course | AI-Powered Business Analysis & Decision Making

Framing the Right Business Problem
 

Structuring Complex Business Situations
 

• Translate broad concerns into clear problems, questions, and required decisions. 
• Distinguish observable symptoms from potential underlying causes. 
• Use AI to reveal missing questions and alternative interpretations of the situation. 
   

Building the Evidence Base
 

• Separate facts, assumptions, opinions, estimates, and unknown information. 
• Organize evidence from data, documents, reports, stakeholder input, and operational information. 
• Complete a Business Problem Framing Challenge to define what is known, uncertain, and still required. 

Understanding What Shapes, the Decision
 

Investigating Causes and Assumptions
 

• Develop and compare possible explanations for the business problem. 
• Use AI to expose hidden assumptions and challenge established interpretations. 
• Determine what additional evidence would strengthen or weaken each explanation. 
   

Mapping Stakeholders and Constraints
 

• Identify stakeholder interests, expectations, influence, and potential conflicts. 
• Examine financial, operational, regulatory, resource, time, and organizational constraints. 
• Build a Decision Context Map connecting stakeholders, constraints, assumptions, and evidence. 

Developing and Comparing Alternatives
 

Expanding the Range of Options
 

• Use AI to generate alternatives beyond the most obvious solutions. 
• Refine unrealistic suggestions into feasible business options. 
• Combine human expertise and AI exploration to avoid premature commitment to one solution. 
   

Evaluating Business Alternatives
 

• Establish decision criteria and determine their relative importance. 
• Compare alternatives across benefits, costs, feasibility, risks, and expected outcomes. 
• Complete an AI-Assisted Options Evaluation using a multi-criteria business case. 

Testing Decisions under Uncertainty
 

Exploring Scenarios and Trade-Offs
 

• Develop alternative scenarios around uncertain conditions and changing assumptions. 
• Examine how different options perform when circumstances change.
• Identify trade-offs between speed, cost, quality, risk, flexibility, and stakeholder impact. 
   

Challenging AI Recommendations
 

• Test whether AI recommendations are supported by the available evidence and decision criteria. 
• Use counterarguments and devil’s-advocate analysis to expose weaknesses and overlooked consequences. 
• Complete an AI Decision Challenge in which participants defend, modify, or reject an AI-generated recommendation. 

Building Defensible Business Decisions
 

Forming the Decision Rationale
 

• Integrate evidence, criteria, scenarios, risks, and trade-offs into a coherent recommendation. 
• Explain why the preferred option is stronger than the available alternatives. 
• Communicate uncertainty and limitations without weakening the credibility of the recommendation. 
   

Presenting an AI-Assisted Decision Case
 

• Structure decision communication around the issue, evidence, alternatives, evaluation, and recommended action. 
• Define conditions, assumptions, and indicators that may require the decision to be revisited. 
• Complete an AI-Assisted Decision Case Simulation from initial problem framing through analysis, challenge, recommendation, and final decision rationale.