# Variance Analysis – Definition

### Variance Analysis Definition

Variance analysis is used in budgeting and management accounting. It is a study of the variation (difference) between an actual (forecasted) action and a planned action. Variance analysis carries out a quantitative investigation to find out the difference between the actual cost and the standard cost of production. This investigation or analysis aids in adequate management of a business or project.

Oftentimes, there is a variation between planned cost and the actual cost of a project, these variations are compiled using variance analysis.

### A Little More on What is Variance Analysis

Variance analysis helps project managers in outlining sudden and systematic changes between the amount budgeted for a project and the actual amount spent. This term is also applicable in sales, for instance, if an individual budgets \$50,000 for sales in a particular month and the actual sales is \$38,000, the variance is \$12,000. Hence, variance analysis studies these differences and also factors responsible for the variation. With the detailed analysis presented in variance study, managements are brief on the occurrence of fluctuations, why they occur and how they can be addressed. The popular variances used in variance analysis are as follows:

• Purchase price variance
• Selling price variance
• Labor rate variance
• Labor efficiency variance
• Material yield variance

Despite that many variances can by analyzed, certain organization prefer to do a variance analysis of the aspect that affects them the most. The inability to track preceeding variances also leave many organizations with no option than to review the available variances. The services offered by an organization also determines which variance will be analyzed. For instance, a consulting firm might focus on labor efficiency variance will a store or retail business might focus on purchase price and selling price variation.

Variance analysis help organizations discover underlying issues in their practices and where the issues can be rectified.

Despite the usefulness of variance analysis, certain problems associated with the analysis discourage organizations from using it. Some of the problems are;

• Sources of data for variance analysis – the analysis depends on information and data in order to investigate the difference between a standard cost and actual cost. However, some data used in the analysis are not premised on accounting records, which can be misleading for many forms.
• Time delay – this is another problem with variance analysis. While management needs prompt feedback and not just one a month feedback, variance analyst rely on monthly accounting compilations for the analysis.
• Another problem is that the result of a variance analysis might not provide an organization with useful information.

Due to the problems attributed to variance analysis, many organizations seek alternative and a better method. Many organizations have developed preference for the use of horizontal analysis in place of variance analysis. Horizontal analysis examines financial results of multiple periods or preceding months. This makes it easier for management to discover the variance on a trend line.

### Academic Research on Variance Analysis

Use of ranks in one-criterion variance analysis, Kruskal, W. H., & Wallis, W. A. (1952). Journal of the American statistical Association, 47(260), 583-621.

A mean/variance analysis of tracking error, Roll, R. (1992). The Journal of Portfolio Management, 18(4), 13-22.

Arbitrage, factor structure, and mean-variance analysis on large asset markets, Chamberlain, G., & Rothschild, M. (1982).

Minimum and maximum variance analysis, Sonnerup, B. U., & Scheible, M. (1998). Analysis methods for multi-spacecraft data, 185-220.

A reexamination of mean-variance analysis of bank capital regulation, Keeley, M. C., & Furlong, F. T. (1990). Journal of Banking & Finance, 14(1), 69-84.

Mean-variance analysis in the theory of liquidity preference and portfolio selection, Feldstein, M. S. (1969). The Review of Economic Studies, 36(1), 5-12.

Algorithms for computing the sample variance: Analysis and recommendations, Chan, T. F., Golub, G. H., & LeVeque, R. J. (1983). The American Statistician, 37(3), 242-247.

Multiāperiod meanāvariance analysis: toward a general theory of portfolio choice, Hakansson, N. H. (1971). The Journal of Finance, 26(4), 857-884.

Prospect theory and mean-variance analysis, Levy, H., & Levy, M. (2003). Review of Financial Studies, 17(4), 1015-1041.

Economic implications of using a mean-VaR model for portfolio selection: A comparison with mean-variance analysis, Alexander, G. J., & Baptista, A. M. (2002). Journal of Economic Dynamics and Control, 26(7-8), 1159-1193.

Is mean-variance analysis applicable to hedge funds?, Fung, W., & Hsieh, D. A. (1999). Economics Letters, 62(1), 53-58.