Calculate the two pieces that are shown by the question marks.
Reflect on the business practices of this large regional reference lab. Is the laboratory profitable now? What would you suggest change? What might be next steps?
Calculation of the gross marketing contribution with the original product mix
Product mix variance.
The mix variance is a cost variance that comes about when the actual product mix varies from the planned or budgeted product mix. This variance explains the efficiency or usage variance resulting from using direct labor and direct materials in different ratios from the standard proportion. Product mix variance enables us to determine the efficiency with which mixing operations have been done.
This variance can be either a favorable variance or an adverse variance. When the product mix variance is favorable, it means that the gross marketing contribution that results from the actual product mix is more than the gross marketing contribution that would have resulted from the original product mix. When the product mix variance is adverse, then the gross marketing contribution that results from the actual product mix is less than the gross marketing contribution with the original product mix.
Calculation of product mix variance:
Product mix = gross marketing contribution _ gross marketing contribution with
Variance with original product mix actual product mix
Product mix variance = $2,024,500 - $1,749,500 = $275,000
This is an adverse product mix variance. This shows that the actual product mixing operations have not been performed as per the original product mix hence an adverse deviation that has led to a decrease in the gross marketing contribution. Due to the variances resulting from the deviation of the actual results from the expected results, there should be a reconciliation statement. This is where adverse variances are added back to the actual results or subtracted from the expected/planned results, while the favorable variances are subtracted from the actual results or added back to the planned results. In doing this we find the total figure for the actual and planned results is the same.
Rao, P. S. R. S. (1997). Variance components estimation: Mixed models, methodologies and applications. London [u.a.: Chapman and Hall.
Lindman, H. R. (1992). Analysis of variance in experimental design. New York: Springer-Verlag.