Figure 1From “Variable pay is a risk design when effort is hard to observe”
The variable-pay risk-design card
Name observability, output uncertainty, risk, control alternatives, and incentive loading before changing variable pay.
Figure 1The variable-pay risk-design card
| Risk-design field | Required input | Permitted statement | Stop signal |
|---|---|---|---|
| Effort | Which effort matters, and can it be verified? | “This part of the effort is observed or remains hidden.” | Output is used as a substitute for all effort. |
| Uncertainty | How uncertain is the effort-output link? | “The outcome is a noisy or more predictable signal under this setting.” | A noisy outcome is treated as a clean measure. |
| Agent risk | Who bears outcome risk, and what is known about it? | “The pay rule transfers this declared risk.” | Risk aversion is assumed away. |
| Control alternatives | What coaching, information, supervision, or field management is available? | “Compensation is one part of the control mix.” | Pay is used to repair every process problem. |
| Loading | How strongly does pay vary with the outcome? | “This is the incentive intensity under review.” | A higher percentage is presented as universally better. |
| Evidence | Which study or local test supports the choice? | “The decision is conditional on this evidence.” | An experiment becomes a current prescription. |
Swipe or scroll horizontally if the table is wider than your screen.
Source: Author's diagnostic framework grounded in Ghosh and John (2000) and Cravens, Ingram, LaForge, and Young (1993). The worksheet is synthetic and does not calculate pay.
Source and evidence
Each line names a claim related to this exhibit, its source, and how it was checked.
- A GJ00-C1 "we conducted three experiments to investigate three unresolved predictions involving the incentive-insurance trade-off posited in the model", against a literature where "empirical support remains sketchy"Ghosh & John. (2000)
- A GJ00-C2 The first prediction, and the condition it needs: "compensation should be less incentive loaded with greater effort-output uncertainty so as to provide additional insurance to a risk-averse agent", supported "but only when risk-averse agents undertook nonverifiable effort"Ghosh & John. (2000)
- A GJ00-C3 The second prediction failed: "when verifiable effort made incentives moot, as is the case for the second prediction, the model failed to order the data", which is why this is conditional support and not a ruleGhosh & John. (2000)
- A CLY93-C2 The finding runs against the intuition: "the results imply a limited role for incen"tive compensation "in salesforce control systems"Cravens, Ingram, LaForge & Young. (1993)
- A CLY93-C3 And what they call for instead: "they also suggest the need for a proper blend between field sales management and compensation control and identify important avenues for future research"Cravens, Ingram, LaForge & Young. (1993)
Grades: A, verified against the printed page of the primary source · B, primary source, text layer only · C, authoritative secondary · D, reported.
From the essay
Revenue operations & AI
Variable pay is a risk design when effort is hard to observe
When effort is hidden and output is uncertain, incentive intensity is conditional: separate observability, risk, uncertainty, and wider control.
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Why is variable sales pay a risk-sharing contract when rep effort is hard to observe?
Variable pay is a risk design when effort is hard to observe
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