Water planning requires management and analysis of a wide range of interdisciplinary data, often from multiple sources with varying formats and quality. Raw data has little value or worth until it has been processed, analyzed, and organized to become useful information. Knowledge is created when this information is processed to develop and enhance the understanding of a situation or a problem. It is this knowledge that can reduce the risk of undesirable consequences of a decision.
Information management is a core competency area for WRIME. We have developed a unique approach to cost-effective information management, which consists of:
- User- centric design instead of feature-centric design;
- Early user involvement and feedback;
- Flexible, expandable, and modular designs; and
- User friendliness.
Our professional staff includes computer scientists, database specialists, and application developers, supported by subject matter experts in different fields of water resources.
The first step in information management projects is to undertake a usability analysis to collect information on the end-user requirements. The purpose is to understand how users perform their jobs, determine what data they currently use and analyze, establish what capabilities they would like to have to improve the quality of their work, and define what they would like to be able to do in the future. This helps our software/database designers understand the frame of reference of the end users and minimizes the conventional design pitfalls.
At WRIME we have developed a cost-effective approach to the software design process, and can assist your in-house development team or act as an outsource software design team. We apply systems evaluation techniques that focus on the end user of the information and on the decisions and actions that the information must ultimately support. This emphasis on the users and decisions ensures that our systems have a high degree of user support and will be implemented and used.
Our design approach results in user friendly systems that transform data into knowledge, produce understandable results, and provide timely answers to important questions. |
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