How To Use Retailflow

AI-Driven Business Innovation Masterclass

How to Use the RetailFlow Case Study

A guide for getting maximum value from today’s exercises

What is RetailFlow?

RetailFlow Inc. is a fictional mid-market omnichannel retailer facing real AI investment decisions. Today, you’ll step into the shoes of RetailFlow’s leadership team to practice strategic frameworks and make tough investment choices.

Why Use a Case Study?

✅ Safe learning environment – Practice frameworks without IP concerns, NDAs, or company politics ✅ Shared foundation – Everyone analyzes the same information, enabling rich debate ✅ Strategic focus – Think objectively without organisational baggage ✅ Proven approach – Top business schools and strategy firms use case-based learning

RetailFlow Quick Facts

Industry Omnichannel Retail (Apparel & Home Goods)
Revenue $450M annually
Employees 2,400
Market Position Mid-market, Western US, being squeezed by online-first competitors
AI Maturity Level 2-3 (basic data collection, limited analytics, no AI in production)
Budget Challenge $2M available for AI, but $2.95M in proposals

The Strategic Dilemma

RetailFlow’s CEO (from Amazon) wants transformational AI. The CFO wants clear ROI. The Board wants competitive parity with online retailers. Customers want better experience.

Your job today: Help RetailFlow balance these competing demands with limited resources.

How to Engage with RetailFlow

✅ DO:

  • Treat RetailFlow’s challenges as real – They mirror what you face
  • Debate vigorously – Challenge assumptions, defend your positions
  • Apply the frameworks rigorously – Practice the evaluation criteria
  • Ask “What if?” – Explore different scenarios and trade-offs
  • Connect to your experience – “RetailFlow faces X… we face Y…”

❌ DON’T:

  • Dismiss it as “just a case study” – The challenges are authentic
  • Rush to answers – The struggle with trade-offs IS the learning
  • Ignore AI-specific criteria – That’s the whole point of today
  • Make it about YOUR company – Save that for Personal Action Planning

The RetailFlow Learning Arc

Morning: Learn the Frameworks

  • Map RetailFlow’s AI initiatives on the Transformation Matrix
  • Assess RetailFlow’s data readiness
  • Identify RetailFlow’s competitive threats and opportunities
  • Reflection: “How does RetailFlow compare to my organisation?”

Afternoon: Make the Decision

  • Evaluate RetailFlow’s 4 competing AI proposals:
    • AI Customer Service Chatbot ($525K) – Low ROI, low risk
    • Dynamic Pricing Optimization ($1.3M) – High ROI, high risk
    • AI Inventory Optimization ($1.25M) – High ROI, over budget
    • Fraud Detection System ($1.05M) – Highest ROI, data not ready
  • Allocate RetailFlow’s $2M budget using traditional AND AI-specific criteria
  • Discover how AI evaluation differs from traditional IT
  • Reflection: “What would MY executive team decide?”

End of Day: Apply to YOUR Organisation

  • Create your Personal Action Plan
  • Translate RetailFlow lessons to your context
  • Plan Monday actions based on what you learned

The Four Questions to Keep Asking

As you work through RetailFlow’s challenges, constantly ask yourself:

1. “How is this similar to my company’s situation?”

  • Data quality issues?
  • Competing AI proposals?
  • Budget constraints?
  • Executive stakeholder tensions?

2. “What challenges does RetailFlow face that we also face?”

  • Being squeezed by AI-native competitors?
  • Unclear which AI initiatives to prioritize?
  • Data readiness gaps?
  • Pressure for quick wins vs. long-term transformation?

3. “Would my executive team make the same trade-offs?”

  • Would our CEO overrule the committee?
  • Would our CFO accept high ROI with high risk?
  • Would our Board prioritize defensive moves or offensive plays?

4. “What would I do differently?”

  • Different budget allocation?
  • Different evaluation criteria?
  • Different risk tolerance?
  • Different stakeholder management?

