Before the Breakthrough

Authors:

Dr. T. T. Niranjan

Academic Partner:

LEVEL

Undergraduate, MBA, Executive Ed, Graduate

TYPE

Single Player

DURATION

80 mins

DISCIPLINE

Operations Management, Business Analytics / Decision Sciences

Introduction

You are the capacity adviser to VIB, an Indian vaccine manufacturer racing to be ready for Novishield, a COVID-era vaccine that has not yet been approved. Each round you decide how many plants to build, where every plant is ₹50 billion of dedicated capacity that pays off only if both approval and demand arrive. Approval is a probability and demand is only a set of disagreeing forecasts. Build too little and you strand a market you could have served; build too much and the fixed cost sinks you. You are judged on the profit your commitments earn once the truth is revealed. What the reveal shows is that the forecast-optimal build and the profitable one are rarely the same, and that deep uncertainty rewards restraint.

Learning Objectives

Apply the newsvendor model to a repeated capacity-investment decision under demand uncertainty.
Compute the critical fractile from underage and overage costs to derive an optimal quantity.
Evaluate approval probability and price terms to set the underage margin driving each decision.
Aggregate twelve disagreeing forecasts into a mean and standard deviation for the order quantity.
Assess the trade-off between stranded demand and sunk fixed cost across irreversible plant commitments.

Key Features

Sixteen rounds committing whole vaccine plants for the fictional manufacturer VIB, each plant fixed at ₹50 billion and 50 million vials of dedicated annual capacity.
One decision per round, the number of plants to build, submitted with a written rationale, alongside a HOLD option that scores a real zero-plant decision.
Each round presents an approval probability, twelve named agency forecasts, and that round's selling price and production cost, with base and revised forecast sets across the sixteen rounds.
Critical-fractile engine computing Cu, Co, the fractile CF, z, and the normative quantity Q* equals mu plus z sigma, scored against realised demand at reveal.
Reveal-gated debrief exposing normative plants, post-hoc optimum and round profit, a cumulative-profit leaderboard, and a demand-distribution diagnostics explorer fitting 500 samples.

Educational Outcomes

Ability to translate underage and overage costs into a critical fractile and read it as the service level a rational investor should target.
Ability to size irreversible capacity from a forecast mean and spread, recognising that a wide forecast disagreement inflates the normative build far beyond realised need.
Ability to separate the forecast-optimal quantity from the profit-maximising decision, understanding that matching the normative order can over-build and destroy profit through fixed cost.
Recognition that a higher approval probability or selling price does not always justify more plants when the demand spread and fixed commitment dominate the payoff.
Players come away understanding that committing capacity before approval and demand are known is a bet on a distribution, not a forecast, and that the disciplined response to deep uncertainty is often to build less than the numbers first suggest.

Topics Covered

Newsvendor Model

Critical Fractile Analysis

Capacity Planning Under Uncertainty

Demand Forecast Aggregation

Real Options Under Irreversibility