Value of Information Assessment Worksheet

{ "Title": "Value of Information Assessment Worksheet", "IntroductionHtml": "

Purpose: Quickly estimate whether running an analysis or experiment is likely to be worth the cost. This worksheet helps you prioritize analytic work by focusing on expected decision value rather than raw curiosity.

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How it works: Enter simple monetary estimates and a probability that new information will change your decision. Use the formulas below to judge whether the expected benefit of being able to change the decision exceeds the cost of collecting the information.

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Key formulas (use the same currency for all money fields):

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• Difference in expected payoff if decision changes = Alternative EV − Current EV
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• Expected value of changing decision = (Alternative EV − Current EV) × (Probability change as a fraction)
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• Net expected value of information ≈ Expected value of changing decision − Cost of information − (Probability change × Implementation cost if changed)
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• Simple break-even probability (ignoring implementation cost) = Cost of information / (Alternative EV − Current EV). If the required probability is lower than your estimate of chance that the analysis will change the decision, the analysis is likely worth running.
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Worked example — pricing decision:

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• Current EV = 10,000
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• Alternative EV = 12,000
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• Difference = 2,000
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• Estimated probability the experiment/analysis will change the decision = 30% (0.30)
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• Cost of analysis = 200
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• Implementation cost if changed = 0
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• Expected value of changing decision = 2,000 × 0.30 = 600
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• Net expected value of information = 600 − 200 = 400 → positive, so running the analysis appears warranted.
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• Break-even probability = 200 / 2,000 = 0.10 (10%)
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Notes: These estimates are only as good as the inputs. Use conservative probability estimates when uncertainty is high. If implementation constraints, timing, stakeholder incentives, or decision rules are unclear, treat the result as exploratory rather than definitive.

", "SubmitLabel": "Save assessment", "SuccessMessage": "Assessment saved. Return later to compare or refine this assessment.", "DataType": "VoIAssessment", "SchemaVersion": "1.0", "Fields": [ { "Key": "assessment_title", "FieldType": "text", "Label": "Assessment name", "HelpText": "Short title for this assessment (e.g., 'Q2 pricing test').", "Required": false, "Placeholder": "Optional" }, { "Key": "current_expected_value", "FieldType": "number", "Label": "Current expected value (monetary)", "HelpText": "Expected payoff of the decision if you act now (use same currency for all entries).", "Required": true, "Placeholder": "e.g., 10000" }, { "Key": "alternative_expected_value", "FieldType": "number", "Label": "Alternative expected value (monetary)", "HelpText": "Expected payoff of the best alternative action if the decision changes.", "Required": true, "Placeholder": "e.g., 12000" }, { "Key": "probability_change_percent", "FieldType": "number", "Label": "Probability information will change the decision (%)", "HelpText": "Estimate the chance that the new analysis or experiment will cause you to choose the alternative. Enter a number from 0 to 100.", "Required": true, "Min": 0, "Max": 100, "Placeholder": "e.g., 30" }, { "Key": "cost_of_information", "FieldType": "number", "Label": "Cost of information / analysis (monetary)", "HelpText": "Direct cost to run the analysis or experiment (lab fees, tooling, analyst time, incentives, etc.).", "Required": true, "Placeholder": "e.g., 200" }, { "Key": "implementation_cost_if_changed", "FieldType": "number", "Label": "Implementation cost if decision changes (monetary)", "HelpText": "Estimated one-time cost to implement the alternative if you change your decision. Leave 0 if negligible.", "Required": false, "Placeholder": "e.g., 1000" }, { "Key": "notes", "FieldType": "textarea", "Label": "Notes, assumptions, and key uncertainties", "HelpText": "Record the assumptions and evidence behind your estimates so others can review or revise them.", "Required": false, "Placeholder": "Assumptions about demand, supplier behavior, sample size, etc." } ] }