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3.2. DEVELOPMENT OF THE MODEL 65 RPE use ✻ Positive Environmental Uncertainty Figure 3.1: Conceptual Model Negative (H1) Positive ❄ Noise in the Performance Evaluation Emphasis on Personal-Level Measures In addition to environmental uncertainty, this study also includes other drivers of noise. The second driver of noise that is discussed in this chapter refers to the emphasis on personal-level measures. Performance information can be obtained with measures at various organizational levels, which range from personal-level performance indicators and business-unit-level measures to firm-level performance metrics. The organizational level at which the performance metrics are obtained, impacts the amount of noise in the measure. For example, performance information that is obtained at organizational levels higher than the business unit (i.e., firm-level measures) include more than the organizational parts over which the business unit manager has control and are noisy per se, as the performance measurement includes factors beyond the control of the evaluated manager. In contrast, performance information at the personal level contains little to no noise, as it contains information about the manager’s own actions and abilities. This information includes the manager’s personal development of his professional and social skills, and experience and knowhow. The increased importance of personal-level performance measures in the Performance Measurement System as a whole reduces the room for noisy performance measures. This argument is expressed in the following expectation: the emphasis on personal-level performance measures has a negative effect on noise in the performance evaluation. Emphasis on Disaggregated Performance Measures In addition to the organizational level of the performance metrics, the level of aggregation of the performance measures affects noise. Bouwens & Van Lent (2007) argue that a primary function of disaggregated measures is to reduce the noise in aggregated measures (e.g., accounting returns and profits). Disaggregated measures, including cost, revenue, or cash flow measures, are less subject to exogenous events because disaggregated measures include fewer performance areas that can be affected by external factors. Therefore disaggregated measures contain less noise (Bouwens & Van Lent 2007). As a result, I form the following expectation: the emphasis on disaggregated performance measures has a negative effect on noise in the performance evaluation. ✻
66 CHAPTER 3. NOISE REDUCTION EFFECTIVENESS RPE use ✻ Positive Environmental Uncertainty - Emphasis on Personal Level Performance Measures - Emphasis on Disaggregate Performance Measures - Goal Ambiguity - Measurability of Outputs Figure 3.2: Causal Model Negative (H1) Positive Noise in the Performance Evaluation Goal Ambiguity & Measurability of Outputs The fourth and fifth expectations relate to the impacts of goal ambiguity and measurability of outputs on the noise in the performance evaluation. Both goal ambiguity and measurability of outputs are likely to influence the perceived noise level, because respondents may experience distortion (i.e., the misalignment between the desired organizational results and the measured and achieved performance) as noise. If the organization cannot communicate or measure its desired results, then it can become unclear to the evaluated manager to what standards his achieved results are being compared. This ambiguity can increase the level of noise in the performance evaluation because if the goals and targets are unclear, then there is room for other factors to influence the manager’s performance evaluation. To include the influence of unclear goals, or poorly measurable outputs, this study formalizes its effects as follows: goal ambiguity has a positive effect on the level of noise in the performance evaluation and measurability of outputs has a negative effect on the level of noise in the performance evaluation. The conceptual model, which includes the research hypothesis and the associated expectations, is summarized in figure 3.2. ✻ ❄ ✻
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3.2. DEVELOPMENT OF THE MODEL 65<br />
RPE use<br />
✻ Positive<br />
Environmental<br />
Uncertainty<br />
Figure 3.1: Conceptual Model<br />
Negative (H1)<br />
Positive<br />
❄<br />
Noise in the<br />
Performance<br />
Evaluation<br />
Emphasis on Personal-Level Measures In addition to environmental uncertainty,<br />
this study also includes other drivers of noise. The second driver of noise that is discussed<br />
in this chapter refers to the emphasis on personal-level measures. Performance<br />
information can be obtained with measures at various organizational levels, which range<br />
from personal-level performance indicators and business-unit-level measures to firm-level<br />
performance metrics. The organizational level at which the performance metrics are obtained,<br />
impacts the amount of noise in the measure. For example, performance information<br />
that is obtained at organizational levels higher than the business unit (i.e., firm-level measures)<br />
include more than the organizational parts over which the business unit manager<br />
has control and are noisy per se, as the performance measurement includes factors beyond<br />
the control of the evaluated manager. In contrast, performance information at the personal<br />
level contains little to no noise, as it contains information about the manager’s own<br />
actions and abilities. This information includes the manager’s personal development of his<br />
professional and social skills, and experience and knowhow. The increased importance of<br />
personal-level performance measures in the Performance Measurement System as a whole<br />
reduces the room for noisy performance measures. This argument is expressed in the following<br />
expectation: the emphasis on personal-level performance measures has a negative<br />
effect on noise in the performance evaluation.<br />
Emphasis on Disaggregated Performance Measures In addition to the organizational<br />
level of the performance metrics, the level of aggregation of the performance measures<br />
affects noise. Bouwens & Van Lent (2007) argue that a primary function of disaggregated<br />
measures is to reduce the noise in aggregated measures (e.g., accounting returns and profits).<br />
Disaggregated measures, including cost, revenue, or cash flow measures, are less<br />
subject to exogenous events because disaggregated measures include fewer performance<br />
areas that can be affected by external factors. Therefore disaggregated measures contain<br />
less noise (Bouwens & Van Lent 2007). As a result, I form the following expectation:<br />
the emphasis on disaggregated performance measures has a negative effect on noise in the<br />
performance evaluation.<br />
✻
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