Métodos cuantitativos · Ciencias de la decisión

Decide Under Risk — Lutèce Mobility's €90M SiC Bet

A four-round, advanced decision-sciences simulation set inside the investment committee of Lutèce Mobility SA, a Lyon-based mid-cap industrial-tech firm (€620M revenue, 9% EBIT, €140M net debt).

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Sobre la simulación

A four-round, advanced decision-sciences simulation set inside the investment committee of Lutèce Mobility SA, a Lyon-based mid-cap industrial-tech firm (€620M revenue, 9% EBIT, €140M net debt). A German rail OEM — 31% of revenue — will dual-source unless Lutèce closes a silicon-carbide (SiC) technology gap before a binding 30 June 2026 supplier decision.

The committee controls a €90M discretionary envelope and three mutually exclusive paths with disclosed odds: escalate the in-house SiC program (€60M; 55% +€130M NPV / 30% +€25M / 15% −€70M write-off), license a proven US design (€45M; 85% +€70M / 15% −€10M), or walk away and defend the legacy silicon line (€0; certain +€15M but the OEM dual-sources, putting 31% of revenue at structural risk). €22M is already sunk into the in-house program, and a −€70M write-off would breach a 3.0x net-debt/EBITDA covenant.

Operationalizing Enrico Diecidue's research on aspiration levels, anticipated regret, and risk, the simulation forces you to (1) set an explicit aspiration line and compute expected value per path, (2) build a regret matrix and size each path's worst-case covenant exposure, (3) commit under the live deadline and react to a leaked signal that cuts Path A's on-time probability from 55% to 45% — hold, switch, or hedge (€75M combined) — and (4) escalate or cut losses on an interim result drawn from your own committed odds, then defend the decision trail.

The math rewards decision hygiene — a consistent aspiration, EV-and-regret-aware choice, a pre-set switch trigger, and covenant discipline — and punishes the five classic errors: computing EV with no aspiration, sunk-cost escalation, ignoring maximum regret, hedging into a covenant breach, and flinching on the signal instead of updating.

Final KPIs track Decision Quality (process consistency), Expected Value captured, Anticipated Regret, and Covenant Headroom.

Para quién es

Una simulación avanzada para participantes acostumbrados a trabajar con los principales marcos y dilemas de la materia, pensada para formación de directivos y profesionales con experiencia.

Cómo funciona una sesión

  1. El docente crea una sesión desde el panel de Eureka e invita a los participantes.
  2. Los participantes juegan 4 rondas. En cada una envían sus decisiones y la simulación calcula los resultados.
  3. El docente sigue el progreso y los resultados de cada participante desde el panel, y usa los resultados de la clase para el debriefing.

Decisiones que toman los participantes

Las decisiones que toman los participantes durante la simulación:

  • Set your aspiration line — the NPV outcome below which this committee calls the decision a failure (€M)
  • Which reference point should anchor the aspiration?
  • After computing expected value, which path has the highest EV?
  • From your regret matrix, which path MINIMIZES anticipated (probability-weighted) regret?
  • Which path carries the LARGEST maximum regret (the worst foregone-best outcome)?
  • Which path, in its WORST state, breaches the 3.0x net-debt/EBITDA covenant?
  • When EV-maximization and minimum-regret point to different paths, which does this committee weight?
  • Commit the committee to ONE path under the deadline
  • Did you set a PRE-COMMITTED switch trigger in advance, or react to the leaked number?
  • How do you treat the 30 June OEM deadline?

Qué siguen los participantes

Lo que los participantes siguen en pantalla a medida que avanzan las rondas:

  • Committee Decisions This Round
  • Decision Trail
  • Decision-Quality vs EV & Regret Trajectory

Temas que cubre

Diseñada para asignaturas de Ciencias de la decisión.

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