5 Ways Big Data and Analytics is Revolutionizing the Food Industry

Jan 4, 2019

product profitability analysis

The food industry is one of the most profitable sectors across the globe. However, with the increase in global competition, companies in the food industry have started facing numerous challenges such as reducing supply chain waste, optimizing supply chain efficiency, boosting sustainable growth, implementing green policies, and finding a competitive advantage. To deal with such challenges, businesses in the food industry need to focus on leveraging big data and analytics to keep close tabs on new supply chain trends and competitors’ market progress.

An inefficient supply chain leads to low-profit margins and more wastage. Furthermore, if the supply chain is not optimized, it can result in the inability to adapt quickly to a problem and can increase operational costs. Therefore, players in the food industry must leverage the benefits of technology like big data and analytics to gain better insights into the ability to track and monitor supply chain activities in real-time.

At Quantzig, we understand that to ensure the efficiency and performance of your supply chains, from sourcing to manufacturing to delivery, optimization is required. And to help companies in the food industry thrive in the competitive landscape, our team of experts has highlighted five ways in which big data and analytics can help companies in the food industry to become market leaders.

To know how our solutions have helped leading food and beverage companies, contact us.

How Big Data and Analytics is Revolutionizing the Food Industry?

1. Improve Operational Efficiency

From analyzing the food industry trends to the effect temperature has on food quality, big data and analytics can help food industry businesses to ensure that they always deliver the best quality possible. But this is not the only way big data and analytics can improve operational efficiency. It can also help in analyzing customers’ behavior using their shopping data. By applying predictive analytics to historic shopping data companies in the food industry can cut the average checkout wait time. Big data and analytics can also help in analyzing market trends and suggest optimum inventory levels at different locations.

2. Boost On-time Delivery

Using various big data and analytics tools and techniques, companies can also optimize the food delivery mechanism. Big data and analytics can help in collecting data from various sources like weather, road traffic, route, temperature, etc. and provide a proper estimate for the time taken to deliver goods. Moreover, big data and analytics can also predict the impact of all the above factors on the quality of food. Thus, big data and analytics ensure that you don’t waste your resources in transporting stale food products and deliver perishable food items in good quality.

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3. Better Customer Sentiment Analysis

Sentiment analysis is the process of monitoring customer behaviors over social media networks. Using IoT and digital transformation technology, companies can categorize consumer behavior into positive, negative, or neutral. This can help companies in the food industry to analyze their customer emotions on a scale. Any negative review can be analyzed at scale and preventive measures can be taken to prevent the spread of negative words. This technique is beneficial for large-scale food retailers like McDonald’s, KFC, Pizza Hut, etc.

4. Personalized Customer Experience

Big data and analytics help companies to provide a personalized, customer-centric experience to every buyer. This includes important analysis of customer views like what they like, how much they can pay, what they share on social media, the stories they resonate with, the reviews they make, etc. Today, big data and analytics have made tracking, collection, and timely delivery all possible through data. Data analysis can give an insight into their changing behavior and improve the efficiency of marketing. The nexus of big data and machine learning in all its forms, including predictive analytics and even neural network deep learning, are the underpinnings of highly efficient, well informed, and deeply satisfying interactions that benefit both food industry businesses and customers.

Wondering how to make your food supply chain efficient and boost your business growth? Request a free demo below and access the potential of big data analytics on real-time dashboards.

5. Improved Quality

Providing and maintaining the same taste of food for consumers is a very challenging task in the food industry. The taste of food not only depends upon the proper ingredients measurement but also on their storage, quality, and season. Big data and analytics can analyze such changes and forecast the impact of each on the food taste and quality. Big data and analytics can also analyze the impact of factors like transportation and storage on the quality of packaged foods. The insights from such analysis can be used to understand pain points and suggest improvement measures.

Ready to Harness Game-Changing Insights?

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