By Sophie Dulhunty at September 29 2018 17:57:31
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.
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.
They are more difficult to implement through discipline than administrative human-centric processes (although some discipline is needed). It is better to focus on obtaining buy-in from the people affected by the processes through early involvement, communication and expectations management. It is a known fact that knowledge workers are reluctant to change their habits. Some say knowledge workers don't like following procedures because they feel it limits their creativity; but most of the time they will be happy to follow a procedure as long as they see value in it, perceiving that it helps them work better and produce a better process output.
How to create a flowchart When you're working on a complex project, creating the flowchart itself may be a time-consuming task. Here are six simple steps you can follow to create even complex flowcharts: Start by defining the end result of the process or project. The end result could be anything such as completing a user manual, writing a complex software process, installing a new part, or performing a test. List the various steps involved to achieve the end result. This will take some research. In complex processes, each step could have a series of sub steps. The steps involved to create a user manual could be: a. Meet with SME ; b. Research existing documentation ; c. Videotape the procedure ; d. Take photographs ; e. Create illustrations ; f. Develop the user guide ; g. Test the user guide ; h. Make changes/adjustments ; i. Deliver final product.
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.
Process definitions are high level descriptions instead of rigid workflows : Processes can only be defined up to a certain level of detail, and it is difficult to provide low level work instructions or to automate decisions. Because they cannot be formalised in detail, process simulation is rarely possible. Decisions are highly subjective and too complex to be expressed in a formal language, as they are taken based on intuition and not on rigid business rules.