Slide 4: Priority Intervention 1 - Information Flow
Enhancement
Expected Impact & Justification:
● Cost Reduction: 15% reduction in food wastage through better demand prediction
○ Rationale: Industry studies show 25-30% food wastage in restaurants; predictive
analytics typically reduces this by 50-60%
○ Calculation: 30% wastage × 50% reduction = 15% cost savings on ingredient
costs
● Orders/Day: 8-12% increase through optimized menu availability
○ Rationale: Current "out of stock" rate ~15-20% during peak hours; real-time
inventory prevents 60% of these instances
○ Calculation: 18% unavailability × 60% prevention = ~11% order recovery
● TOV: 10% increase via data-driven upselling recommendations
○ Rationale: E-commerce upselling typically increases basket size by 10-15%;
restaurant context may be lower due to food constraints
○ Calculation: Conservative estimate based on 15% upselling success rate × 70%
average basket increase
Secondary Effects:
● Improved restaurant profitability → reduced churn (estimated 25% partner retention
improvement)
● Better inventory management → supply chain efficiency
● Enhanced restaurant satisfaction → premium placement willingness
Slide 5: Priority Intervention 2 - Rules and Incentives
Restructuring
Expected Impact & Justification:
● Cost Reduction: 12% reduction in logistics costs through optimized rider allocation
○ Rationale: Current average delivery time ~35 minutes; surge pricing reduces
peak-time demand spikes by 20-25%
○ Calculation: 25% peak demand smoothing × 45% logistics cost correlation =
~12% cost reduction
● Orders/Day: 15% increase through improved service quality and availability
○ Rationale: 30% of potential orders lost during peak hours due to rider
unavailability; dynamic incentives improve availability by 50%
○ Calculation: 30% lost orders × 50% recovery = 15% order increase
● TOV: 8% increase via restaurant partner upselling incentives
○ Rationale: Performance-based commissions motivate restaurants to increase
order values; pilot programs show 6-10% improvement
○ Calculation: Conservative estimate based on incentive alignment effectiveness
Tertiary Effects:
● Market expansion into underserved areas (rider availability increases by 40% in Tier-2
cities)
● Competitive moat strengthening
● Ecosystem lock-in effects
Slide 6: Priority Intervention 3 - Self-Organization
Capability
Expected Impact & Justification:
● Cost Reduction: 20% logistics cost reduction through proximity optimization
○ Rationale: Current average delivery distance ~4.5km; micro-hubs can reduce this
to ~2.8km (38% reduction)
○ Calculation: Distance reduction directly correlates to fuel/time costs: 38% × 55%
logistics cost factor = ~21% cost savings
● Orders/Day: 25% increase through reduced delivery times
○ Rationale: Delivery time reduces from 35 mins to ~22 mins; customer studies
show 18% demand elasticity per 10-minute reduction
○ Calculation: 13-minute reduction × 18% elasticity = ~25% order volume increase
● TOV: 12% increase through expanded service capacity
○ Rationale: Faster deliveries enable premium pricing; reduced wait times allow for
time-sensitive, higher-value orders
○ Calculation: Premium service tier adoption (15% of orders) × 80% higher AOV =
12% blended increase
Long-term Effects:
● Network effects amplification (40% increase in market coverage)
● Barrier to entry creation for competitors (₹200Cr+ investment required to replicate)
● Rural/semi-urban market penetration (60% new market accessibility)
Slide 7: Supporting Interventions - Structure & Feedback
Loops
A. Enhanced Feedback Systems
● Real-time performance dashboards for all stakeholders
● Predictive analytics for demand/supply imbalances
● Automated quality scoring and corrective actions
B. Structural Optimizations
● Regional cluster management approach
● Specialized delivery partner categories (premium, bulk, etc.)
● Restaurant partner tiering system with differentiated services
Combined Impact & Justification:
● Cost Reduction: Additional 8% through operational efficiencies
○ Rationale: Feedback systems reduce coordination costs by eliminating 40% of
miscommunications
○ Calculation: Communication inefficiencies account for ~20% operational
overhead × 40% reduction = 8% savings
● Orders/Day: Additional 10% through improved coordination
○ Rationale: Better demand-supply matching reduces wait times and improves
success rates
○ Calculation: Current order failure rate ~12% due to poor coordination; 80%
improvement = ~10% order recovery
● TOV: Additional 6% through better service differentiation
○ Rationale: Tiered service model allows premium pricing for 20% of customer
base
○ Calculation: 20% premium customers × 30% higher AOV = 6% blended increase
Slide 10: Expected Outcomes & Success Metrics
6-Month Targets (Phases 1 & 2):
● Cost Reduction: 18% overall operational cost decrease
○ Justification: Information flow (15%) + Partial incentive optimization (3%) = 18%
● Orders/Day: 20% increase in daily order volume
○ Justification: Menu availability (11%) + Service quality improvements (9%) = 20%
● TOV: 15% increase in total order value
○ Justification: Upselling systems (10%) + Incentive-driven restaurant behavior
(5%) = 15%
12-Month Targets (All Phases):
● Cost Reduction: 30% overall operational cost decrease
○ Justification: Cumulative effect of all interventions with compounding benefits
○ Calculation: (1-0.85) × (1-0.12) × (1-0.20) × (1-0.08) = 0.70, hence 30% reduction
● Orders/Day: 35% increase in daily order volume
○ Justification: Non-linear growth due to network effects and market expansion
● TOV: 25% increase in total order value
○ Justification: Multiplicative effect of all value-enhancement interventions
Long-term Strategic Impact:
● Market leadership consolidation
● Ecosystem dependency creation
● Sustainable competitive advantage
● Platform network effects maximization
Final Recommendation: Focus on Information Flow and Rules & Incentives interventions first,
as they offer the highest impact-to-effort ratio while building foundation for long-term systematic
transformation.
