End User Computing

For the past decade or more, managers and non-managers alike have experienced a pent-up demand for computing and information resources, coupled with long lead times for MIS systems development, testing and installation. At the same time, information technology has advanced to the point where computer support permeates all the functional units and users are becoming and accountable for the information systems in their organizations. With the development of problem solving software that can be easily learned and used, end-user computing the creative use of computers by employees who are not data processing experts is growing at a significant rate.

Decision support systems and artificial intelligence techniques are two examples of end user computing that are becoming more useful to managers. Like MIS, DSS and artificial intelligence offer managers the ability to receive filtered, condensed, and analyzed information that can enhance their job performance and, in the case of artificial intelligence, provide them with an information system that can keep pace with own knowledge and sophistication.

Decision support Systems:

As defined in the article overview, a decision support system (DSS) is an interactive computer system that is easily accessible to, and operated by, those who are not computer specialists to assist them in planning and decision making functions. While DSS may differ in their emphases on data access and modeling functions, there is an overriding in all such systems on user accessibility to data for decision making.

Because the DSS is an outgrowth of the MIS, there are basic similarities between them. They are both computer based and designed to supply information to managers. However, the DSS has an important advantage: it is geared to information manipulation and not essentially to data storage and retrieval, as are many MIS. A DSS is operated directly by its users. When they need access to information, they can immediately consult their own on-line system without having to wait days or weeks for results from the MIS department. Once managers call up the required data through a DSS, they can manipulate it directly, asking questions and reformatting the data to meet their specific needs without having to explain what they want to the EDP/MIS staff. Managers are, therefore, more likely to get the information they need when they need it. In addition, direct manipulation of data has the advantage of greater security for sensitive information.

Another key differences between and MIS and a DSS is that a DSS helps managers make non-routine decisions in unstructured situations. An MIS, on the other hand, emphasizes standard periodical reports and cannot respond well to non-routine, unstructured or ad hoc situations. MIS departments may be unfamiliar with the decisions made in such situations. Because they often have a tremendous backlog of request for data, they may be unable to respond quickly to additional special requests. Conversely, some managers who have no difficulty manipulating the data themselves may have difficulty explaining their information requirements to MIS staff.

Using DSS:
At Pet Foods in St. Louis the sales forecasting department performs a large percentage of its own data processing tasks. Using readily available DSS applications software, users can project sales demand by units per territory and region and translate that information into a financial forecast. Through this process, the department can determine the effects of closing a particular warehouse in a matter of days, where the same task take the MIS department weeks or months. This is but one example of the successful application of DSS.

End User Computing: With the increasing growth in end user computing, computer professionals are likely to spend more time away from MIS department offices guiding and supporting the end users are learning to use and apply new technology and tools.

Including users on the Design team: It is widely agreed that cooperation between the eventual users and systems designers is necessary in developing a DSS. Users know what information they need, so their input is essential in developing a system that will meet those needs.