FOOD AND THE FUTURE: Digital Transformation in the Food Industry
A look at how trends in digital transformation are enhancing the way we consume
By Diane Dominique Ting
Change is constant, and that has perhaps never been truer than today. The pandemic has turned the entire food industry upside down as they were forced to operate differently to adapt to the changes brought by COVID-19. While stories of contactless purchases and sanitizing protocols are plenty, the real changes in the food industry might be more substantial than that. Although there has always been an obvious appetite in incorporating technologies to companies, the pandemic has undoubtedly accelerated digital transformations in the food industry by allowing it to be open to new concepts and changed behaviors. In most cases, the pandemic accelerated the popularity of pre-existing trends.
The food and beverage market is expected to register a compound annual growth rate (CAGR) of over 65.3% during the period of 2019-2024. Figure 1 shows that the Americans and parts of Europe are expected to be a significant part of this explosion towards Artificial Intelligence (Al).
As more consumers demand greater access and information on the food they consume, food manufacturers must find Innovative ways to provide solutions. Today's digital Innovation is promoting efficiency at multiple points along the food chain. Digital technology has driven change on multiple fronts at accelerated rates by collecting, using, and analyzing massive amounts of data on practically every aspect of the food system. Fortunately, there are multiple ways on how the food industry can make the most out of digital transformations.
Data and Devices
Within the incr easingly competitive technology landscape, data is the most essential commodity. Data has been so valuable that when managed and analyzed properly, it can provide correct insights thatbusinesses can use to innovate and grow. Today, higher-quality data can now be captured quicker and in greater volumes due to the Internet of Things (loT).
IoT is defined as a network of devices that gather and convey data using the Internet. According to a report by Report Liner, the loT and traceability for the food and beverage. manufacturing market was valued at 4.08 billion USD in market value in 2017 and is expected to reach 8.43 billion USD by 2025, growing at a CAGR of 9.5%, loT adds a layer of technology to food manufacturers to ensure better food safety by being able to oversee the entire food manufacturing process. For example, loT devices allow the management of entire operational and quality control procedures such as the temperature of processed items, the pressure levels of items, and even the application of labels to products.
In fact, loT-enabled technologies have proven to be more beneficial today than ever. Employees with wearables are now able to monitor their own health and share verified data with their companies through biometric identification that can pick up indicators of illnesses such as high temperature.
In addition, IoT-enabled wearable devices such as smart watches, smart gloves, and smart glasses with augmented reality can be used in food processing plants to improve production processes and food safety.
The implementation of lot in the food industry has also considerably diminished the risk of a food illness pandemic. loT-enabled sensors prove to be the most popular since they are able to monitor food safety, indicators such as temperature, humidity, and carbon dioxide content most especially during production, storage, and transport. These sensors can significantly improve quality control measures.
With loT, the supply chain will also be able to function jointly with global and local regulations such as automated Hazard Analysis and Critical Control Points (HACCP) checklists. When HACCP checklists are used throughout manufacturing, production, and transportation processes, companies are able to receive meaningful and consistent data to help them put food safety solutions in place.
"Data is the most essential commodity"
Towards data science
While IoT technology is a powerful tool that can improve the efficiency of food manufacturing businesses, some of its greatest potential is found in its ability to collect and interpret data to improve operations. Data science, also known as data analytics, involves the collection of data to help identify customers' needs with immense accuracy to help businesses grow and succeed. Business functions such as product development, inventory levels, delivery procedures, and employees' staff schedules can all be improved when businesses harness the power of data science. Fortunately, the extensive food industry holds massive data waiting to be processed and analyzed, providing undeniable advantage to those who apply it. Figure 2 shows how big data analytics are able to benefit supply chain businesses.
Being able to analyze data is especially important to ensure products meet certain quality control standards as it can cover all the information regarding price, condition, and quality of products. By analyzing components along the entire supply chain, data analytics can help identify ways to improve quality control. Consumers have become more demanding by wanting to know how food was processed, how the livestock was treated, and what chemicals were used in the food. Data science, particularly data visualization, can build transparency within supply chains by allowing customers to understand where each supply comes from allowing more confidence in the quality of the product. Being able to control nearly every aspect of food production can help food producers produce high-quality products and minimize food-related health hazards.
