As Easy to Use as a Banking Machine

Abstract

Over 100 million people use productivity suites such as Microsoft Office to accomplish a huge variety of tasks. Most of those tasks are `problem solving' tasks that require users to generate novel solutions in novel situations. It is the problem solving nature of work that makes designing productivity software difficult. It is difficult for the designer to anticipate and understand the user's task. As a consequence, productivity suites present difficulties for users and those difficulties are often discussed in the HCI community. Despite the difficulties involved in designing productivity software, suites are `pretty well' designed and users are successful using them. Productivity software is only `pretty well' designed because current user research practice is good at locally optimising individual features in products. When users are not successful it is because current user research practices are not very good at understanding the kinds of problem solving tasks that constitute work. Practitioners do not currently have good methods for taking field observations and turning those observations into design. It is only by developing these methods that we can improve the design of productivity software. Understanding how to turn observations into designs Is very important to improving the design of productivity software and it is very difficult. Solving this problem will require cooperation between HCI researchers and HCI practitioners.