Case Studies

Enhancing NPI Forecast Accuracy with an AI-Powered Demand Forecast Solution

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How one company streamlined the forecasting process for successful new product launches

New product introductions (NPIs) need accurate demand forecasts. Why? Good forecasts help companies better manage inventory, reduce stockouts, and meet revenue targets.

A leading global consumer packaged goods (CPG) company struggled with NPI forecasting, and consistently overestimated true demand. The company’s forecasting capabilities were in dire need of an overhaul. They partnered with e2open to transform their approach to demand forecasting by leveraging cutting-edge innovations like demand sensing and AI clustering.

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The Situation

For this company, introducing new products into the market was fraught with uncertainties. Traditional forecasting methods and manual planning processes failed to capture nuanced trends for emerging products. This is especially true in fast-paced industries like CPG, where there is large volume and velocity of demand.

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The Challenge

Forecast errors during product launches create a domino effect. Overestimated demand means overstock, capital tied up in excess inventory, and impact on the bottom line. Conversely, underestimating demand risks stockouts, eroding customer trust, and potentially losing market share. The existing tools this company had lacked the adaptability needed for the dynamic variables that impact NPI forecasting.

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The Solution

The company harnessed the power of e2open’s revolutionary supply chain AI to refine its NPI forecasting models. E2open’s demand sensing solution uses AI clustering to analyze patterns from multiple data points, including early sales signals, market trends, and historical product performance. This approach empowers more accurate demand forecasts and enhances inventory optimization.

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The Outcome

The company reported transformational results:

Improved demand forecast accuracy by up to 85%, reducing forecast errors for NPI launches

Optimized inventory levels, minimizing waste from excess inventory and missed opportunities from understock

Faster response to market trends, thanks to AI-driven demand sensing

Sustainable profitability with scalable processes tailor-made for CPG and other industries

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Conclusion

By implementing e2open’s demand sensing capabilities, the company gained confidence in their demand forecasts. By deploying AI-enhanced tools, the company was able to improve NPI forecasting accuracy, reduce errors, and effectively align inventory with market demand.

Applications used
Demand sensing

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