Subsequently, machine learning is a method of data analysis that automates analytics model building. As a branch of artificial intelligence, this method is based on the idea that systems can learn from data and industry patterns to make decisions with minimal human intervention. Optimum sorting solutions, supply chain optimization, predictive maintenance, and self- serving robotic solutions are some examples of machine learning applications. With the immense amount of data present in the food industry, machine learning allows computers to analyze data and make recommendations based on input data.
The more notable and state of the art technology involved in data science is predictive analytics. Using the unique capacity of Artificial Intelligence (AI) algorithms, predictive analysis is capable of determining and forecasting possible outcomes and issues from gathered data allowing businesses to correct and adjust strategies before undesirable outcomes. For example, predictive analysis allows manufacturers to identify time to repair and cost to repair indicators through categorizing issues and predictive alerts, being able to save up to 50% maintenance time and reduce costs by 10%.
At the same time, predictive analysis can help detect contamination in food packaging by tracking food temperatures beyond their in house operations. This data can be used to help identify temperature fluctuations and predict potential contamination issues, consequently avoiding food recalls.
Data science does not just focus on production and supply chain processes, data science also involves analyzing market trends and consumer patterns that can help identify stock and menu choices that customers will naturally gravitate towards. Data, such as when products are relevant, where target customers spend their time, what marketing platforms can cater to a product, and factors that affect a customer’s decision to buy can help assist in designing effective and targeted marketing campaigns.
Sentiment analysis is the process of analyzing a customer's inclination, emotions, and feelings towards a brand based on data gathered from different social media platforms. Technologies such as natural language processing allow data analysis tools to categorize text gathered into positive, negative, or natural reviews. Marketing campaigns then become less about guesswork and more about studying customer's needs.
From supply chain to blockchain
Food supply chains are vast and spread over the world making it crucial yet nearly impossible to trace the entire network. Fortunately, blockchain technology allows a powerful opportunity to trace the lifestyle of food products from every point of contact from farm to table. By a simple scan of a QR code, users can get access to relevant information in just a matter of seconds.
Carrefour, Europe's largest retailer, implemented blockchain traceability to track the diffe- rent production stages of free-range chickens across France. Walmart, on the other hand, partnered with IBM and Tsinghua University to run pilots using blockchain and IoT sensors to track pork from China and Mexican mangoes shipped to the United States. These trials reduced the time to track supply chain information from one week to just a few seconds.
While it may take years to develop, the long-term vision is for companies to produce fully transpa- rent food supply chains. With an industry with over 500 food recalls annually in the United States alone, blockchain's transparency makes it possible to identify the safety of food production by accessing food safety information should an outbreak or contamination occur at any point.
Rapid alert systems
When public health is at risk, the flow of information to enable swift reaction when an outbreak or contamination occurs is of utmost importance. Once presented with that information, knowing what to do with that information is crucial.
Created and operated by the European Commission in 1979, the Rapid Alert System for Food and Feed (RASFF) was put into place to provide food and feed control authorities with an effective way to exchange information between Member States in case of any risk detected in food or feed. The online system allows the Commission, European Food Safety Authority (EFSA), European Economic Area (EEA), Norway, Liechtenstein, Iceland, and Switzerland to submit notifications on the withdrawals of unsafe or illegal products in the market allowing Member States to act more rapidly and in a coordinated manner in response to a safety threat. The RASFF portal features an interactive online database that gives access to summary information as well as a search function for information on any notifications issued in the past.
On the other hand, the RASFF consumers' portal was launched in June 2014, which allows consumers access to the latest information on food recall notices, and public health warnings issued by food safety authorities and companies. In the same way, consumers are able to identify food that has been tagged in the system allowing them to make more informed choices. Thanks to RASFF, many food safety risks have been averted even before they could be harmful to European consumers.
In the Philippines, the Rapid Alert System for Food & Feeds (Phil RASFF) was established, which is a web- based system tool for rapid exchange of food and feed safety information among competent authorities involved in food safety control. Phil RASFF was modeled from the ASEAN RASFF and EU RASFF to institutionalize an alert and notification system for food and feed safety concerns, and improve coordination amongst food safety control agencies at national and regional levels.
