As the candy maker expanded globally and demand for its products grew, its existing demand planning process became increasingly ineffective. Heavy reliance on manual tasks prevented planners from focusing on higher‑value work, while limited forecasting segmentation and lack of what‑if scenario analysis reduced their ability to anticipate change. This made it difficult to detect demand shifts early enough to take corrective action. In the highly competitive snacking industry, accurately predicting demand is essential to avoid stockouts or excess inventory. Ongoing seasonal demand fluctuations, even before the pandemic, further exposed weaknesses in the planning process and underscored the need for a more agile, data‑driven approach to demand forecasting.

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