Using Flexible Budgeting to Improve Sustainability Measures, Part II 

Published April 17, 2017

In our first article, Using Flexible Budgeting to Improve Sustainability Measures, we identified a common problem with sustainability reporting.1  Some companies incorrectly use the average intensity of sustainability key performance indicators as measures to report efficiency improvement. While it is true that efficiency improvements impact average intensity, we identified four confounding factors that also impact average intensity causing it to lose usefulness as a measure of improvement in efficiency. With a straightforward example, we demonstrated how CPAs can use their expertise to remedy this situation by applying flexible budgeting to correctly measure efficiency improvement.

In the initial article, we focused on correctly measuring efficiency improvement when a single confounding factor, a shift in product mix, is present. We considered a shift in production volume from a high-energy intensive product to a low-energy intensive product. The shift in production volume to the less energy intensive product causes average intensity to decline even if no efficiency improvements were made in the production of either product. This reduction in average intensity should not be reported as an improvement in energy efficiency, and we demonstrated how flexible budgeting can be used to correctly measure the change in energy efficiency (none in this case). In this article, we acknowledge that in real life situations more than one factor will likely change.  Accordingly, we demonstrate the application of flexible budgeting to correctly measure the change in efficiency in a more complex situation where both a shift in product mix and an outsourcing event occur.

We begin with the Nelson Company, a manufacturer of two products, X and Y. Product X is produced in two stages. In Stage 1 a component, N, is manufactured to be used as an input in the completion of X in Stage 2. One unit of N is required for each unit of X. In year 1, 6,000 units of N and 6,000 units of X are manufactured. Electricity consumption was 6,000 KWH and 18,000 KWH for Stage 1 and Stage 2, respectively. Thus, total electricity consumption is 24,000 for the 6,000 units of X. Relative to X, Y is very energy intensive. In year 1, 2,000 units of Y were produced consuming 20,000 KWH of electricity.

TABLE 1

Year 1 
 

 Production

 Electricity Used

 Rate 

 (Units)

 (kWh)

 (kWh/Unit)

 Input N

 6,000

 6,000

 1.0

 Product X

 6,000

 18,000

 3.0

 Product Y

 2,000

 20,000

 10.0

 Total

 14,000

 44,000

 
 
 Average Intensity:
 = Total electricity used/Total units of products produced*
 = 44,000/(6,000+2,000)
 = 5.5

 

 * N is an input, NOT a product


Three changes take place in year 2. First, Nelson outsources the production of N. Second, there is a shift in the production mix. Nelson now produces only 2,000 units of X and increases production of Y to 6,000 units. Total production remains the same as in year 1 at 8,000 units. The third change is an energy efficiency improvement of 10% in the Stage 2 production of X and a 20% energy efficiency improvement in the production of Y. In year 1, the rate for Stage 2 is 3.0 KWH of electricity per unit of X  (18,000 KWH/6,000 units of X) (see Table 1). The rate for Y was 10 KWH per unit of Y (20,000 KWH/2,000 units of Y) (see Table 1). For year 2, a 10% efficiency improvement for Stage 2 results in a new rate of 2.7 KWH per unit of X and a 20% improvement for Y yields a new rate of 8 KWH per unit of Y (see Table 2).

TABLE 2

Year 2
 

 Production (2)

Rate (3) 

Electricity Used 

 (Units)

 (kWh/Unit)

(kWh)

 Input N (1)

 -

-

 -

 Product X

 2,000

2.7 (3*90%)

5,400

 Product Y

 6,000

8  (10*80%)

48,000

 Total

 8,000

 53,400

 
 Changes from Year 1:
 (1) Production of Input N is outsourced
 (2) Shift in production mix:
       - 2,000 units of X are produced (versus 6,000 Year 1)
       - 6,000 units of Y are produced (versus 2,000 Year 1)
(3) Energy efficiency improvements: 10% for Product X and 20% for Product Y 
 
Average Intensity:
= Total electricity used/Total units of products produced
= 53,400/(2,000+6,000)

= 6.7 

 
 
Nelson’s management is pleased with the thoughtful investments made to improve energy efficiency and is expecting its numbers to reflect this effort. Nelson uses average intensity to measure its progress at improving energy efficiency. We know that the three changes will each have its own impact on average intensity. Outsourcing reduces electricity and will contribute to a reduction in average intensity. The shift in production mix to a higher energy intensive product will contribute to an increase in average intensity. And the improvement in energy efficiency will contribute to a decline in average intensity. Average intensity for year 1 is 5.5 {(6,000+18,000+20,000)/(6,000+2000)} (see Table 1) and is 6.7 {(5,400+48,000)/(2,000+6000)} for year 2 (see Table 2). Management is shocked that average intensity has worsened.

TABLE 3

Year 2  
 Production

Flexible Budget 

 Actual
Electricity Used

Efficiency
Improvement

 (Units)

(kWh) 

 (kWh)

(%)

 

(a)

(b)

= (a-b)/a

  Input N

 -

-

-

-

Product X   2,000

6,000  (3*2,000) 

5,400 

10.0% 

Product Y 6,000

60,000  (10*6,000) 

48,000 

20.0%

Total 8,000

66,000 

53,400

19.1% 

 
As we understand, the calculation of average intensity is correct, but this measure should not be used to monitor efficiency improvement. As we see in Table 3, the flexible budgeting approach does show an improvement in electricity efficiency of 10% and 20% for X and Y respectively. More importantly, this approach provides a measure of the aggregate average improvement in electricity efficiency. For Nelson it is 19.1%. The aggregate improvement is not the simple average of 10% and 20%. Rather, the aggregate improvement is a weighted average of the individual improvements and the weights are driven by the relative size of each component of the total flexible budget amount. Because Y is the most significant part of the flexible budget, the aggregate average improvement is closer to the 20% improvement in Y.

In summary, we demonstrate, once again, how the commonly used measure of average intensity by companies to report efficiency improvements often does not produce an accurate metric.  Fortunately, the use of the flexible budget approach provides information to support a more accurate measure of the improvement in efficiency; thereby facilitating better decision making for investing in sustainability initiatives and in reporting the results of these investments.  In our next article, we will discuss the third confounding factor of changes in total production as a company more fully utilizes its capacity.


1 AICPA, January 26, 2017
http://www.aicpa.org/InterestAreas/BusinessIndustryAndGovernment/Resources/Sustainability/Pages/ImproveSustainabilityMeasures.aspx



Jon Bartley, CPA, Ph.D., is Professor Emeritus of Accounting and former Dean of the Poole College of Management, North Carolina State University in Raleigh, NC.  You can reach Jon at
jon_bartley@ncsu.edu

Y.S. Al Chen, Ph.D., CPA, CITP, CGMA, CMA, CFM, is Professor of Accounting at the Poole College of Management, North Carolina State University in Raleigh, NC.  You can reach Al at alchen@ncsu.edu

Stephen K. Harvey, M.S., M.B.A., P.E., is former Global Director of Environment, Health and Safety for Bacardi Limited and is currently Industry Fellow in Corporate Responsibility at the Poole College of Management, North Carolina State University. You can reach Steve at skh1454@gmail.com
D. Scott Showalter, CPA, CGMA, CGFM, is Professor of Practice at the Poole College of Management, North Carolina State University in Raleigh, NC.  You can reach Scott at dsshowal@ncsu.edu

Gilroy Zuckerman, Ph.D., is Associate Professor of Accounting and former Associate Dean of Academic Affairs of the Poole College of Management, North Carolina State University in Raleigh, NC.  You can reach Gil at gilroy_zuckerman@ncsu.edu




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