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Undertakes a comparative study of the statistical capability of three spreadsheets which are commonly used in the business sector. The spreadsheets considered are Lotus 1‐2‐3, Microsoft Excel and Quattro Pro. Considers five areas of statistical analysis regularly used by business decision makers (rather than specialist personnel). In order to obtain an objective measure of the statistical provision of each spreadsheet, comparison has also been made with dedicated statistical software regularly used by business decision makers, namely MINITAB. By making this comparison, argues that the spreadsheet is not only a tool for analysis, but also for presentation. Moreover, considers that two spreadsheets in particular, namely Excel and Quattro Pro, offer a user‐friendly statistical provision which should be sufficient for most business decision makers.

The commercial spreadsheet is 21 years old and is now a commonplace business tool. To assess its impact on today’s modern business, this paper presents research based on a questionnaire survey of 227 respondents drawn from a range of business disciplines, and at various levels within their organisations. The results suggests that over 80 per cent are regular spreadsheet users, with Excel being the dominant spreadsheet. However, while its use in a variety of business applications is apparent, often only relatively low‐level features of the spreadsheet are utilised. Limited and inappropriate training persists and it is argued that unless this issue is embraced and appropriate resources channelled into developing expertise in this area, companies are unlikely to fully capitalise on the potential of the spreadsheet to encourage knowledge transfer and enhance workplace performance.

Considers the potential use of spreadsheets as decision‐support systems (DSS). Commences by considering the nature of DSS and the advantages and disadvantages of spreadsheets as DSS, and then proceeds to consider and illustrate some of the models that can be easily built with modern spreadsheet packages, including models to support what‐if or scenario analysis, sensitivity analysis, goal seeking and optimization. Develops detailed examples using Excel, but most of the features used in model building in these examples are also available in recent releases of other spreadsheet packages.

Manufacturing facilities may simplify their operations by converting from a process‐based layout to manufacturing cells. Mathematically, many possible configurations of cells exist, so it may prove computationally infeasible to analyse them all. Also, some current methods of cell design do not take account of the pattern of demand of the existing products or the sequence of the operations that are performed on the products. Presents a simple method of designing manufacturing cells, which uses product demand and operations sequence to design feasible cells, while remaining computationally simple. The method uses a standard spreadsheet tool, so is accessible to a wide range of manufacturing facilities. The method is illustrated with an actual application to a press shop manufacturing over 200 products on 20 presses.

One of the most difficult aspects of deriving an information management plan for a large knowledge‐based enterprise is to determine what information people require to do their various tasks as well as help them expand and update their existing knowledge. Achieving this goal can be time consuming. To speed up and yet effectively define information needs, an electronic survey tool was designed to survey the employees of a large government organization. This paper concentrates on the development and implementation of the electronic survey including survey preparation, distribution, data collection and processing, and data analysis and evaluation. Practical, tested, guidelines are included. In addition, alternative means, tools and techniques to conduct the electronic survey are discussed.

Classifies the critical knowledge/skill set according to content or domain of knowledge by means of a survey. This is conducted in accordance with what IS practitioners and educators can easily relate. The survey uses this approach and includes four broad categories of critical Information Systems (IS) knowledge/skills: IS technology knowledge/skills, organizational and societal knowledge/skills, interpersonal knowledge/skills, and personal trait knowledge/skills.

Data warehousing is the technological trend for the corporate decision support process. This article investigates the current business environment of the data warehouse, including OLAP, data mining, data visualization and other technologies. This article also analyzes the importance of data warehouse management and maintenance and its future developments.

Business process reengineering (BPR) and total quality management (TQM) both emphasise the benefits that a process orientated view of company operations can bring. Acquiring a clear definition of the “as‐is” business process and developing an understanding about how the process may be re‐engineered is a crucial stage in any BPR project. This early phase normally has three objectives: to achieve a full understanding of the process to be re‐engineered so as to clarify its objectives and characteristics; to create a shared vision and understanding among the re‐engineering team; to have a basis for starting the redesign. To support this phase, there is a range of tools: manual, computer supported and computer enabled which are traditionally used to help in the activities of process definition and analysis. This paper describes some of the newer approaches. The product introduction process (PIP) is examined in a general sense, and specific examples from the automotive industry are taken as a basis for evaluation of the available tools and applications. A sample from the process analysis tools identified was used to model the PIP, and from the difficulties and successes an understanding of the attributes required in such an analysis tool was derived.

An important part of any strategic competitive analysis has always been access to timely and relevant data that can be pruned into useful information. Some new and still rapidly evolving technology is lowering the cost and simplifying access to huge data banks. This technology is already having an impact on competitive analysis. What once may have been a million‐dollar research effort taking many months, can now be accomplished in a few hours using a well‐equipped desktop PC that can read the new data sources.