work Try to figure out the best way to carry out a knowledge process, by making the best practices existing in your organization (or in your industry) explicit. Publish process definitions in a format that is easy to consult and understand. Provide tools that facilitate and standardize work Decide which tools are best to help knowledge workers carry out their work. Involving all affected knowledge workers in the process of deciding which tools will be used is very convenient, in order to obtain user buy in.
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.
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.
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.