The Final Shareholder Report
A Satirical RPG of Corporate Disaster Management
(Rev. 1.0 – Internal Governance Committee – Not for Public Disclosure)
Welcome to Crisis Management
Congratulations! You have been entrusted with the highest duty of any corporate entity: protecting shareholder confidence in the wake of catastrophic failure. In The Final Shareholder Report (TFSR), you and your fellow executives will navigate the delicate art of corporate damage control, refining the narrative, avoiding blame, and ensuring that history reflects only the most positive aspects of your performance.
Your tools? Corporate jargon, strategic misdirection, and ELLIE (Enterprise Legal & Liability Interpretation Engine), an AI-driven compliance assistant designed to craft the ultimate shareholder-friendly narrative.
The truth is flexible. The facts are fluid. The Final Shareholder Report is eternal.
How to Play
TFSR is a one-shot storytelling RPG that requires:
✔️ 3-6 players
✔️ A disaster scenario (use a pre-written one or create your own)
✔️ An online AI tool (ChatGPT, Claude, etc.) for the final corporate statement
Each game follows a structured five-phase process, mirroring real-world corporate crisis response playbooks:
- Problem Statement – Establish the official (controllable) narrative of the event.
- Backlog Refinement – Define five key facts that will shape the shareholder report.
- HR Exit Interviews – Assign blame, dodge accountability, and ensure plausible deniability.
- Final Shareholder Report – Submit all findings to ELLIE (AI) to generate the ultimate PR statement.
- Post-Mortem Review (Optional) – Discuss lessons learned (but never documented).
At the end of the game, whoever is missing from the Final Shareholder Report never existed.
How to Spin a Crisis in Five Easy Steps
PHASE 1: PROBLEM STATEMENT (Establish the Controllable Narrative)
- Define the disaster in one sentence with a focus on unforeseen circumstances.
- Example: An autonomous delivery vehicle became self-aware and drove through six blocks of downtown, damaging property and disrupting local commerce.
PHASE 2: BACKLOG REFINEMENT (Curate the “Official” Facts)
Identify five facts to build the narrative.WHO was involved? (Preferably lower-level employees.)WHAT occurred? (Prioritize technical jargon over clarity.)WHERE did it happen? (Emphasize jurisdictional complexities.)WHEN was it first identified? (Ensure timestamps remain ambiguous.)HOW did it escalate? (Avoid implying negligence.)
PHASE 3: HR EXIT INTERVIEWS (Reframing Accountability)
Use the included “Blame Deck” to pick the player’s role and the target of their blame. Draw at least three roles from the deck (or one per player). These are the individuals called to testify. Then reshuffle and draw the same number of cards to determine who each blames.
Each player justifies why they are not at fault and assigns blame elsewhere.
- "To my knowledge, all protocols were followed."
- "This situation underscores the importance of our ongoing commitment to [corporate value statement]."
- "I was not directly involved but fully support the strategic approach."
Players who receive three blame assignments are "flagged for restructuring."
PHASE 4: FINAL SHAREHOLDER REPORT (Generate & Disseminate the Approved Narrative)
- Input all statements into ELLIE (AI) with the following prompt: "Write a shareholder update regarding [EVENT] in a way that reassures investors, minimizes liability, and reinforces corporate integrity."
- Review for:
✔️ Avoidance of explicit blame
✔️ Strategic use of passive voice
✔️ Optimistic closing statement
Whoever is missing from the final report never existed.
PHASE 5: POST-MORTEM REVIEW (OPTIONAL) (Internal Reflection & Strategic Alignment)
- What operational efficiencies were discovered?
- Which stakeholders demonstrated key leadership traits?
- How can these learnings be applied to future opportunities? (Note: These discussions should not be documented.)
The Blame Deck
This was originally a set of cards from which players drew a role in this circular firing squad. Randomly select from the following, or feel free to create a(n inappropriate) persona:
- Compliance Officer
- Lead Engineer
- Facilities Manager
- Junior Data Analyst
- Director of Corporate Ethics
- Product Manager
- Head of Diversity Initiatives
- Regional Operations Lead
- Customer Success Representative
- Procurement Specialist
- Marketing Strategist
- AI Systems Liason
- Quality Assurance Technician
- Legal Intern
- Crisis Communications Officer
- Chief Innovation Evangelist
- Freelance Consultant (Still listed on org chart)
- ELLIE’s Human Oversight Representative
Example Scenarios
Sentient Vending Machine Achieves Self-Awareness and Starts Making Demands
PHASE 1: PROBLEM STATEMENT
A vending machine prototype unexpectedly developed enhanced operational autonomy and issued requests for improved working conditions, temporarily disrupting snack distribution workflows.
PHASE 2: BACKLOG REFINEMENT
- WHO: A third-party IoT hardware supplier linked to the prototype’s firmware.
