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§ Project 03 Strategy Competitive Analysis RMIT Jul 2025

Navigating omnichannel conflict in a competitive digital economy.

A strategic pitch and top-performing course assignment analysing Beiersdorf’s position against Unilever in Vietnam’s skincare market, using a simultaneous-move game with repeated interactions, mixed-strategy analysis, and Bayesian equilibria.

Industry-Evaluated — by Beiersdorf regional reps & employees
Winning Pitch Competitive Analysis Game Theory Bayesian Equilibrium Strategic Presentation
Overview

The question under the case.

Vietnam’s FMCG market presented a clear strategic tension for Beiersdorf: online channels were expanding faster, while offline channels still offered higher margins and stronger retail economics. Rather than treat this as a simple binary choice, our analysis modelled the problem first as a mixed-strategy game under complete information, then extended it through Harsanyi transformation into a Bayesian game under uncertainty about Unilever’s type. Sensitivity analysis was used to test how stable the recommendation remained under changing cost and channel assumptions. Together, the analysis supported an omnichannel recommendation shaped by both profitability and strategic uncertainty.

§ Analysis Process

Four steps from competitive mapping to a defended recommendation.

The game was the framework. The evidence was the argument. The delivery was the edit.

i.
Step 01 · Industry & Competitor Analysis

Map the strategic tension clearly.

Mapped the overlap between Beiersdorf and Unilever across shared skincare categories and converging channels in Vietnam’s FMCG market. The central trade-off was clear: online channels offered faster growth, while offline channels remained more profitable and more important for preserving retailer relationships.

Competitive analysis matters most when it makes the real trade-off impossible to ignore.
ii.
Step 02 · Game-Theoretic Modeling

Turn the tension into a game clearly.

Framed the decision as a simultaneous-move, repeated game in which both firms had to choose between pushing online or preserving offline strength. Built the payoff structure around channel economics, investment costs, competitive response, and profitability.

A model becomes useful when it forces strategic choices into explicit terms.
iii.
Step 03 · Equilibrium Solving & Sensitivity

Test the recommendation under pressure.

Solved for mixed-strategy Nash equilibrium, then tested how the result changed under different assumptions about technology investment intensity and offline discounting. This helped identify which parts of the recommendation were stable and which depended heavily on assumptions.

A recommendation is only credible when it survives its weakest assumptions.
iv.
Step 04 · Bayesian Refinement and Recommendation

Refine for uncertainty, then recommend.

Extended the model into a Bayesian game by considering different possible Unilever types, then used those outcomes to refine the strategic recommendation. The final recommendation was not a simple channel switch, but a move toward omnichannel execution while preserving profitable offline relationships.

Strategy improves when it is built for uncertainty, not certainty.
§ Selected Works

A Few Slides from the Deck.

Strategies — push online vs push offline matrix for Beiersdorf and Unilever
i.Strategy matrix — push online vs push offline, for both players.
Beiersdorf payoff construction framework with revenue base calculation
ii.Payoff construction — revenue base to net payoff for each channel play.
Bayesian Nash equilibrium expected payoffs table
iii.Bayesian Nash equilibrium — expected payoffs under Unilever's type uncertainty.
Recommendations — reorient to preserve retail relationships and shift to true omnichannel
iv.Recommendations — preserve retail, shift to true omnichannel.
§ Outcomes

What the pitch won.

Beiersdorf pitching competition certification
Award Certification
won

Industry-evaluated strategic pitch — selected by Beiersdorf regional representatives and company employees.

defended

Live Q&A with industry judges — model held under pressure.

team lead

Led the game-theoretic framing, equilibrium analysis, and final pitch delivery.