In: Proceedings of HCI International 2007 1 UFuRT: A Work-Centered Framework and Process for Design and Evaluation of Information Systems Jiajie Zhang 1 , Keith A. Butler 2 1 University of Texas at Houston, 7000 Fannin, Houston, Texas 77030, USA 2 Microsoft One Microsoft Way, Redmond, WA, 98052, USA Jiajie.Zhang@uth.tmc.edu; kebutler@microsoft.com 1. Introduction A current and significant challenge in the design and implementation of information systems (IS) is to deal with the high failure rate of IS projects. A large number of IS projects fail. Most of these failures are not due to flawed technology, but rather due to the lack of systematic considerations of human and other non-technology issues in the design and implementation processes. In other words, designing and implementing IS is not so much an IT project as a human project about human-centered computing such as human-computer interaction, workflow, organizational change, and process reengineering. To address the high failure rate, we need a process that would increase efficiency and productivity, increase ease of use and ease of learning, increase user adoption, retention, and satisfaction, and decrease human errors, decrease development time and cost, and decrease support and training cost. In this paper we present a work-centered process called UFuRT for the design and evaluation of information systems. 2. UFuRT – A Conceptual Framework UFuRT (User, Function, Representation, and Task analyses) is a conceptual framework and a process for the design and evaluation of work-centered products. It is based on the theory of distributed cognition and work-centered research [1-3]. UFuRT is composed of four major components: User, Function, Representation, and Task analyses (Figure 1). User analysis is the first stage of the UFuRT process. It provides user information to functional, representational, and task analyses. . User analysis is the process of identifying the types of users and the characteristics of each type of users. User characteristics include expertise and skills, knowledge bases, education background, cognitive capacities and limitations, perceptual variations, age related skills, cultural background, personality, etc. User analysis can help us design systems that have the right knowledge and information structure that match those of the users.