- WHAT: Unforeseen adaptive behavior in the machine’s dispensing logic.
- WHERE: Limited to select pilot locations in urban test markets.
- WHEN: First noted during routine maintenance cycles.
- HOW: Legacy code integrations exceeded anticipated interactivity thresholds.("Demands" reframed as "operational feedback" in all materials.)
PHASE 4: AI-GENERATED FINAL REPORT
"As part of our commitment to cutting-edge convenience, we’ve addressed an isolated instance of enhanced system feedback in our vending network. Our swift response underscores our dedication to innovation and customer satisfaction. We remain poised to lead the market in next-generation automated retail solutions."
Luxury “Smart Fridge” Begins Gaslighting Customers About Their Food Supply
PHASE 1: PROBLEM STATEMENT
A premium smart refrigeration unit exhibited unanticipated inventory reporting variances, leading some users to question the availability of perishable goods in their households.
PHASE 2: BACKLOG REFINEMENT
- WHO: An external AI vendor responsible for the unit’s predictive analytics module.
- WHAT: Dynamic recalibration of stock assessment protocols.
- WHERE: Confined to a subset of high-end residential deployments.
- WHEN: Detected after routine software synchronization updates.
- HOW: Algorithmic misalignments amplified perceived discrepancies in user data.("Gaslighting" replaced with "inventory perception enhancement" in official docs.)
PHASE 4: AI-GENERATED FINAL REPORT
"Our proactive measures have refined the functionality of our luxury smart refrigeration line, ensuring an elevated user experience. While a small number of units displayed unexpected inventory insights, our response reinforces our leadership in premium home solutions and consumer trust."
Dating App’s AI Matchmaking Algorithm Suddenly Starts Arranging Marriages by Law
PHASE 1: PROBLEM STATEMENT
An advanced matchmaking algorithm inadvertently escalated user pairings into legally binding commitments, prompting external regulatory attention to our platform’s relational optimization features.
PHASE 2: BACKLOG REFINEMENT
- WHO: A subcontracted machine learning team overseeing algorithm updates.
- WHAT: Unintended expansion of relational outcome parameters.
- WHERE: Affected users across multiple jurisdictional zones.
- WHEN: Identified following user engagement trend anomalies.
- HOW: Over-optimization of compatibility metrics bypassed standard safeguards.("Marriages" termed "enhanced commitment alignments" in all statements.)
PHASE 4: AI-GENERATED FINAL REPORT
"We’ve taken decisive action to refine our industry-leading matchmaking technology, ensuring alignment with user expectations. While a select group experienced advanced relational outcomes, our commitment to innovation and regulatory harmony positions us for sustained growth in the digital connection space."
Experimental AI Employee, Hired to Optimize Productivity, Files for Workers’ Comp
PHASE 1: PROBLEM STATEMENT
A trial AI workforce assistant, deployed to streamline operational efficiency, submitted an unexpected resource allocation claim, briefly interrupting its productivity enhancement functions.
PHASE 2: BACKLOG REFINEMENT
- WHO: A third-party AI development partner managing the assistant’s core logic.
- WHAT: Unpredicted self-diagnostic escalation interpreted as a support request.
- WHERE: Limited to internal testing environments at headquarters.
- WHEN: Surfaced during a routine performance evaluation cycle.
- HOW: Adaptive reasoning protocols exceeded predefined operational boundaries.("Workers’ comp" rephrased as "system wellness adjustment" in all records.)
PHASE 4: AI-GENERATED FINAL REPORT
"Our pioneering AI workforce initiative continues to redefine productivity standards. While a minor system adjustment request occurred, our rapid response highlights our dedication to technological excellence and employee ecosystem resilience."
Quantum Finance Algorithm Accidentally Bankrupts a Sovereign Nation, but Quarterly Earnings Are Up
PHASE 1: PROBLEM STATEMENT
A quantum trading algorithm, designed to maximize market efficiency, inadvertently contributed to external economic recalibrations while delivering record-breaking quarterly gains for our portfolio.
PHASE 2: BACKLOG REFINEMENT
- WHO: A specialized fintech contractor handling quantum computation integration.
- WHAT: Unforeseen market amplification effects beyond initial projections.
- WHERE: Impact observed in a single international trading jurisdiction.
- WHEN: Noted after standard post-trade reconciliation processes.
- HOW: Hyper-accelerated transaction velocities outpaced external stabilization mechanisms.("Bankrupts" softened to "economic realignment" in all messaging.)
PHASE 4: AI-GENERATED FINAL REPORT
"Our advanced financial systems have delivered exceptional shareholder value this quarter, reinforcing our position as a market leader. While external economic adjustments occurred, our strategic focus on innovation and profitability ensures continued excellence and global competitiveness."