What features could E2open add to its Demand Sensing solution to increase forecast accuracy for seasonal products?

Introduction

To improve E2open's Demand Sensing solution for seasonal products, we need to focus on enhancing forecast accuracy. This challenge involves understanding the unique characteristics of seasonal demand patterns and leveraging advanced technologies to capture and predict these fluctuations more effectively. I'll outline a strategic approach to address this product improvement opportunity.

Step 1

Clarifying Questions (5 mins)

• Looking at the product context, I'm thinking about the specific industries E2open serves. Could you provide more information on the primary sectors using the Demand Sensing solution for seasonal products?

Why it matters: Different industries have unique seasonal patterns that could inform our feature development. Expected answer: Retail, consumer goods, and fashion are primary users. Impact on approach: Would tailor features to address industry-specific seasonality challenges.

• Considering user behavior, I'm curious about the current data inputs for the Demand Sensing solution. What types of data are customers currently providing, and how frequently is this data updated?

Why it matters: Determines the breadth and depth of data available for improving forecast accuracy. Expected answer: Point-of-sale data, historical sales, and some external factors, updated weekly. Impact on approach: Would focus on expanding data sources and increasing update frequency.

• Examining the product lifecycle, where does the Demand Sensing solution stand in terms of market adoption and maturity?

Why it matters: Influences whether we should focus on core functionality improvements or advanced features. Expected answer: Established product with a solid user base, but facing increased competition. Impact on approach: Would prioritize innovative features to maintain market leadership.

• Considering external factors, how has the recent global supply chain disruption affected customer needs and expectations for seasonal product forecasting?

Why it matters: Helps identify new pain points or shifting priorities in demand sensing. Expected answer: Increased need for agility and real-time adjustments to forecasts. Impact on approach: Would emphasize features that enhance responsiveness and adaptability.