How data analytics increase profitability in food and beverage industry

Sertis
7 min readNov 17, 2022

Recently, the food and beverage industry (F&B) has been facing the situation of ‘Shrinkflation’, which is that all manufacturers decide to downsize their products while remaining at the same price. Has anyone noticed that our favorite treat became smaller despite the same price tag? Snickers, one of the most popular chocolate brands, has reduced the size of its chocolate bars by 11 percent.

This situation highlights the key challenges food and beverage manufacturers are encountering, which are the increasing cost of raw materials and distribution and drastically changing consumer trends. These factors are why we see more and more manufacturers trying to save costs by using the Shrinkflation practice, and this will continue to be more intense. The profit margins will continue to be thinner because the global economic slowdown has reduced purchasing power. Either keeping downsizing the product or increasing the price is not a long-term solution since it puts a burden on consumers, which negatively impacts the brand.

To find the solution, sometimes there is no need to look outside for help. It is better to try to look inside to improve internal operations instead. Among the situations, data analytics, a technology that analyzes big data to find insight, is what manufacturers are looking for since it can efficiently reduce costs to increase profitability. Data analytics brings together and analyzes a large amount of data in our business that is beyond human capability to find insight that can improve our operations, eliminate mistakes, reduce costs, and improve customer experiences. This article will guide you through how data analytics increase profits in the food and beverage industry.

Food waste is one of the biggest operating costs in the F&B industry

Shockingly, statistics show that one-third of the entire food produced around the world is wasted, which is weighted around 1.3 billion tons every year. It doesn’t only account for 2.6 trillion USD per year, but it also severely damages the environment.

Food and beverages have a limited shelf life. Its life clock starts counting down from the minute it enters the supply chain system, from production, and distribution, to getting on shelves. If the product isn’t bought within its shelf life, it will be disposed of, whether it is instant food, fruits, vegetables, or ingredients used for restaurants. The more limited their shelf lives are, the more chances they get wasted. Speeding up the supply chain helps extend product lives, reduces chances of disposal, reduces costs, and eventually boosts the F&B industry’s profitability. Data analytics have the capability to improve all processes in the supply chain system. As a result, we can leverage data analytics to create an efficient supply chain system that maximizes profits.

Accurately predicting customer demands

Creating a cost-effective supply chain system for the F&B industry starts with production planning that meets customer demands. It will increase the chances of purchase and reduce the cost of food wastage. There are various data analytics approaches for demand forecasting. For example, the sentimental analysis to detect sentiment from texts in social media to see how customers feel toward the brand, what are current consumer trends, and which product is in-demand. This tactic is used by large food chains like McDonald’s and Pizza Hut.

Furthermore, we can do demand forecasting that predicts and estimates customer demands altogether to efficiently plan the supply chain management. Demand forecasting for multiple channels and product categories can be done to determine the optimal quantities and distributions of each product in each channel. We leverage a machine learning model to process all relevant big data, such as purchasing history, weather, situational factors, sales records, prices, and promotions to find applicable insight. The model is live and automatically updated to changes to generate real-time production planning to reduce surpluses and misproductions.

A cost-effective approach to quality control in production

Another aspect of a supply chain that we can improve is the production process. Quality management is most important in the F&B industry because defective products can not be resold, not like in other industries. For example, clothes that don’t pass the quality control process will be sold at discounts in outlets, while defective food and beverage products only end up in the trash. Production quality will extend product shelf life, reduce chances of getting wasted, and attract more consumers. Furthermore, managing cost, time, and resources efficiently reduce the cost of downtime and increase production capacity.

Data analytics can contribute to the quality control process. For example, production optimization applies machine learning algorithms with production planning and scheduling and creates a plan that is tailored to site constraints to reduce production planning time from 4–6 hours to 10–15 minutes and make it flexible to unexpected changes. Also, the plan created by machine learning optimizes production costs while operating at the same production capacity level.

Quality management practices can leverage data analytics to analyze all critical factors that affect product quality, e.g., production processes, quantities, storage, temperatures, and ingredients. The automation system can be used to monitor each factor to ensure the quality of each product.

Fast delivery to improve quality and shelf life

Effective shipment is another important factor in the F&B industry, as it is the industry that focuses on products with limited shelf lives. The longer these products are stuck in transit, the more chance that they end up in the trash. Besides, the quality and freshness decrease with time, which reduces the chance of being sold as well.

F&B businesses can reduce costs to increase profit by using data analytics technologies to increase logistics efficiency and speed up shipping operations. For example, data analytics analyze traffic, weather, and temperature conditions to find the best shipping type that maintains products’ freshness. Also, the model will find the fastest route to get products delivered to retail stores or restaurants. We can apply this solution to restaurants to get a quality meal delivered to customers within 30 minutes to provide them with a better experience and strengthen their relationship with the restaurant.

Managing your inventory properly

Inventory management affects the profitability of F&B businesses. Due to the products’ limited shelf lives, streamlined inventory management and optimal stocks are essential for cutting the cost of overstock.

Data analytics play an important part in inventory forecasting. It can combine the insight from demand forecasting with other product data such as shipments, shelf lives, weather conditions, storage constraints, and other factors to determine optimal stock levels. This will diminish the cost of overstocking inventory. We can also create an inventory plan specifically for each store location by collecting and analyzing store data to see which are best-selling products to plan their optimal inventory. Besides, the model can monitor stock availability to notify when a product is nearly out of stock and plan to place the order at the appropriate time by calculating the shipping time to avoid the gap in the shelf that leads to missed selling opportunities.

Create more brilliant and efficient marketing strategies

Apart from the products, marketing strategies, pricing, campaigns, and tactics we use to offer products and promotions to customers are essential in F&B businesses. Because of the fast-moving consumer trends, selling time-sensitive products within their shelf lives and boosting sales require creative marketing strategies.

We can apply data analytics with marketing by analyzing consumer trends, customers’ purchasing histories, reviews and feedback, and sales records to plan the promotions and campaigns that successfully attract customers. For example, we can plan a sales promotion with products that have sales potential, or a promotion to clear the dead stock. We can bundle the dishes that are usually ordered together to create appealing deals. We can provide customers with personalized product and promotion recommendations through email marketing or push notifications. Also, a recommendation engine in online platforms that recommend a personalized product to each customer can help create a better impression from customers and increase chances of buying.

Do you see how impactful data analytics can be on the F&B businesses’ supply chains? It can tackle the most serious problem of the costs of perishable products. This is why industry players should consider data analytics to uplift their sales and increase their profitability in the long run.

Be the winner in this fast-moving competitive world with Sertis. We are a data analytics solution provider who can help you customize the solutions that are tailored to your business needs, characteristics, and problems. No matter what industry you are in, we can create the right solutions for you.

Learn more about the solutions for the food and beverage industry from Sertis: https://www.sertiscorp.com/fmcg

Written by: Sertis

Originally published at https://www.sertiscorp.com/

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