Demand forecasting to improve customer loyalty and margins while minimizing food loss

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With the global population estimated to reach 9.3 billion by 2050, the United Nations Food and Agricultural Organization (UN FAO) has calculated that there is a need to increase food production by 60% to meet the growing demand. Urbanization, growing awareness about healthy and functional food, demand for convenience, lifestyle changes, and a rise in disposable income have led to an upsurge in demand for processed food.

According to a verified market research report, the food processing market size was valued at USD 143.51 billion in 2020 and is projected to reach USD 235.67 billion by 2028, growing at a Compound Annual Growth Rate (CAGR) of 6.6% from 2021 to 2028. One of the biggest challenges of the food processing industry to meet this growth is the fluctuating demand and difficulty in adjusting production and stocks to minimize food loss.

Producing more than what is required will lead to wastage of food and other resources such as water and energy that go into production both at the processing and farming stage, while producing less may lead to out-of-stock situations at retail outlets that may hinder food processing.

Demand forecasting in food processing

Food demand forecasting refers to analyzing historical data and accurately predicting customer demand for a product in a given time period. It helps to:

  • Create a blueprint of production schedules
  • Determine the quantity of production to meet the demand
  • Make informed production and supply decisions
  • Improve supply chain optimization and inventory management strategies
  • Reduce food loss and greenhouse gas emissions

According to internal research of food processing industry done by Cropin:

  • 47% of respondents polled demand forecasting as a top priority to drive growth
  • 46% preferred farm to fork traceability
  • 44% prioritized improving brand value and trust

Volatile commodity pricing, the perishable nature of food, timely procurement from farmers, changing consumer needs, an increasingly health-conscious population, social media, etc., all influence demand for processed food.

Intelligent agriculture cloud to accurately forecast demand

The food processing companies must deploy technology to better manage food demand and supply, which can be daunting when done manually. Cropin, in a bid to digitize the entire agri-ecosystem, has built Cropin Cloud – a secure, flexible, scalable, and intelligent cloud platform. Cropin Cloud digitizes and captures agri-data from farm to fork and provides food processing companies with the most accurate data, enabling them to make informed strategic decisions in a sustainable manner.

Prevent overstocking by planning procurement

The very nature of food (short shelf life) requires accurate calculation, so it does not lead to overstocking or stockouts. Overstocking may lead to the scrapping of products as they expire, while stockouts will lead to losing customers. Finding the right balance is important.

Cropin Apps has an integrated portfolio with highly customizable apps and web solutions (Cropin Grow, Cropin Connect, and Cropin Trace) that capture and digitize data from multiple data points like IoT devices and drones, robots, remote sensing satellite information, and weather advisory sources. It helps food processing companies monitor crops, plan harvest, and arrange for timely procurement from farmers.

Accurate yield prediction to manage production

Accurate yield prediction is essential to increase production efficiency. Cropin Apps not only enable remote crop monitoring, but also engages with farmers and offers pest and disease alerts, and alerts for adherence to Package of Practices. This ensures companies and farmers protect crops and benefit from maximum yield per acre. Cropin Cloud leverages data and intelligence to provide accurate yield estimates that help food processors manage production.

End-to-end traceability to improve consumer confidence

Gaining customer loyalty is among the biggest challenges for food processors and establishing end-to-end transparency goes a long way to enable this. Cropin Apps helps maintain the quality of the agricultural produce, minimize loss due to unprecedented weather conditions, ensure end-to-end traceability that eliminates malpractices, promotes transparency, and builds customer loyalty and trust.

Additionally, Cropin Cloud enables food processing companies with inventory management, QR-code labeling technology, QR-code enabled counterfeit detection, monitoring and managing downstream processes, and much more. This helps companies meet consumers’ need for transparency in production and help gain loyalty.

Build consumer trust with our farm-to-fork traceability app - Cropin Trace

Catering to changing demands of consumers

Consumer demands and tastes are constantly changing today. Food companies must keep up with the pace of this change by deploying technology. Digitalization of the downstream food production value chain by Cropin App provides real-time intelligence and data-driven insights, which, when analyzed with customer data, will help anticipate and meet the changing demands of consumers.

Seamlessly manage food demand and supply

Seamlessly integrating several factors influencing food demand analysis and food supply forecasting is not possible using conventional tools. There is a need for leveraging technology and digitization to eliminate human errors and predict accurate demand forecasts.

Cropin Data Hub has built-in advanced data frameworks that solve the most common problems in the agri-ecosystem and helps in consistent engagement with farmers, forecasting quantity and quality of the harvest, and harvest planning/scheduling. Data helps in accurate food demand sensing for production planning, improves supply chain connectivity, and addresses climate change, all of which ultimately augments the company’s margins.

Cropin Cloud integrates all the data and leverages it to provide intelligent insights. Leveraging Artificial Intelligence (AI) and machine learning models, predictive insights are generated, enabling smart decision-making on and off the field. Several built-in contextual deep-learning AI models help to solve various challenges faced by the food processing industry while managing everyday operations. Cropin is also pursuing an incremental, practical approach towards food demand forecasting using technologies such as AI and intelligent automation.

Transforming supply-demand management with Cropin Cloud

To summarize, Cropin is aligning with the demands of the food processing industry and driving discussions around ‘sustainable food’ with technology. This helps gain customer loyalty, save costs, and increase revenue with digitization. Indeed, food processing industry estimates indicate that digitization can save costs by 23% and increase revenue by 18%.

The combined use of automation, data analytics, and cognitive techniques offered by Cropin Cloud will transform the food processing industry by providing visibility and transparency across the business value chain, driving process efficiencies, and changing how companies engage with customers.

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Cropin Apps

Applications for
digitization

Cropin Apps is an integrated portfolio of highly customizable apps and solutions that capture and digitise agri-data from the farm to the warehouse to the fork. These applications are designed to scale digital transformation across agriculture and allied industries including forestry, commodity, banking and insurance.

DataHub

ML-ready data pipelines for enhanced analytics

Cropin Data Hub is designed to deliver the power of unified data by enabling interfacing with all agri-data sources from on-the-field farm management apps, IoT devices, mechanization data from farming resources, drones in agriculture, remote sensing satellite information, weather data, and many more.                                                      

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Access to field-tested machine learning models

Cropin Intelligence enables access to over 22 of Cropin’s contextual deep-learning AI models to help agri-businesses with insights and predictive intelligence. Built using the world's largest crop knowledge graph, these models have been field-tested and deployed worldwide while being fine-tuned to work with a range of specific crop varieties, conditions, and locations.

Abishek Keerthi Narayan

About the Author

A results-driven and strategic leader with over 18 years of experience in customer success, SaaS, management consulting and technology enablement. Proven track record of implementing customer-centric strategies to realize the key business outcomes of clients. Strong leader with a track record of building and scaling high-performing teams. Passionate about solving customer problems, creating value, and driving success.