By Olivia Giles at October 03 2018 20:58:00
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).
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.
In the last few years a lot has been written about Business Process Management, and about technologies supporting it such as BPMS, SOAP and Web Services. Most of these theories, tools and techniques refer to processes of a highly structured nature. Typically, BPM theorists and practitioners have focused on highly structured processes, like back-office processes of industrial or administrative nature. These processes are highly standardized and repeatable, produce a consistent output and are likely to be automated in part or end-to-end (STP).
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.