Retail, CPG and Logistics

Following consumer preference trends, the AI way

Set to reach a whopping USD 14 trillion by 2025, the Consumer Packaged Goods (CPG) industry is witnessing gigantic growth. Comprising goods like food, beverages, cleaning products and the like that are replaced frequently by consumers, CPG companies are engaged in massive product design and development efforts. They gather data from social campaigns, point of sales (POS) systems, customer feedback cycles and more, and funnel insights into improving products.

Undoubtedly, CPG companies are affected by marketplace fluctuations: the sector is influenced massively by changing demographics, customer preferences, and market trends. Inflation, geopolitics and black swan events such as the pandemic of 2020 can have an outsize influence on the companies. Shoppers’ demands and tastes can change at the turn of a coin, and CPG players must follow the ‘turn’ as it were, catering to such shifts with an eye on profitability, and of late, sustainability. Other challenges include:

• Regulatory compliance requirements across countries and geographies (e.g., the EU). These regulations may pertain to food safety, raw material procurement, labelling, packaging and other parts of the product production process. Non-adherence may result in penalties and fines
• The environmental and sustainability aspects of regulation have increased significantly over the last decade, making such compliance particularly important for CPG manufacturers and traders in production, supply chain or packaging operations
• Condensed product life cycles due to changing customer preferences, seasonality, or trends. These make R&D cycles very short and leave the CPG manufacturer very little time to recoup their costs
• Product recalls can be disastrous not just financially but also for the product and the company’s reputation. Reputation management becomes particularly important in such a situation, leaving minimal scope for errors to creep into the finished product
• Like many others, CPG players have built lean supply chains that leave them very little scope for error

What happens if Artificial Intelligence (AI) gets into this mix? Many CPG enterprises are discovering that AI can give them a massive competitive advantage. The process involves designing and deploying AI models on the large amounts of structured and unstructured data that CPG companies store, and routinely procure. Sources may include sales, logistics, weather data, social media, shipping movements and other supply chain data. It may also include data on consumer behaviours and preferences garnered from studies and focus group testing. Predictive analytics are employed to operate on the patterns and trends that the models spot in the data.

Case studies of key successes abound, and as with other industries and sectors, AI is making rapid inroads in the way CPG companies operate.

Here are some key avenues to growth that CPG companies have discovered, thanks to AI:

1. Automation of tasks, including data analytics can lead to faster time-to-market and product development life cycles. Consumer preference patterns and trends can be spotted, analysed and churned back into the product much more quickly with AI, helping product marketers turn the intelligence into a competitive advantage.
2. The scope for errors is vastly reduced, with AI-powered technology in action. This can mitigate product recall issues, and prevent reputational harm, besides preserving the bottom line. Product formulation, including ingredient proportions, raw material quality checks, and combinations can be monitored rigorously by using machine telemetry and high-speed analytics. This, too, feeds into the virtuous cycle of better product quality and improved time to market.
3. AI also supports speedier R&D, which, as we discussed earlier, can be a bottleneck in taking CPG products to the market. Bots that are trained using the organisation’s implicit and explicit knowledge repositories can act as virtual assistants to R&D and product development personnel, helping them speedily with queries and what-if scenarios. This is in sharp contrast to previous search queries which could have taken enormous time to construct.
4. Advanced analytics aided by AI tools for testing and quality assurance can improve product safety and efficacy by leaps and bounds.
5. CPG R&D groups can use AI to model complex ‘what-if’ scenarios with product deployments and gamify particular market trends or movements to judge how product sales and performance may change. With AI on their side, virtual prototyping of products can be an easier and faster affair as well, helping product teams gauge product benefits better. This intelligence can be fed back into product development - preventing costly ‘real world’ occurrences of particular events. For example, product packaging can be improved by modelling product behaviour in extreme weather conditions.
6. AI models can dynamically alter their predictions over time, as they access the latest data in real time. CPG companies can reliably use such prescriptive models to guide their moves in the marketplace.

Many of these recommendations are still in the ‘can do’ hypothetical list for CPG players. The reason? The adoption rate of AI is still around 40% in the industry. Happily, many companies are rapidly picking up pace and adoption is expected to go to 80% by 2025. For the CPG industry, the future is indeed AI-driven!

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