By Sophie Dulhunty at September 27 2018 15:14:31
Tables : When your data doesn't clearly show a trend, use a table. You may have this data in Excel, and can even link to the Excel file. Quotations : Quotes are very powerful when they come from authorities or well-known individuals. In a persuasive presentation, you can use testimonials from other customers, for example. Stories : Stories are powerful when they support your message. They can be personal, related to current events, examples from other customers, and so on. They can be full-blown situations, or simple examples. Collect stories as you hear them and keep them in a file for use later.
According to the U.S. Department of Labor, the average salary for technical writers is $60,380. Freelance technical writers can make from $30 to $70 per hour. The field of technical writing is like a golden city. It's filled with wealth, rewards and opportunities. After learning technical writing you can branch out into business writing, marketing writing and communications writing. All of these can become additional income streams. But to succeed you must learn how to market yourself to clients. You have to prove to them that you are an invaluable asset. That's where ProTech - Your Fast Track to Becoming a Successful Technical Writer can help. It's a technical writing course that does two equally important things :
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.
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.
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.
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.