[Newsletter] Demand is Volatile. AI/ML Would Like a Word.
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[Newsletter] Demand is Volatile. AI/ML Would Like a Word.

AI/ML technology is the future of demand planning. Here’s how leading CPG companies are leveraging it.

In today’s rapidly changing consumer landscape, generating an accurate picture of future demand has become increasingly challenging for consumer goods companies. With the fluctuating consumer behavior, volatile market conditions, and the rise of e-commerce, industry leaders are implementing innovative strategies and next-generation planning capabilities to adapt to shifting consumer preferences and optimize their decision-making processes. In this blog, we will explore the top five takeaways from an executive panel discussion on generating a clearer picture of volatile demand.

1. Importance of Clear Demand Signals:

A clear demand signal is crucial for companies as it directly impacts sales, inventory management, and overall business performance. Without an accurate understanding of demand, companies face the risk of tying up excessive working capital, obsolescence, and markdowns. Recognizing the significance of clear demand signals, industry leaders are prioritizing strategies to capture and interpret volatile demand data effectively.

2. Addressing Rapidly Changing Consumer Behavior:

The panel participants acknowledged the substantial impact of rapidly changing consumer behavior driven by factors such as COVID-19, inflationary pressures, and geopolitical issues. They emphasized the need to adapt to these changes proactively. By leveraging attribute analytics and demand sensing, companies can gain valuable insights into consumer preferences, reduce turnover, and align their product offerings with market demands.

3. Managing Channel Mix and E-commerce Growth:

The rise of e-commerce and the proliferation of various distribution channels pose both challenges and opportunities for consumer goods companies. The panel discussed the importance of predicting and managing the proliferation of channels effectively. They highlighted the need for a comprehensive understanding of customer preferences and the ability to adapt distribution strategies accordingly. Retailers shared their experiences with digital commerce, emphasizing the importance of evaluating profitability and anticipating inventory growth when venturing into e-commerce.

4. Balancing Historical Patterns and New Norms:

The panelists acknowledged the difficulty of relying solely on historical patterns in the face of shifting consumer preferences. With the advent of the COVID-19 pandemic, determining the new norm and predicting recovery became more challenging. They emphasized the need for closer collaboration between departments, connecting with customers, and leveraging up-to-date data and insights to accurately forecast demand and plan accordingly.

5. Effectively Managing Product Life Cycles:

The panelists discussed the challenges of managing product life cycles in an environment of volatile demand and shorter timeframes. They emphasized the importance of establishing a robust portfolio review process and employing statistical analysis and machine learning techniques. By identifying key attributes, conducting like-for-like comparisons, and leveraging external market data, companies can make informed decisions, rationalize their product portfolios, and minimize costs associated with launching and discontinuing products.

*This article was previously writen at aim10x platform, a place where Supply Chain leaders meet to discuss Digital Transformation. Click here to join the community for free.

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