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The tool described is most appropriate for a first-level undergraduate course in cost/management accounting, which is typically taken in the second year of a post-secondary business program.

This chapter discusses a method for teaching a challenging topic within cost/management accounting, which is calculating variances for expenses. The proposed methodology focuses on a “common sense” understanding of variances as differences between budgeted and actual results. The new approach (i) uses a golfing analogy as a frame of reference, (ii) includes questions to assist in the analysis, and (iii) provides a table to organize and calculate variances. The variances examined include eight common expense-side variances used by manufacturers: material price and efficiency variances; labor price and efficiency variances; variable overhead spending and efficiency variances and fixed overhead spending and production volume variances.

By using this tool, students will be able to understand how and why variances are calculated. It will also provide them with better insight into appropriate corrective action that will address deviation from plans.

I provide a template to facilitate the calculation of variances, along with a list of questions that will guide students in their analysis. I also give an application of the suggested approach, using a standard textbook problem.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.

Theeuwes and Adriaansen (1994), among others, have asserted that activity-based costing (ABC) is inappropriate for operational decision-making. In this article, ABC is modified to reflect separate flexible and committed cost driver rates for an activity. This enables the model to reflect the difference in the behavior of an activity’s flexible and committed costs needed for operational planning decisions. The modified ABC facilitates determining the resources required to produce the product mix developed from the firm’s strategic plan and the excess capacity that will result. The modifications made to ABC aid in determining an optimal product mix when the firm has excess capacity, while the traditional ABC may not. Equally important, it facilitates measuring the financial implications of the resource allocation decisions that comprise the firm’s operational plan. As the operational plan is implemented, operational control is used to ensure that it is performed in an efficient and effective manner. The modified ABC enables the firm’s managers to compute the different types of deviations that arise from using flexible and committed resources at the unit, batch, and product levels of the firm’s operations. This aids in understanding problematic aspects of the firm’s operations and identifying where management resources are needed to improve operational efficiency.

Attribution bias can be costly to firms because it hinders decision makers’ ability to infer the real cause of prior events and take corrective action to improve future performance. This study extends prior research by examining whether and how the presence of variance reporting from accounting systems affects firm profitability through a labor cost management decision that is highly susceptible to attribution bias. Our results support the prediction that the presence of variance reporting (process feedback) increases the likelihood of belief revision and corrective action related to the systematic error, and thus increases overall profitability for the firm. The findings of our study propose a solution to attribution and learning problems observed when decision makers are responsible for both cost management and bids as documented in prior literature.

Presents a case study demonstrating financial statement ratio analysis (FSRA). This analysis matches company to industry data and builds sales forecasting models. FSRA imputes forecast standards of sales and costs, and applies them to a budgeted financial statement variance analysis for the EE (electronic and electrical) industry. Develops the concept of industry base standards, integrating them into the more traditional statistical and accounting concepts of quality control standards. Provides an implementation example, and reviews possible improvements to the current methodology and approach. Uses a similar methodology to forecast the stock market value with some exceptions. Models sales and costs of an individual company and an industry based largely on aggregate industry databases. For this purpose, uses a multivariate linear trend regression analysis for the sales forecasting model. Defines and tests related hypotheses and evaluates their significance and confidence levels. For an illustration uses the EE industry and the APM company. Also demonstrates a microcomputer‐based FSRA software that speeds, facilitates, and helps to accomplish the stated objectives. The FSRA software uses industry financial statement databases, computes financial ratios and builds forecasting models.

In this paper we discuss a mechanism for making business decisions on the basis of an expected penalty function associated with cost variance. We assume that the decision maker is knowledgeable of the economic environment in which the decision will be made, but that he has no hard data” such as a market research report. In this setting fuzzy logic is more applicable than ordinary statistical decision theory. We develop a method of computing a fuzzy expected penalty based on a fuzzy distribution of cost variance and a fuzzy penalty function. These fuzzy expected penalties are then defuzzified” so that a non‐fuzzy decision can be made.

BRITISH industry and commerce as a whole is recovering confidence despite continued stagnation in the manufacturing sector, forecasts a survey for the next quarter published by Manpower, the international work contractors.

Preface The functions of business divide into several areas and the general focus of this book is on one of the most important although least understood of these—DISTRIBUTION. The particular focus is on reviewing current practice in distribution costing and on attempting to push the frontiers back a little by suggesting some new approaches to overcome previously defined shortcomings.

Most research on the process control charts concentrates on the economic design of its parameters. Reduction of variance as a control decision has not been researched. Presents a model for optimal decision on variance reduction and includes the rejection losses of the non‐conforming units increasing due to increased variance, Taguchi loss of the conforming units, and the cost of reducing variance. Optimal policies are derived analytically for uniform distribution and numerically for normal distribution. Applications of the model to the area of machine replacement and global manufacturing are suggested.

Accounting, particularly in the area of cost variance analysis, contains a great deal of ambiguity due to imprecise or ill‐defined control terms. Cost accountants must continually incorporate good sense and professional judgment in the accounting process to overcome that ambiguity. Because of the construction of accounting expert systems, no ambiguity is present in the facts or rules, thereby excluding human reasoning and analysis of feedback within those systems. The use of fuzzy sets to build fuzzy control systems provides a method to incorporate ambiguity into expert systems, allowing expert systems to more closely emulate the complex human decision making process.