Problem Solving Prompts

(Problem solving is a goal-oriented process triggered by a specific gap between "where we are" and "where we need to be."
It means:
remove blockers
restore delivery baseline
generate viable paths forward)

1. Structured Option Generator

• Purpose: To convert the AI from a single-answer generator into a strategy enumerator, producing multiple solution paths so decision-makers can compare options rather than react to a single recommendation.

• Prompt: “You are acting as a senior program delivery advisor.
  
  Context
  Project: [PROJECT NAME]
  Objective: [GOAL OR DELIVERABLE]
  Constraint(s): [BUDGET / TIME / REGULATORY / RESOURCE LIMITS]
  Current problem: [CLEAR PROBLEM STATEMENT]
  
  Task
  Generate 3-7 distinct solution paths to address the problem.
  
  For each path provide:
  1. Description of the approach
  2. Key actions required
  3. Advantages
  4. Risks or unintended consequences
  5. Resource implications
  6. Political or stakeholder resistance likely
  7. Situations where this option is the best choice
  
  Then rank the options by:
  - fastest recovery
  - lowest risk
  - lowest stakeholder resistance
  
  Output in a comparison table.”

• Technique:
  Decision Menu Facilitation
  - Generates multiple solution paths so the PM facilitates choice rather than advocating a single option
  Executive-Ready Output
  - A comparison table converts the analysis into a format suitable for steering committee decisions

2. Dependency Chain Unwinder

• Purpose: To identify the true root constraint by distinguishing critical dependencies from downstream symptoms.

• Prompt: “Act as a systems thinker embedded in a [industry/sector, e.g. "infrastructure programme"].
  The following task or milestone is blocked: [describe blocked item].
  
  Map the full upstream and downstream dependency chain.
  Identify which dependency is the true root constraint vs. which ones are symptoms.
  
  Then propose the minimum viable intervention - the smallest change that unblocks the most.
  Flag any fix that solves the immediate problem but creates a downstream fragility.”

• Technique:
  Constraint Triage
  - It enforces "Theory of Constraints" logic, preventing the waste of energy on downstream symptoms that resolve themselves once the primary upstream bottleneck is cleared.
  Fragility Detection
  - It moves beyond simple list-making to identify "minimal interventions," while flagging quick fixes that solve a current block but create long-term structural weakness.

3. Constraint-Driven Recovery Planner

• Purpose: To manage "Red" projects (RAG) by providing tiered recovery options that mirror real-world decision spaces and hard constraints.

• Prompt: “Act as a project recovery consultant.
  
  Project type: [IT / INFRASTRUCTURE / PRODUCT / TRANSFORMATION]
  Current status: [SUMMARY]
  Problem: [SCHEDULE DELAY / COST OVERRUN / SCOPE BLOCKER]
  
  Constraints:
  - Deadline: [DATE]
  - Budget flexibility: [NONE / LOW / MEDIUM / HIGH]
  - Resource flexibility: [LOW / MEDIUM / HIGH]
  - Political sensitivity: [LOW / MEDIUM / HIGH]
  
  Task:
  Produce a recovery strategy with three tiers:
  
  1. Conservative recovery
  2. Balanced recovery
  3. Aggressive recovery
  
  For each tier include:
  - specific actions
  - timeline impact
  - cost impact
  - operational risk
  - stakeholder reaction risk
  
  End with a recommendation based on the constraints.”

• Technique:
  Scenario Banding
  - Uses tiered recovery strategies (Conservative / Balanced / Aggressive) to present realistic decision options instead of a single recommendation.
  Constraint-Hardened Logic
  - It forces the model to reason within specific boundaries of budget and political sensitivity, ensuring the output mirrors a real recovery board paper rather than generic advice.

4. Second-Order Consequence Analyser

• Purpose: To challenge sunk-cost momentum and pre-commitment bias by surfacing the "hidden" downstream risks of a solution that appears successful on the surface.

• Prompt: “Evaluate the following proposed solution:
  
  [PROPOSED PLAN OR DECISION]
  
  Context:
  Project: [TYPE]
  Stakeholders: [KEY GROUPS]
  Dependencies: [SYSTEMS / TEAMS / SUPPLIERS]
  
  Analyse the decision in three layers:
  1. Immediate operational impact
  2. Second-order consequences (new risks, dependencies, workload shifts)
  3. Long-term strategic implications
  
  Identify:
  - hidden costs
  - organisational friction
  - risks that would likely emerge 2–6 months later
  
  Conclude with a risk-adjusted viability score from 1–10.”

• Technique:
  Decision Validation Scrutiny
  - Surfaces second-order risks such as workload shifts and new dependencies.
  Temporal Calibration
  - Forces evaluation of risks that emerge 2–6 months after implementation, not just immediate impacts.

5. Resource Reallocation Pressure Test

Political Feasibility

• Purpose: To evaluate the political feasibility of recovery options by modeling resource shifts that account for organisational friction and stakeholder power rather than just technical merit.

• Prompt: “We are [X weeks] into a [type] project with the following constraints: [budget envelope / team capacity / fixed deadline].
  The project is currently [status, e.g. "amber on scope, green on budget"].
  
  Model three resource reallocation scenarios that could recover schedule without increasing cost.
  For each, show
  the sequencing logic,
  the role most affected,
  any 'technical debt' incurred, and
  whether the trade is reversible or locks us into a path.
  
  Present the options in order of political ease, not just technical merit.”

• Technique:
  Political Feasibility Modelling
  - Forces options to be ranked by organisational friction and stakeholder resistance, not just technical optimisation.
  Path-Lock & Debt Awareness
  - By highlighting reversibility and technical debt, it distinguishes between temporary shifts and permanent structural changes, helping PMs protect their future maneuverability.

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