How AI Is Shaping The FMCG Industry

Artificial Intelligence (AI) is revolutionising the FMCG industry, streamlining operations and boosting productivity. Here are just some of the latest advancements to keep an eye on.
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The gradsingapore Team
Brendan Yee
Writer
How AI Is Shaping The FMCG Industry

As a vital component of the global economy, the fast moving consumer goods (FMCG) industry is characterised by not just its dynamic nature, but also with rapid changes occurring frequently. Together with the similarly natured state of AI, their integration has resulted in not just the redefinition of traditional paradigms, but also spur new innovative growth for the FMCG industry.

This union has enhanced the overall digitalisation of supply chains, and can augment individual segments within the industry. Everything from work processes and consumer behaviour, to distribution and marketing efforts can be analysed and optimised efficiently and in real time. This is especially critical with the effects of globalisation, where international markets operate differently from each other, as well as e-commerce platforms that allow businesses to reach customers worldwide.

In light of these potential changes, budding career hopefuls looking at this sector should not only review the likely transformations in the field but foresee where the changes could eventually lead to.

Spearheading product innovation

As the name suggests, this industry is built around consumer products, and its success relies heavily on getting a large quantity of customers to purchase items on a regular basis. In a bid to remain competitive, companies will have to refresh their line of products from time to time with new products that are likely to spark new buying interest.

To achieve this, companies have to comprehensively assess both its own data and the data from customers to foster a better understanding of the target demographics they are selling to.

This includes trends that lead to boost in sales, consumer feedback, sales numbers from previous years, and patron sentiments regarding their product line, just to name a few. The collated data is then fed into an AI platform that processes these statistics and applies virtual prototyping to determine the most successful products and concepts.

AI FMCG
Credit: Idea Scale

The newly established Nestle Institute of Agricultural Science is one such enterprise that has integrated AI into its research and development program to help combat the growing intricacies of the food industry. It has helped reduce the time of their investigative research through the use of chatbots, which produces tailored content and determines the best solution to problems.

With smart platforms as the catalysts for growth and innovation, other firms can follow in Nestle’s footsteps to develop all sorts of new offerings like healthier options, distinctive taste profiles, or adapting to dietary shifts brought about by health culture in an ever-changing market.

Optimising operations and supply chains

One of the biggest challenges faced by the FMCG industry is the management of its operations and supply chains. With networks that span the world, much has to be taken into consideration to ensure operations remain seamless and trouble-free. From a broad perspective, this can include things such as geo-political tensions and conflict, supply shortages and fluctuating demand, which all contribute to a supply chain’s volatility.

This is especially true in the current global climate, where issues like the Ukraine-Russia war and the rivalry between the US and China, have disrupted many processes, such as the sourcing of raw materials and shipping. This, in turn, has led to an increase in prices across the supply chain that can be by consumers. By employing the use of AI, organisations are able to formulate solutions based on real time analysis and predictions provided by the system.

AI FMCG
Credits: Gartner

For instance, the recent Red Sea crisis in the Indian Ocean has forced many vessels to avoid the highly-travelled Suez Canal. This has led to a disruption in world trade since 30% of global container shipping passes through it. A severe drought in the Panama Canal in 2023, which serves as another super highway for ships, has also slowed traffic in the area to just 24 crossings a day.

To safeguard supply chains against further setbacks, companies can use AI systems to examine the current situation and generate recommended solutions, such as alternative routes and methods of transporting their goods.

Aside from dealing with external issues, companies can also replace traditional methods of handling logistics that hinge on a team executing analog planning based on past experience and knowledge. On the other hand, AI’s capabilities goes beyond just real-time, round-the-clock data collection and analysis. The system can evaluate things like traffic patterns, delivery periods and transport load capacity to help provide recommendations on the most efficient routes to take.

In doing so, organisations can minimise fuel consumption, reduce cost and cut down on shipping times while ensuring that the overall supply chain is not only agile but resilient to instability.

Product and inventory management

Once the products have arrived at the warehouses, companies then need to consider their inventory and product sales. However, there’s more to this than just ensuring their supplies are well-stocked and ready for order.

Companies need to toe the line between understocking and overstocking; the former can result in frustrated customers, while the latter means wasting money on time and space, with both outcomings equating to a loss in profit. In addition, they’ll also need to take note of any outdated and/or slow-selling items, and either replace them with other products or come up with new strategies to improve their selling power.

AI FMCG
Credit: Emerge

To prevent any blunders or issues, AI can be used to sort through mass data sets, which can include stats on things like purchasing trends, market variations and seasonal shifts. Firms can then react accordingly to these insights by ensuring their goods stay relevant to the needs and desires of their customers.

Walmart uses such a system, teaching their AI system to differentiate between the many brands and their inventory placements. The system’s accuracy rate is more than 95%, and since its implementation, has increased operational productivity by 15%. Apart from being able to automatically notify the stockroom to prevent stockouts, it can also instruct staff to place products in the appropriate places, allowing shoppers direct access and saving time. In fact, the platform is so intricate that it can take variables such as lighting conditions and shelf depth into consideration.

Another included feature is adaptive pricing, which changes based on fluctuations in demand, and comparative pricing. Cost is a big factor to both consumers and companies due to a myriad of external conditions like inflation and shortage of labour. Predictive algorithms can utilise the collected data to adjust prices in real time, ensuring that costs aren’t too expensive for buyers, while still staying within profit margins.

Accounting for international differences

With factors like globalisation and the popularity of e-commerce platforms, many brands and organisations can now extend their network and access markets that were previously out of reach. This undoubtedly comes with its own challenges, such as culture differences, language barriers, and consumer behaviour. Aside from this, companies also have to contend with macro issues like individual government restrictions, international regulations, and timezone variations.

In order to keep up with all these, employees need to work round-the-clock to accommodate the markets their organisations are working with. They also have to maintain a good understanding of the region, their counterparts’ business practices, and their consumers’ preferences. This means longer hours at the office, and more time to train fresh newcomers. Moreover, during peak seasons, the likelihood of errors can increase as well.

AI FMCG
Credit: LinkedIn

This is where the strengths of AI come into play, which can be leveraged to counter these issues. A good example of this is using a deep learning system capable of storing information and educating itself to navigate both macro and micro constraints and distinctions.

The user can input various guidelines, like national laws the company needs to adhere to or cultural norms that their target consumers believe in, and the apparatus can work along these parameters. Over time, the system increases in intelligence with the collection of new data and can provide better insights. The best part about this is that the platform is available 24/7, and is able to work through multiple time zones, taking the strain off the staff who have to do so previously.

AI’s influence on the FMCG sector

As consumer demands continue to change and new challenges emerge, the adoption of AI technology is expected to continue and increase across the FMCG industry. With the swift evolution in AI and the integration of advanced models, it is quickly proving to be an integral part of the entire supply chain management system.

Given its capabilities, these platforms are able to tackle multiple complex issues at once, with high levels of accuracy and efficiency. Not only does this instil confidence within organisations to attempt new ventures in foreign markets and/or new product launches, but also allows them to make data-driven decisions that will result in the most fruitful outcome.

Those interested in pursuing a career in this field should recognise this significant shift and stay informed about potential developments to remain competitive. By doing so, they can ease their transition into the job market and develop a skill set that aligns with emerging trends, thereby enhancing their value as new hires.