Optimizing Demand Forecasting to Reduce Losses and Enhance Operational Efficiency  

Business Challenge

The client, a leading industrial manufacturer headquartered in the USA, with annual revenue exceeding $4 billion, faced significant operational challenges due to inaccuracies in their demand forecasting processes. The client operated a complex manufacturing network with over 20 production facilities and 70 warehouses worldwide.

Inaccurate Demand Forecasting

Inefficient Inventory Management

Losses Exceeding $200M

The existing forecasting solution followed a one-size-fits-all approach, failing to incorporate critical signals from marketing activities. This led to substantial inefficiencies, including SKU pile-ups and stockouts, which collectively resulted in losses exceeding $200 million. The combined impact of stockouts and inventory holding costs (IHC) contributed to approximately 20% of the client’s total business losses.

To address these challenges, the client required a demand forecasting solution capable of improving accuracy by at least 20%, thereby enabling more effective production planning and inventory management.

How Quantzig Helped

Quantzig adopted a structured and data-driven approach to address the client's demand forecasting challenges:

1. Identifying Key Influencing Factors: : Quantzig identified critical factors impacting demand forecasting by leveraging various knowledge forums and platforms. These included deal size, incumbent vendor, business segment, opportunity type, product, time span, and seasonality.
2. Developing a KED Framework: : A Key Event Driver (KED) framework was created to systematically track salesforce performance against these identified influencing factors.
3. Advanced Modeling Techniques:: Quantzig implemented advanced modeling methodologies to develop a win/loss predictor. This enabled accurate forecasting and better alignment of production with market demand.

Results and Impacts

The solution delivered remarkable outcomes, including 75-90% improvement in forecast accuracy while also garnering an 80% reduction in forecasting process time. These advancements collectively enhanced production planning, enabling the client to align supply with demand more effectively and minimize operational inefficiencies.