New Product Performance Tracking

Launch velocity analysis, comparison to forecast, and cannibalization impact assessment to optimize new product introductions and portfolio management

Business Outcome
reduction in pilot program duration
Complexity:
Medium
Time to Value:
3-6 months

Why This Matters

What It Is

Launch velocity analysis, comparison to forecast, and cannibalization impact assessment to optimize new product introductions and portfolio management

Current State vs Future State Comparison

Current State

(Traditional)

Product managers manually track new item sales in Excel, comparing weekly sales to pre-launch forecasts using simple variance calculations. They create PowerPoint reports with launch performance summaries weeks after introduction. Analysis of cannibalization on existing products is anecdotal or ignored entirely. Success criteria are vague, and post-launch learning is captured inconsistently. The lack of systematic tracking makes it difficult to improve forecasting or make rapid course corrections on underperforming launches.

Characteristics

  • Digital Kitchen Display Systems (KDS)
  • Integrated ERP systems
  • AI-driven automation tools (e.g., PreciTaste's Prep Assistant)
  • Real-time analytics platforms

Pain Points

  • Data fragmentation across disconnected systems.
  • Complexity in inventory management leading to waste or stockouts.
  • Labor efficiency issues and staff adoption challenges.
  • Difficulty in identifying specific bottlenecks in kitchen operations.
  • Many smaller QSRs still rely on manual tracking methods, which are less efficient.
  • Real-time visibility into actual ingredient usage versus theoretical requirements is often lacking.

Future State

(Agentic)

A Launch Analytics Orchestrator coordinates comprehensive new product performance tracking from day one. A Velocity Tracker Agent monitors launch sales trajectory, comparing actual performance to forecast and historical launch benchmarks with daily granularity. A Cannibalization Analyst Agent identifies sales displacement on existing SKUs using market basket shifts and control group analysis. A Forecast Calibration Agent continuously compares predictions to actuals, identifies forecast error patterns, and improves future launch forecasts. An Intervention Engine recommends rapid corrective actions (additional promotion, placement changes, expanded distribution) for underperforming launches.

Characteristics

  • Customer feedback platforms
  • Sales data from KDS
  • Inventory levels from ERP systems
  • Market research databases

Benefits

  • 30% reduction in pilot program duration due to real-time data insights and automated reporting.
  • Error rate in order accuracy reduced from 5-10% to 1-2% through continuous monitoring and feedback loops.
  • Reduction in food waste by 20% through optimized inventory management.

Is This Right for You?

50% match

This score is based on general applicability (industry fit, implementation complexity, and ROI potential). Use the Preferences button above to set your industry, role, and company profile for personalized matching.

Why this score:

  • Applicable across multiple industries
  • Moderate expected business value
  • Time to value: 3-6 months
  • (Score based on general applicability - set preferences for personalized matching)

You might benefit from New Product Performance Tracking if:

  • You're experiencing: Data fragmentation across disconnected systems.
  • You're experiencing: Complexity in inventory management leading to waste or stockouts.
  • You're experiencing: Labor efficiency issues and staff adoption challenges.

This may not be right for you if:

  • Requires human oversight for critical decision points - not fully autonomous

Related Functions

Metadata

Function ID
new-product-performance-tracking