From bean to bottom line: AI smoothens Cocoa’s price volatility for consumer packaged goods

Stabilizing Cocoa price volatility for consumer packaged goods with AI
Prathmesh Thergaonkar

Director, Finance Analytics

Summary
Cocoa prices have risen steeply, impacting the bottom line for chocolate producers. Adverse weather, political instability, and supply chain disruptions worsen the unstable market situation for cocoa pricing, among other unfavorable external factors. Read on to discover how artificial intelligence (AI) can be leveraged by consumer-packaged goods companies to effectively address price fluctuations for their secure financial future through use cases like high-accuracy forecasts, real-time risk analysis, etc.
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Summary
Cocoa prices have risen steeply, impacting the bottom line for chocolate producers. Adverse weather, political instability, and supply chain disruptions worsen the unstable market situation for cocoa pricing, among other unfavorable external factors. Read on to discover how artificial intelligence (AI) can be leveraged by consumer-packaged goods companies to effectively address price fluctuations for their secure financial future through use cases like high-accuracy forecasts, real-time risk analysis, etc.

Cocoa prices, the key ingredient in our flagship chocolate products, have surged by a staggering 47.02% in the past 18 months. 1 This isn’t just a ripple; it’s a tidal wave threatening to capsize the bottom line.

The Cocoa chaos:

The once-predictable world of cocoa pricing has become a volatile storm. Favorable weather forecasts for 2023 in Ivory Coast and Ghana, the world’s top producers, initially promised a smooth ride. But then, like a rogue wave, heavy rains and political instability struck, casting doubt on the supply.

Meanwhile, global supply chains, already struggling with port congestion and labor shortages, became further entangled. Delays in cocoa shipments compounded the worries, pushing prices even higher. The war in Ukraine added another layer of uncertainty, disrupting trade flows and impacting fertilizer availability for cocoa farms.

Since the end of last year, hedge funds have heavily invested in the cocoa market, intensifying an unprecedented price surge driven by inadequate harvests in West Africa. Speculative traders have accrued an $8.7 billion wager through London and New York cocoa futures contracts, marking the largest dollar amount ever recorded, per data on market positioning from the Commodity Futures Trading Commission. The price surge has CPG giants reeling. For instance, Hershey’s saw its margins shrink in 2023 as cocoa costs jumped over 20%. Mars, Mondelez, and Nestle are facing similar struggles, caught between rising input costs and the delicate dance of maintaining competitive prices.

https://tradingeconomics.com/commodity/cocoa.

This volatility creates a chilling effect. How can CPGs plan production, set prices, or secure supplies when the ground beneath their feet keeps shifting? The answer lies in harnessing the power of Artificial Intelligence (AI).

AI – a beacon in the storm:

AI, trained on massive datasets encompassing weather patterns, political events, and historical price trends, can become a CPG’s secret weapon. It can generate high-accuracy forecasts of cocoa prices, empowering companies to navigate the market more confidently. Imagine predicting a potential shortage month in advance! With this knowledge, a CPG can lock in contracts with reliable suppliers at fixed prices, shielding itself from future price hikes.

AI is emerging as a potent tool for navigating this volatile landscape of cocoa prices. Through careful analysis of a large volume of data from various sources, AI can identify patterns and predict future commodity price movements with greater accuracy than traditional methods. AI can identify patterns and predict future commodity price movements with better accuracy than traditional methods.

Here’s how AI is helping CPG companies mitigate risk and minimize bottom line impact:

• High-accuracy forecasts: AI algorithms can analyze diverse datasets to generate more accurate and nuanced commodity price forecasts, allowing companies to anticipate future costs better and make informed purchasing decisions. Price forecasting models consist of an ensemble of ARIMA, LSTMs, etc.

• Dynamic hedging strategies: AI can recommend data-driven strategies tailored to specific commodities and market conditions. This helps in mitigating the impact of price fluctuations and protect profit margins. Dynamic Hedging models incorporate reinforcement learning and optimization strategies.

• Real-time risk analysis: AI can continuously monitor market trends and identify potential risks associated with commodity price movements, equipping companies to react proactively and adapt their strategies as needed. Real-time Risk Analysis models employ a combination of NLP and anomaly detection techniques.

The outputs are disseminated through an interactive dashboard, which provides hedging recommendations, real-time alerts, back-testing results, and simulation and scenario planning capabilities.

The Road ahead

AI is still evolving, and with the advent of Large Language Models (LLMs), accuracy and scalability are improving rapidly. With this, its potential to revolutionize how CPG companies manage commodity price volatility is undeniable. By embracing this technology, companies can gain a competitive edge in the face of uncertainty, navigate the complexities of the global market, and secure their financial future.

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