The difference between the expected amount of direct and actual material used is known as direct material yield variance.
Material yield variance is a management tool to analyze what should be produced from a certain amount of direct material.
Suppose the resulting quantity is less than expected. In that case, it will be termed an unfavorable variance.
If the actual quantity produced is greater than expected, then the variance would be called a favorable variance.
The formula for Direct Material Yield Variance:
= (Actual unit usage – Standard unit usage) × Standard material cost per unit
The favorable result shows that the unit usage of direct material is less than expected.
While the unfavorable results show that the actual unit usage of direct material is greater than budgeted usage.
Hilton Company has estimated that 8 kilograms of rubber will be provided to complete the one unit of a plastic drum.
During the recent production period, the process used 315,000-kilogram rubber to create 35,000 drums, which is exactly 9kg per product.
The standard price for one kg rubber is $0.5.
It is required: The material yield variance for the period.
Put the amounts in an equation and you will get
= (315,000 – 280,000) × 0.5
= $17,500 material yield variance.
Importance of Direct Material Yield Variance:
Material yield variance helps the managers and directors of a company in various aspects by offering comparative data.
This variance is useful in analyzing the efficiency of production machinery, by comparing the standards with actual output.
Variances Company can find out the problematic areas due to which the company could not get their desired results.
Helps in Decision Making:
The data provided by direct material yield variance helps the managers in making decisions to improve the efficiency of the production department.
They can easily identify the factors the company did not achieve the required standards.
For example, if company A and Company B are producing similar products by using similar technologies and raw materials.
If company A cost of material per unit is 1 once while the same product is made by company B taking 1.5ocne of direct material.
So Company B should implement the standard material yield as 1 ounce and analyze the actual results, so they will find out what prohibiting the production department from achieving the required standards.
Based on this finding, managers may arrange training sessions for the workers to achieve the desired standards.
Helps in control Cost:
When you set the standards considering the best in the industry or the best data available internally, then the cost of material will be controlled automatically when there is an effort to achieve the required standard.
So material yield variance is useful in controlling the cost of direct materials.
Limitations of Direct Material Yield Variances:
The material yield variance has also some limitations which should be considered before going for the results, as these may affect your calculations.
Certain factors are associated with every activity beyond management’s control and may affect the activity.
So while making planning all those types of factors should include in calculations.
Change in Quality of Direct Material:
If the company sets its estimates by considering a high-quality direct material and for some reason the company did not find the required amount of material according to their needs.
Then there may be a high chance that the other material used by the company could give the required yield as expected.
So if you analyze at the end, there will be a high difference between planned and achieved. To overcome this limitation, companies should update their planning from time to time.
Change in Technology:
Technology may affect the yield variance positively and negatively. If the change is more advanced with less chance of material wastage, there will be favorable change.
But if you set the targets by considering the standards of another company which uses more advanced technology than yours, then it means you not comparing the same things and your variance result will not be accurate in the sense that it is a comparison of two different things.