Auditing goes remote
While food safety relies on straightforward principles, its verification requires a complex system of specialties, auditors, and certification bodies to ensure processes are practiced consistently and appropriately. Food business certification bodies have explored new ways to gather, analyze, and report data while keeping auditors and personnel safe. Since physical visits have become more difficult today, auditors have migrated to hybrid and remote auditing arrangements.
Remote video auditing through installed cameras is an approach that analyzes segments of live and/or recorded video feeds selected at random by a remote auditor. According to an article entitled "The Rise of Remote Food Safety Audits" from Food Quality & Safety, cameras deployed by various locations within the operation area are conti- nuously running, or at least transmitting a video feed during operational hours.
Another remote auditing approach is via walk-through video where an employee may facilitate an audit by recording a walkthrough of the operations from receiving goods until dispatch of the final products. Remote auditors have used different devices such as hand-held cameras, helmet-mounted cameras, or even glasses equipped with cameras to carry out this type of audit.
Figure 3 shows how the different certifications programs recognized and implemented different remote audits during the pandemic.
"Food business certification bodies have explored new ways to gather, analyze, and report data while keeping auditors and personnel safe. Since physical visits have become more difficult today, auditors have migrated to hybrid and remote auditing arrangements."
While promising, the differences in remote audits among certification bodies prove that the accuracy of remote audits remains a key concern by many authorities. Local authority officers argue that information can be vulnerable to manipulation by food businesses as problems could be missed that may result in public health risks.
This concern was further reiterated when onsite follow-up visits were made following remote audits. The Food Standards Agency (FSA) asked ICF International, Inc., a consulting and technology services provider, to evaluate remote audits done in England, Wales, and Northern Ireland. Several cleanliness problems at a butcher shop were identified in an ICF officer that were not picked up by images or phone calls with the company.
The FSA mentioned that these findings can help assess where remote approaches might be useful in the future. Initially, remote audits were usefu so work could continue safely even during the pandemic. But since lockdown restrictions have been loosening, certification bodies will need to define which aspectsof an audit can be done remotely to ensure that audit efficiency and integrity will not compromised
According to Professor Alan Gillies, Managing Director of AGLC Ltd., remote auditng has been met with resistance, with a lot of people looking forward to the return of traditional inspections, "When technology 'disrupts', we don't replace them entirely," according to Gilles. The goal should be introduce technology to make remote auditing better, ultimately to make food safer.
Driving force of the food tech industry
Perhaps the most important aspect involved in the food and beverage market involves consumers as the driving force of the entire food industry. Aside from the pandemic and other uncertainties that have disrupted the food industry, its digital transformation is largely based on consumers and their modern lifestyles. Factors such as the demand for more healthy products, the demand for better efficiency in food production, the impact of environmental and political sectors, and the reality and perception gap all can contribute to the food industry’s demand for digital transformation.
According to Adamo Digital, a top software outsourcing company based in Vietnam, food technology towards digitalization covers four centered concepts: online ordering system, food delivery system, inventory management software, and restaurant Point of Sale (POS) system. Consequently, the innovation of the food industry would greatly benefit software development companies with projects to build hi-tech programs, particularly innovations in restaurant technology. In fact, the digitalization of the market is predicted to reach over 250 billion USD by the end of 2022. Examples of restaurant technologies that would dominate the market in the next decade include voice technology, chatbots, self-ordering kiosks, hand-held ordering devices, custom restaurant mobile apps, Kitchen Display Systems (KDS), and tabletop ordering systems.
Barriers to transformation
Generally, digital transformation has contributed to every player involved in the food industry. However, successfully applying digital transformation starts with changing an organization's mindset to embrace technologies. But as with any new technology, there is a learning curve associated with it. IoT devices may increase the time it takes to implement solutions into the workflow when improperly managed and implemented. Transition periods are highly suggested where employees are able to adjust to new technology. While employees will have access to more data than they are used to, managers should be able to show the new data that is available and how it can be used to their advantage.
While the food industry is not known for its early adoption of technology and may not serve as a distinct niche for digital transformation, change does not necessarily mean large-scale disruptions. Instead, the adoption of digital innovations to a growing food industry proves that its potential can be further maximized. The rapid development and deployment of digital technologies promise to accelerate food system transformation to help businesses make better business decisions. Ultimately, digital transformations can positively disrupt the food industry and set entirely new standards for health, food quality, and customer experience.
