LONDON--(BUSINESS WIRE)--Quantzig, a leading analytics and advisory firm that delivers customized big data analytics solutions, has announced the completion of their article on the advantages of big data and analytics for the food industry companies.
With the recent increase in global competition, challenges for the food industry companies have grown manifolds. Food industry companies have to address numerous challenges such as reducing supply chain waste, optimizing supply chain efficiency, boosting sustainable growth, implementing green policies, and finding a competitive advantage. Moreover, they need to monitor product and data throughout the supply chain to comply with the state and federal regulations on food safety and disposal. They also need to ensure that good quality products are delivered at the lowest possible prices without compromising on the quality.
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Creating technology and automated processes that adapt to ever-changing consumer trends has become vital for food industry companies. Since the supply chain is an ever-changing world, companies need to adapt to new technologies to become more efficient and productive in the food business. The inefficiency of a supply chain to adapt quickly to a problem increases operational costs and results in low-profit margins and more wastage for companies. Therefore, companies need to leverage technologies like big data and analytics to gain better insights and track and monitor supply chain activities in real time.
Few of the common supply chain challenges faced by food manufacturing companies:
- Customer service
- Cost control
- Future planning
- Partnerships
- Developing supply chain talent
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Advantages of big data and analytics for the food industry companies:
Improve operational efficiency
Big data and analytics play a crucial role in the growth of food industry companies. Big data management improves operational efficiency by analyzing the customers’ behavior using their shopping data and helps in the implementation of predictive analytics to calculate the average checkout wait time. This assists food industry companies to enhance their operational efficiency and deliver the best services to their customers. Also, big data and analytics assists companies in analyzing market trends and suggest optimum inventory levels food industry companies need to maintain at different locations.
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Boost on-time delivery
Food industry companies necessarily need to optimize the food delivery mechanism to enhance their on-time delivery services. Companies leverage big data and analytics to collect data from various sources like weather, road traffic, route, temperature etc. and provide a proper estimate for the time taken to deliver goods. Also, big data and analytics can predict the impact of all the above factors on the quality of food by the time it reaches customers. Thus, big data analysis ensures that companies invest their resources in transporting the food products that reach customers in good quality rather than investing in transporting stale products.
Better customer sentiment analysis
Sentiment analysis is the process of monitoring customer emotions over social media networks. Using data tools, food industry companies can analyze consumer behavior into positive, negative, or neutral. This application of big data and analytics can help companies to analyze their customer emotions on a scale. Moreover, any negative review can be analyzed at scale and preventive measures can be taken to prevent the spread of negative feelings. This technique is highly beneficial for large-scale food retailers like McDonald's, KFC, PizzaHut etc.
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About Quantzig
Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. For more than 15 years, we have assisted our clients across the globe with end-to-end data modeling capabilities to leverage analytics for prudent decision making. Today, our firm consists of 120+ clients, including 45 Fortune 500 companies. For more information on our engagement policies and pricing plans, visit: https://www.quantzig.com/request-for-proposal
