One of the often-neglected steps in building software is understanding the end user’s job—the tasks that computer automation is intended to support. Occasionally, this is because the application itself is quite specialized; more often, it is because the approach to design tends to be data oriented. Frequently, these are the major questions asked in the analysis:
- What data should be captured?
- How should the data be processed?
- How should the data be reported?
These questions expand into a series of subquestions, and they include issues such as input forms, codes, screen layouts, computations, postings, corrections, audit trails, retention, storage volumes, processing cycles, report formatting, distribution, and maintenance. These are all vitally important areas. One difficulty, however, is that they all focus solely on data.
People use data, but they do tasks. One might argue that although this may be true of professional workers, key-entry clerks really only transfer data from an input form to a keyboard; their tasks are very data oriented. This is a fair portrayal of these jobs today. But is this a consequence of the real job that needs to get done, or is it a symptom of the design of the computer application? Using humans as input devices, particularly for data that is voluminous, consistent in format (as on forms), and in a limited range of variability, is an expensive and antiquated, not to mention dehumanizing, method of capturing data. Like the use of codes to accommodate machine limitations, it’s an idea whose time has passed.
This may sound like so much philosophy, but it has practical import in the way application design is done. People use data, but they do tasks. And they don’t do tasks through to completion one at a time. They do several tasks that are subsets of or in intersection with each other, and they do them all at once, in parallel.
When designers allow this idea to direct the analysis and creation of an application, rather than focusing on the data orientation that has been historically dominant, the very nature of the effort changes significantly. Why have windowing and web environments been so successful? Because they allow a user to jump quickly among small tasks, keeping them all active without having to shut down and exit one in order to begin another. The windowing environment comes closer to mapping the way people really think and work than the old “one thing at a time” approach ever did. This lesson should not be lost. It should be built upon.
Understanding the application tasks means going far beyond identifying the data elements, normalizing them, and creating screens, processing programs, and reports. It means really understanding what the users do and what their tasks are, and designing the application to be responsive to those tasks, not just to capture the data associated with them. In fact, when the orientation is toward the data, the resulting design will inevitably distort the users’ tasks rather than support them.
How do you design an application that is responsive to tasks rather than data? The biggest hurdle is simply understanding that focusing on tasks is necessary. This allows you to approach the analysis of the business from a fresh perspective.
The first step in the analysis process is to understand the tasks. For which tasks do the members of this group really need to use computers? What is the real service or product produced? This seems like a fundamental and even simplistic first question, but you’ll find that a surprising number of business people are quite unclear about the answer. An amazing number of businesses, from healthcare to banking, from shipping to manufacturing, used to think they were in the data processing business. After all, they input data, processed it, and reported it, didn’t they? This delusion is yet another symptom of the data orientation our systems designs have had that has led dozens of companies to attempt to market their imagined “real” product, data processing, with disastrous consequences for most of them.
Hence the importance of learning about a business application: You have to keep an open mind, and may often have to challenge pet notions about what the business is in order to learn what it really is. This is a healthy, if sometimes difficult, process.
And, just as it is essential that business people become literate users of SQL and understand the basics of the relational model, so it is important that application designers really understand the service or product being delivered, and the tasks necessary to make that happen. A project team that includes end users who have been introduced to the essentials of SQL and the relational approach, such as by reading this book, and designers who are sensitive to end users’ needs and understand the value of a task-oriented, readable application environment, will turn out extraordinarily good systems. The members of such a project team check, support, and enhance each other’s efforts.
One approach to this process is to develop two converging documents: a task document and a data document. It is in the process of preparing the task document that the deep understanding of the application comes about. The data document will help implement the vision and ensure that the details and rules are all accounted for, but the task document defines the vision of what the business is.
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