By Sophie Dulhunty at October 10 2018 09:02:41
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.
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.
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.
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.