CASE STUDY

70% Loss Reduction Achieved by a Leading FMCG Company by the Implementation of Multi-Factor Price Forecasting Methods

Sep 23, 2016

Business Challenge

Implementation of a robust price forecasting mechanism.

The client wanted to develop a robust price forecasting mechanism that could help them negotiate better rates with suppliers and optimize future raw material inventory levels.

Speak with our analytics experts today to know more about pricing analytics and how it helps organizations implement an analytics-driven approach to price and discount optimization for improving sales and gaining market leadership.

Situation

Lack of visibility on future prices and negotiation support.

The client was experiencing a lack of visibility on future Pyridine prices resulting in budgeting issues and supply chain fluctuations. In addition, the client also did not have access to fact-based insights that could enable them to negotiate long-term contracts with suppliers at individual category or product levels.

Solution/Approach

Pricing analytics solution enabling dynamic pricing at SKU and product levels.

We developed a multi-factor price forecasting model capturing various macro and micro-economic factors including Pyridine specific demand and supply factors. This model provided accurate price forecasting information and insights for improving supply chain efficiency.

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Impact

Reduced levels of losses and improved supply chain efficiency.

Our model helped the client in reducing losses by 70% in the first year along with improved supply chain efficiencies and optimized Pyridine inventory levels.

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