RetailFlow’s Four AI Proposals at a Glance

Initiative Budget Request Traditional ROI Key AI Challenges
Chatbot $525K 92% ✅ Data ready, ✅ Low risk, ⚠️ Lowest ROI
Dynamic Pricing $1.3M 253% ⚠️ Over budget, ⚠️ Ethical risk (price discrimination)
Inventory $1.25M 264% ⚠️ Slightly over budget, ⚠️ Needs explainability
Fraud Detection $1.05M 315% ⚠️ Data not ready, ⚠️ High bias risk

Total requested: $2.95M Total available: $2.0M You cannot fund everything.

What Makes a Good RetailFlow Analysis?

Excellent Analysis Includes:

✅ Using ALL the frameworks – Transformation Matrix, Data Value Pyramid, Three Horizons, AI Investment Model ✅ Considering BOTH traditional AND AI-specific criteria – ROI matters, but so does data readiness, ethics, explainability ✅ Making explicit trade-offs – “We’re choosing X over Y because…” ✅ Articulating risks – “This could fail if…” ✅ Building a balanced portfolio – Not just “best ROI wins” ✅ Showing your thinking – “Our logic is…”

Weak Analysis Looks Like:

❌ Only looking at traditional ROI – “Highest ROI wins” ❌ Ignoring AI-specific risks – “We’ll deal with bias later” ❌ Trying to fund everything – “We’ll find more money somehow” ❌ Not using the frameworks – “This just feels right” ❌ Defending choices weakly – “Everyone else is doing AI”

How This Connects to YOUR Real Work

During the Dragon’s Den Investment Simulation

If you’re on the Investment Committee: - Use the same rigor you’d use for a real $2M decision - Ask the tough questions your CFO would ask - Consider: “Would I approve this project at MY company?”

If you’re on a Project Team: - Pitch with the same passion you’d use for your real AI proposal - Anticipate the objections your executives would raise - Consider: “Have I addressed the AI-specific criteria?”

In Your Personal Action Plan

You’ll translate today’s RetailFlow lessons to YOUR context: - Map YOUR AI maturity level - Assess YOUR portfolio balance - Evaluate YOUR pending AI investment using today’s frameworks - Plan YOUR Monday actions

Common Questions

“RetailFlow is a retailer. I’m in [healthcare/finance/manufacturing]. Does this still apply?”

Yes. The strategic frameworks and AI-specific evaluation criteria are universal. The competitive dynamics RetailFlow faces—being squeezed by AI-native players, struggling with data readiness, balancing quick wins vs. transformation—are industry-agnostic.

“RetailFlow seems simpler than my organisation. Is this too basic?”

That’s the point. If you can’t apply these frameworks to a clean case study, you won’t be able to apply them to your messy reality. We’re building muscle memory first, then transferring to complexity.

“Can I share RetailFlow details publicly after the course?”

Absolutely. RetailFlow is fictional and designed for teaching. Feel free to use it as an example when explaining these frameworks to your team. (Just don’t share other participants’ company details!)

“What if our Dragon’s Den committee makes a ‘wrong’ decision?”

There is no one right answer—that’s the point. Different risk tolerances, strategic priorities, and stakeholder pressures lead to different valid decisions. The learning is in the PROCESS of evaluation, not the final outcome.

Key Takeaway

RetailFlow is your practice field.

Today you’ll make decisions without career risk, political pressure, or real-money consequences. You’ll struggle with the trade-offs, debate the criteria, and maybe choose wrong—and that’s PERFECT.

Because tomorrow you go back to your organisation where the stakes are real. And you’ll be ready.

Get Started

Your RetailFlow journey begins now:

  1. Read the RetailFlow Company Overview carefully
  2. Identify which of the 4 AI initiatives most resembles something you’re evaluating
  3. Start thinking: “What would I do with $2M and these four proposals?”
  4. Get ready to make some tough decisions

Welcome to RetailFlow. Let’s make some strategic AI investments.