Efficiency Variance

By
Will Kenton
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Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School for Social Research and Doctor of Philosophy in English literature from NYU.
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Updated January 10, 2022
Reviewed by
Khadija Khartit
Khadija Khartit
Reviewed by Khadija Khartit
Full Bio
Khadija Khartit is a strategy, investment, and funding expert, and an educator of fintech and strategic finance in top universities. She has been an investor, entrepreneur, and advisor for more than 25 years. She is a FINRA Series 7, 63, and 66 license holder.
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What Is Efficiency Variance?

Efficiency variance is the difference between the theoretical amount of inputs required to produce a unit of output and the actual number of inputs used to produce the unit of output. The expected inputs to produce the unit of output are based on models or past experiences. The difference between expected required input and the actual required input can be attributed to inefficiencies in labor or use of resources, or they may be due to errors in the assumptions used to set input expectations.

In manufacturing, efficiency variance can be used to analyze the effectiveness of an operation with respect to labor, materials, machine time, and other production factors.

Key Takeaways

  • Efficiency variance is a numerical figure that represents the difference between the theoretical amount of inputs required to produce a unit of output and the actual number used in practice.
  • The differences in these two figures may be attributed to inefficiencies in labor, or they may be due to errors in the assumptions used to project input expectations.
  • In manufacturing, efficiency variance can help managers analyze the effectiveness of operations, with respect to labor, materials, machine time, and other factors.

Understanding Efficiency Variance

An important factor in measuring efficiency variance is the development of a set of realistic assumptions surrounding the theoretical amount of inputs that should be required. If the actual amount of inputs used exceeds the amount theoretically required, there is a negative efficiency variance.

On the other hand, if actual inputs are less than the amounts theoretically required, then there would be a positive efficiency variance. Since the baseline theoretical inputs are often calculated for the optimal conditions, a slightly negative efficiency variance is normally expected.

Efficiency variance calculations not only apply to the output of tangible goods, but they also apply to the completion of cerebral tasks, such as the number of hours it takes to audit an individual's tax records.

Why Efficiency Variance Is Important

Efficiency Variance is essential to the manufacturing processes because managers rely on different ratios and budget breakdowns in order to analyze the productivity of the factory output in their overall efforts to maximize efficiency.

It’s thus typical for management personnel to set expectations and benchmarks for both costs and output, while the manufacturing activity is still in its planning stage before the production process even starts.

Examples of Efficiency Variance

During the planning stages, the management staff might have projected that it will take 50 labor hours to produce one unit of a specific product. However, after the first round of products is completed, records indicate that 65 labor hours were used, to complete the item in question.

In this case, the efficiency variance on the labor hours for this particular manufacturing process is -15, which indicates that fifteen hours of labor were wasted in the manufacturing process, and signals that the process wasn’t as efficient as previously thought.

With this figure in hand, management can make adjustments to overheard and other factors. But on the other hand, if only 45 labor hours were actually used, then the efficiency variance would be +5, indicating that the manufacturing process was more productive and cost-effective than initially assumed.