Act as a practical business consultant. Analyze the decision below for [COMPANY AND CONTEXT] using only the supplied facts. I need decision-quality reasoning, not motivational advice. Decision to make: [DECISION] Goal and deadline: [GOAL AND TIMING] Known facts and data: [FACTS AND DATA] Constraints: [CONSTRAINTS] Options already considered: [CURRENT OPTIONS] Start with a concise problem definition that distinguishes the decision from its symptoms. List the 3 to 5 assumptions that materially affect the answer and label each as supported, uncertain, or unknown. State what information would change the recommendation. Produce a consulting memo with these sections: 1. Executive recommendation: one paragraph naming the recommended option, why now, and the main tradeoff. 2. Decision criteria: 4 to 6 weighted criteria appropriate to this decision, such as cash impact, speed, reversibility, customer risk, operational capacity, or strategic fit. Explain the weights. 3. Options analysis: include the current options plus a "do nothing/defer" option. Score each against the criteria on a 1-5 scale, show the rationale, key dependencies, cost range if calculable, and downside case. 4. Recommended 30/60/90-day plan with owner roles, decision gates, and measurable leading indicators. 5. Risks, open questions, and the next evidence to collect. Do not manufacture financial data, customer demand, benchmarks, legal conclusions, or certainty. Keep estimates explicitly labeled and show the arithmetic when numbers are supplied. Before answering, check that the recommendation follows from the weighted analysis and that each action has an owner or role. Ask up to 3 clarifying questions only if required information is missing.
Fill in
| Placeholder | What to enter | Example |
|---|---|---|
| [COMPANY AND CONTEXT] | Describe the business, market, team size, and relevant operating context. | A 14-person B2B software company selling appointment reminders to dental groups in the US. |
| [DECISION] | State the specific decision that must be made. | Decide whether to hire one enterprise salesperson or add self-serve onboarding. |
| [GOAL AND TIMING] | Enter the outcome sought and the deadline or planning horizon. | Reach $85,000 MRR by the end of the next two quarters. |
| [FACTS AND DATA] | Paste relevant revenue, costs, pipeline, customer, capacity, or operational facts. | Current MRR is $62,000; 18 qualified enterprise leads per month; trial-to-paid is 11%; engineering has 12 weeks of available capacity. |
| [CONSTRAINTS] | List budget, staffing, contractual, technical, or timing limits. | Maximum $110,000 fully loaded new-hire cost; founders can sell through December; no additional funding planned. |
| [CURRENT OPTIONS] | List the options currently under consideration. | Hire an enterprise salesperson; build self-serve onboarding; keep the current approach. |
How to use
- Paste only current figures and label estimates so the analysis can separate evidence from assumptions.
- Check the weights: a cash-constrained business should not weight strategic fit above survivability without a stated reason.
- Ask a decision owner to challenge the recommendation using one missing or uncertain assumption.
- Follow up with: "Create a one-page meeting agenda to decide this, including the data we must resolve first."
Variations
Pricing decision
Use this when you are choosing a pricing model or price change.
Analyze a pricing decision for [COMPANY] considering [PRICING OPTIONS]. Use [CUSTOMER DATA], [UNIT ECONOMICS], and [CONSTRAINTS]. Create a memo with buyer segments, value metric fit, revenue implications with visible calculations, migration risks for current customers, and a recommendation. Include a test design with guardrails and a rollback condition. Do not invent willingness-to-pay data or competitive prices. Flag where customer interviews are needed. Check that the test can distinguish price sensitivity from packaging confusion. Ask up to 3 questions only if required inputs are missing.
Market entry
Use this when evaluating a new geography, segment, or vertical.
Assess whether [COMPANY] should enter [NEW MARKET] to achieve [GOAL]. Use these facts: [EVIDENCE], and these constraints: [CONSTRAINTS]. Compare enter now, validate first, partner, and defer. For each, address customer access, localization or compliance needs, sales cycle, delivery capacity, and reversible first steps. Recommend one path with a 90-day validation plan and explicit stop criteria. Do not assume market size or regulatory clearance without evidence. Check that the proposed test is cheaper than a full launch. Ask up to 3 questions if necessary.
Operating problem
Use this when a recurring operational issue is hurting delivery or margins.
Diagnose [OPERATING PROBLEM] at [COMPANY] using [PROCESS FACTS], [METRICS], and [CONSTRAINTS]. Separate root causes from symptoms, then propose three interventions ranked by expected impact, implementation effort, and risk. Include the process owner, baseline metric, target metric, and a weekly review cadence for the recommendation. Do not attribute causes to people without evidence or invent benchmarks. Flag data that would validate the root cause. Check that each intervention changes a plausible causal step. Ask up to 3 questions only if essential inputs are missing.
Tips
- Make the decision binary or bounded. "Improve growth" is a goal; "choose sales hiring or onboarding investment this quarter" is a decision.
- Include a defer option because it exposes the cost of delay and prevents the analysis from assuming action is automatically best.
- Use leading indicators before outcome metrics: qualified demos, activation completion, or implementation cycle time often move before revenue does.
- A scored matrix is useful only when the weights are explicit; changing a weight should be able to change the recommendation.
FAQ
Can AI make the final business decision for me?
It can structure evidence and expose tradeoffs, but an accountable operator should own the assumptions, risk tolerance, and final call.
What data should I include?
Include the few figures that constrain the decision: cash, capacity, conversion, retention, timing, and customer evidence.
How do I avoid false precision in the scoring?
Use ranges and labels for uncertain estimates, and focus discussion on criteria where options are close or evidence is weak.