Introduction to Modern Business Analysis

Chapter 1: Digital Evolution of Business Analysis

• Overview of the modern business analysis playbook: digital, data-centric, AI-driven, and Lean/Agile.
• Shift the business analyst mindset from requirements documenter to value driver.
• Contrast traditional and digital BA practices: handoffs versus cross-functional collaboration, process focus versus customer and data focus, and reporting versus predicting and prescribing.
• Introduce value management and the balance between stakeholder needs and the resources required to deliver sustainable value.
• Clarify strategic product ownership and tactical business analysis responsibilities.
• Connect product vision, themes, epics, stories, iteration planning, and release decisions.
• Explore collaboration networks, Product Owner–BA partnership, and business analysis agility.
• Use VUCA—volatility, uncertainty, complexity, and ambiguity—to explain the need for adaptive BA practices.
• Develop an adaptive BA mindset through cultural change, critical thinking, discipline, team focus, and collaborative tools.

Chapter 2: Strategy and Data-Driven Decisions

• Use data-driven analysis to move from reporting numbers to influencing decisions.
• Define meaningful KPIs that connect directly to business outcomes.
• Identify decision-worthy patterns by asking “so what?” and linking data to human impact.
• Build persuasive data stories using the Context–Insight–Action structure.
• Apply practical rules for actionable data: lead with the insight, make it human, show the gap, focus each message, and end with a clear ask.
• Develop business need statements and calls to action that establish urgency and measurable targets.
• Use SCAMPER to expand product ideas and T-shirt sizing to compare and prioritize them.
• Progressively elaborate the current and future state from themes and epics to user stories and release waves.
• Differentiate the strategic product roadmap from the tactical product backlog.

Chapter 3: AI-Enabled Analysis

• Identify practical uses of AI across requirements, analysis, insights, and stakeholder communication.
• Generate and refine user stories, acceptance criteria, and edge cases with AI assistance.
• Summarize stakeholder interviews and transcripts into goals, pain points, and supporting evidence.
• Draft business-case narratives that connect baselines, targets, expected outcomes, and return on investment.
• Develop prompts for common business analysis activities.
• Apply simple, more complex, and complex prompt-engineering frameworks.
• Use AI with the SCAMPER technique to extend and test a product-feature brainstorm.
• Compare prompt approaches and apply business analyst judgment to evaluate AI-generated outputs.

Chapter 4: Customer-Centric Analysis

• Use customer-centric and experience-driven analysis to identify friction and prioritize improvements.
• Create research-based personas that represent distinct user goals, behaviors, needs, and constraints.
• Trace the customer journey across awareness, consideration, engagement, use, and advocacy.
• Identify touchpoints, handoffs, effort spikes, trust gaps, pain points, and improvement opportunities.
• Apply structured process flows to strengthen clarity, accountability, repeatability, scalability, and technology integration.
• Use user journey modeling to walk through a process from the customer’s perspective.
• Use user story mapping to organize requirements visually around the journey.
• Slice the story map into current, next, later, and future release priorities.

Chapter 5: Agile and Product Thinking

• Differentiate the roles of Business Analyst, Product Owner, and Product Analyst.
• Focus product decisions on value delivered rather than requirements completed.
• Use progressive elaboration to refine epics into smaller, actionable stories near the top of the product backlog.
• Prioritize backlog items using MoSCoW analysis.
• Write user stories from the user’s point of view using role, capability, and value.
• Apply the Three C’s: Card, Conversation, and Confirmation.
• Develop measurable acceptance criteria and distinguish user stories from technical tasks.
• Assess story readiness using Definition of Ready and INVEST criteria.
• Estimate stories using relative estimation, Fibonacci sequencing, and T-shirt sizing.
• Connect the product backlog’s “what” to the sprint backlog’s “how.”
• Define non-functional requirements covering regulatory, business-rule, and IT quality constraints.
• Apply lean documentation standards: document with intent and avoid unnecessary artifacts.

Chapter 6: Building Collaborative Intelligence

• Use influence without authority to align stakeholders around shared outcomes.
• Translate between customer needs, business priorities, and technical delivery.
• Apply executive storytelling to make data understandable, relevant, and actionable.
• Build collaborative intelligence through inclusive participation, inquiry, shared goals, joint decisions, and collective ownership.
• Recognize the characteristics of effective collaborators: responsive, responsible, progressive, and persuasive.
• Practice listening, welcoming feedback, addressing conflict constructively, and seeking solutions rather than blame.
• Use facilitated collaboration to convert diverse viewpoints into stronger analysis and business capability.

Chapter 7: Summary—Building the Digital BA Practice

• Synthesize digital BA practice, value management, data storytelling, AI prompting, customer-centric analysis, product thinking, and collaborative leadership.
• Reinforce the shift from documenter to value driver.
• Use measurable outcomes, customer evidence, and data signals to guide decisions.
• Apply Lean/Agile practices to reduce handoffs, eliminate waste, and deliver value incrementally.
• Identify personal upskilling priorities and next steps for expanding influence.
• Use the Digital BA Toolkit to transfer course practices into day-to-day work.

Course Activities

• Discuss how the business analyst role is changing within participants’ organizations.
• Assess current practices against the Adaptive BA and Lean/Agile BA mind maps.
• Develop a business need statement and data-driven call to action.
• Brainstorm and size capabilities using SCAMPER and T-shirt sizing.
• Create and test AI prompts for practical business analysis assignments.
• Use AI and SCAMPER to extend a product-feature brainstorm.
• Build a persona-based customer journey and identify improvement opportunities.
• Write, refine, and prioritize user stories with acceptance criteria and INVEST.
• Complete a capstone collaboration mind map, identify strengths and gaps, and rank improvement priorities.

Participants will use the course activities, collaborative discussions, workbook resources, prompt frameworks, templates, and Digital BA Toolkit to practice the concepts and develop a practical plan for applying them in their organizations.