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Lanen, W. N. 1999. Waste minimization at 3M Company: A field study of nonfinancial performance measurement. Journal of Management Accounting Research (11): 29-43.

Summary by Antoinette L. Lynch
Ph.D. Program in Accounting
University of South Florida, Spring 2002

Environmental Cost Main Page | Performance Measures Main Page

The purpose of this paper is to describe one formal environmental performance program at 3M Company and to use data generated from the program to assess the impact of various factors on its results.

Motivation: Many firms have adopted programs to improve environmental performance. Regulators mandate some programs and some are voluntary. At this time, however, there is little systematic empirical evidence on the results of these environmental programs or the factors that affect their success (or lack thereof).

Sample: 55 3M Company plants located throughout the United States. Results are based on the experience of a single program at one company.

Background: The late 1960s and early 1970s represented a period of increasing environmental regulation and legislation. As a result, in 1975, 3M initiated a company-wide pollution prevention program. This program, designated "3P" ("Pollution Prevention Pays"), directed 3M employees to take actions to prevent pollution and solve the Company’s environmental and conservation problems. The company shifted to a more comprehensive program called "3P Plus," to minimize the environmental impact of its products, facilities, and operations. The "3P Plus" program includes many individual programs such as a program called "Challenge ’95." The goal of "Challenge ‘95" was to improve cycle times and reduce unit costs at 3M plants, minimize waste and reduce energy.

There are two basic questions of interest with respect to performance measurement programs adopted by firms: First, does the program result in improvements in the measure of interest? Second, what are the factors that affect improvements (as measured by the program) across the units of observation (plants, profit centers, individuals, etc.)? This paper addresses the second question.

Hypothesis:

To the extent that performance is not "high" at the time the performance improvement program is launched, it is more likely that there is slack in the process that allows the business unit to improve the performance metric more easily than those units that were operating at a high level of performance:

H1: Annual gains in performance are negatively related to the level of baseline (prior-year) performance.

As time goes on and performance improves, it becomes difficult to find additional improvement opportunities:

H2: Annual gains in performance are negatively related to the length of time the plan has been in place.

Depending on the level of capacity utilization in the base year, growth in output may require additional capacity, which as a result of technological improvements, may be inherently "cleaner." There is a relationship between waste and good out:

H3: Annual gains in performance are positively related to the level of growth in output.

In the case of "Challenge ’95," the evaluation is at the division level although waste is managed at the plant level. Performance results are then allocated to the divisions. As a result, the more divisions a plant serves (for a given level of waste and output), the less any one division is affected by plant performance. The greater the benefit to the division (and, consequently, the greater the effort of the division to monitor plant performance), the greater will be the performance improvements.

H4: Annual gains in performance are positively related to the marginal benefits accruing to the divisions.

Method: exploratory. Data available for each plant include total output and total wastes (both measured in pounds) allocated to divisions.

Dependent Variable:

Gain = (Performancet-1 – Performancet) / Performancet-1,

where t=91,…,96

where Performance = [Waste (Pounds) / Total Output (Pounds) ] x 100

This measurement tracks waste minimization.

Independent Variables:

Baseline (prior year) level of performance.

Length of time since plan started (plan age) – how long has the plan been in place.

Growth in output – percentage increase in good product shipped from plant.

Benefits to divisions from monitoring plants – 3 proxies are used (1) number of divisions; (2) indicator variable – whether the plant has a single division or multiple division; and (3) inverse number of divisions.

Control Variables:

Plant size

"Challenge ’95 ended in 1995. In order to assess the outcome after the program, the following variables were included in the equation:

Year96t

Base*Yr96t

Growth*Yr96i,t

Monitor*Yr96i,t-1

Conclusion:

H1 supported. Regardless of the measure used for monitoring, there is consistent evidence in support of the baseline-performance hypothesis. Plants that had higher waste ratios (lower baseline performance) in the prior year had a higher performance gain than those with better prior-year performance. This is consistent with managers making those improvements that are "easier" (less costly) first or moving from higher benefit-cost ratio projects to those with lower returns for cost or effort or initially focusing on programs with the biggest benefits.

H2 supported. The Plan Year variable, representing the number of years the program had been in place, is negative and significant at the 1 percent level confirming that relative improvement in performance decreases over time.

H3 is supported. Plants had higher growth rates also showed significantly more improvement in performance than those with slower growth.

H4 is unsupported.

The "Challenge ‘95" program ended in 1995, but the plants continued to report on waste generation. In order to test the impact of the end of the formal program, an indicator variable was included as well as allowing for differences in the baseline, growth, and monitoring effects. The impact of prior-year performance and monitoring was unchanged with the end of the formal program. The effect of growth, however, became even larger in 1996 with an estimated impact over 250 percent above the pre-1996 level.

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