By Olivia Giles at October 30 2018 11:54:10
In the last years some organizations have emerged with the aim of creating professional communities around specific disciplines such as Software Development (SEI, ESI, etc...), Project Management (PMI), Business Process Management (BPMI), IT Service Management (ITSMF), etc... One of the objectives of these groups is to develop a body of knowledge that compiles the discipline's best practices in the form of reference frameworks, methodologies and maturity models. These assets should be considered by any organization interested in knowledge process management.
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.
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.
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.