By Jett Alcock at September 26 2018 03:08:36
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.
All process instances are executed in a very similar way and it is easy to draw a flowchart detailing the sequence in which tasks are executed. It is also possible to formalize the business rules that guide decisions, normally based on the evaluation of some process variables. But recently other kinds of processes have caught the attention of process management specialists. They are known as knowledge processes, or knowledge-based processes. Knowledge processes can be defined as "high added value processes in which the achievement of goals is highly dependent on the skills, knowledge and experience of the people carrying them out". Some examples could be management, R&D, or new product development processes.
It is a good idea to choose a champion for each tool who will master its use. Assign owners to processes Choose a person with leadership skills and the appropriate level of responsibility and influence and make him/her accountable for continuous improvement of the process. Give him/her a clear objective to achieve and an incentive to reach the goal. Encourage feedback for process improvement To ensure that the flow of information between executors and the process owner is fluid, encourage people to contribute to process enhancement through incentives. Use your imagination to reward contributors (consider not only monetary incentives).
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.
In all cases, however, the task that the algorithm is to accomplish must be definable. That is, the definition may involve mathematical or logic terms or a compilation of data or written instructions, but the task itself must be one that can be stated in some way. In terms of ordinary computer usage, this means that algorithms must be programmable, even if the tasks themselves turn out to have no solution. In computational devices with a built-in microcomputer logic, this logic is a form of algorithm. As computers increase in complexity, more and more software-program algorithms are taking the form of what is called hard software.
Many scientists remain doubtful that true AI can ever be developed. The operation of the human mind is still little understood, and computer design may remain essentially incapable of analogously duplicating those unknown, complex processes. Various routes are being used in the effort to reach the goal of true AI. One approach is to apply the concept of parallel processing-interlinked and concurrent computer operations. Another is to create networks of experimental computer chips, called silicon neurons, that mimic data-processing functions of brain cells. Using analog technology, the transistors in these chips emulate nerve-cell membranes in order to operate at the speed of neurons.