Breaders
Breaders · Spring 2026 · 8 weeks

Retail Strategy & Profitability Optimisation for Forno Brisa

Revenue AnalysisDemand ForecastingWaste ReductionRetail StrategyData Analytics

Context

Breaders Group is a multibrand specialty bakery platform formed at end of 2024 through aggregation of five Italian bakeries under Forno Brisa. 2025 was the first year of operational integration. The two Bologna stores — Via Galliera (urban café-hub) and Bolognina (neighbourhood destination) — generated €1.79M in combined revenue across 39,167 transactions. Management needed to understand commercial performance dynamics and receive actionable recommendations for 10% volume growth in 2026.

Task

Using full-year 2025 POS and ordering data (550K+ product-level records), diagnose profitability drivers, seasonal demand patterns, and waste dynamics across both stores. Deliver strategic recommendations and operational tools to improve margins and reduce waste ahead of the 2026 growth target.

My Contribution

Built the end-to-end analysis from raw CSVs using Python: constructed a dual-store profitability model, computed seasonal and day-of-week demand factors, ran a variability-waste correlation study (24 store-month observations), and modelled three waste reduction scenarios. Developed a comprehensive web-tool for store managers and co-designed the management presentation.

Outcome

Delivered three strategic levers: (1) a structured Excel ordering tool using trailing 4-week averages × seasonal factors × day-of-week factors, targeting €1,600–€3,200 in annual waste savings; (2) a second-day Dolci programme extending the existing Zero Spreco model to pastries, recovering ~€3,300; (3) a two-horizon summer activation — immediate iced-drink product pivot plus a 2027 coastal pop-up concept. Combined addressable revenue impact: €13K–€34K (0.7–1.9% of revenue) on top of the 10% volume growth target.

Key Insights

  • Waste is not correlated with demand volatility (r = −0.06 across 24 store-month observations). The expected link — more unpredictable demand causing more waste — simply does not hold. Waste is driven by ordering behaviour, which is fully controllable.
  • January waste spikes to 2.26% of revenue on average (vs. 1.21% annual average), caused by post-holiday ordering inertia: managers carry December-level orders into a demand trough. This single month accounts for over 75% of Scenario 2 savings in the waste reduction model.
  • Galliera and Bolognina serve structurally different roles. Galliera is an urban café-hub where Pizza (26%) and Coffee (21%) dominate and the average basket is impulse-driven. Bolognina is a neighbourhood destination where Bread (22%) signals intentional staple shopping — and its average basket (€9.85) actually exceeds Galliera's (€9.61) despite a smaller format.
  • Galliera has an invisible B2B revenue stream of €70–90K annually (bulk coffee bags and wholesale Grandi Lievitati) that bypasses the POS register entirely. This understates reported revenue and explains the 37.9% Grandi Lievitati price inversion between stores (€19.39 vs. €26.73).
  • The summer dip (July–August) drops transactions 22–28% below annual average — this is a foot-traffic problem, not a product problem. Bologna empties as residents and students leave. No product change can recover customers who are physically in Rimini. A coastal seasonal pop-up is the only structural fix.

Skills Applied

Pandas Data AnalysisProfitability ModellingDemand ForecastingTime Series AnalysisRetail AnalyticsData VisualisationStrategic RecommendationsBusiness Strategy

Presentation Deck