The lack of historical sales data for new product

The gap

Evidence profile

Sourced from the stated research gap and stated challenges of the source papers, classified as general, spanning 3 journals.

Supporting evidence — 3 representative gaps

• Investigating the role of using AI and machine learning for demand forecasting in supply chain management (2026) · Journal of Artificial Intelligence and Technology · doi

  The study identifies a gap in the current demand forecasting methods, which are not quick enough to accurately forecast demand in fast-changing markets. The study identifies a need for hybrid AI-driven models that can adapt to rapidly changing retail environments. The study identifies a lack of a single AI model capable of effectively forecasting demand across a wide range of products and industries.

  generalstated research gapevidence 5/5
  Keywords: study identifies gap current demand forecasting methods quick
• Demand Forecasting Strategies for New Product Launches in the Consumer Electronics Sector: A 2025 Perspective (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  The lack of historical sales data for new product launches limits the effectiveness of traditional forecasting paradigms. The need for a hybrid forecasting approach that combines machine learning predictions with expert adjustments informed by survey data. The importance of integrating qualitative insights with quantitative models in demand forecasting.

  generalstated research gapevidence 5/5
  Keywords: lack historical sales data new product launches limits
• Derived Feature Engineering and ABC–XYZ Segmentation for Machine Learning-Based Forecasting of Intermittent Spare Parts Demand (2026) · Applied Sciences · doi

  The paper identifies the challenge of forecasting intermittent spare parts demand due to its irregular nature. Another challenge is the need to balance the monetary importance of demand volume with the operational importance of demand frequency. The study also highlights the importance of selecting the appropriate category configuration for forecasting model development.

  generalstated challengesevidence 5/5
  Keywords: paper identifies challenge forecasting intermittent spare parts demand

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