Academic journal article Academy of Accounting and Financial Studies Journal

Comprehensive Variance Analysis Based on Ex Post Optimal Budget

Academic journal article Academy of Accounting and Financial Studies Journal

Comprehensive Variance Analysis Based on Ex Post Optimal Budget

Article excerpt

INTRODUCTION

This study offers a new framework for measuring and interpreting profit, cost, and inventory variances. An optimized revision of the static budget developed at the end of the budget period constitutes the core of the proposed method. The proposed framework offers an alternative to the traditional flexible budgeting and enables management to obtain new insight into the firm's operations and financial conditions. Under the traditional approach, flexible budget is a merely revision of the static budget based on actual sales volume. In contrast, the proposed flexible budget is a completely revised and ex post optimal budget. (1) An ex post optimal budget is a revision of the static budget using the latest data available to management by the end of the budget period. Every budget parameter, including sales volumes and prices, and input quantities and prices are subject to change. Under the proposed method, several new variances will be introduced such as planning variance, inventory-change variance, and budgeted unused capacity variance. Following similar articles in this area (2), the methodology adopted here is descriptive and based on numerical examples. Additionally, the current paper utilizes a linear programming model for computation of variances in a multi-product, multi-divisional setting.

Following earlier studies in accounting and marketing literature such as (Demski, 1967), (Hulbert and Toy, 1977), and (Yahya-Zadeh, 2002), the present study redefines flexible budget as an ex post optimal budget. The optimality of the ex post flexible budget proposed here requires the use of an optimization procedure. The linear programming procedure used in this study makes it possible to view annual budgeting as an optimization exercise and to overcome some of the limitations of the traditional approach. Traditional flexible budgeting is constrained by the number of products and departments it can accommodate. The present approach overcomes this constraint. The use of the linear programming technique enables management to seek optimal production levels taking advantage of company-wide resources. Traditional budgeting treats resource allocation as reconciliation between divisional resource demands and company resource supplies. In contrast, the proposed approach achieves optimal profits through a reallocation of company resources in response to changing market and production conditions. The distinction is not trivial since the mere resource reconciliation does not achieve optimality. Critical management decisions concerning capacity utilization levels are incorporated in the overall optimization program. Traditional flexible budgeting often fails to examine the differences between budgeted and actual inventory levels. The present study explicitly incorporates a measure of inventory variance into the analysis.

Traditional budgeting procedures have been widely criticized in academic literature and in popular business media. (3) A frequently cited weakness of traditional budgeting is the absence of timeliness and therefore, relevance. Clearly, the frequency of budget revisions and the timeliness of the information used in those revisions affect the relevance of budgeting. A budget that lacks optimal goals, or loses its optimal goals soon after its introduction, will be a hard sell among managers. The present study offers a solution to this problem. By using an optimization procedure based on the latest available data, optimality of the budget and its relevance can be enhanced.

Traditional flexible budgeting has also been criticized for generating the wrong signals for management decisions. Goldratt and Cox (1990), among other critics, argue that traditional variance analysis treats the cost of unused capacity as an unfavorable variance and penalizes a manager for underutilizing her divisional full capacity. He argues that under traditional variance analysis, increased production is treated as favorable, thus incentivizing managers to increase production to the maximum capacity. …

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