People have become picky eaters. Our ancestors ate whatever they could forage, but modern day Homo Sapiens expect gourmet meals at street food prices on demand. Consumers prefer fast, affordable, healthy, and delicious. To meet fickle consumer tastes, food and beverage (F&B) companies look to artificial intelligence to help them scale new products and stay profitable. Whether they are hacking logistics, human resources, compliance, or customer experience, these smart brands recognize the game-altering impact of AI on how fast-moving consumer goods (FMCG) are produced, packaged, stored, distributed, marketed, and consumed. Artificial intelligence and machine learning are impacting fundamentally the consumer packaged goods (CPG)and food and beverage industries.

Aside from the challenge of mounting consumer expectations, established food and beverage companies are also facing a shift in customer trends away from global conglomerates towards local, artisanal providers. Eaters and drinkers are demonstrating not only a willingness to shovel out more money for a “handcrafted” experience, they’re also getting caught up in the DIY preparation trend of home cooking and craft brewing.

“CPG in general is facing this perfect storm where activist investors are expecting a lot in margin while consumers expect more high-quality tailored products … along with better service,” explains Ben Stiller, who heads digital transformation and analytics for Deloitte’s Consumer Products Business. Stiller’s comment reveals why brands are intrigued by the near-magical promise of AI: “Pressure to do more with less.” No wonder many players in the CPG (or FMCG) space are going beyond automation to the more esoteric fields of big data, machine learning, and other aspects of artificial intelligence.

 

A Taste For Trouble

Consumers judge food based on its impact on their palate and their wallet, but successful food brands with staying power require more than just a killer recipe. Any of the following challenges regularly plague CPG companies trying to speed up and maintain innovation:

  • Product design and specifications (the recipe in case of food processing)
  • Raw materials (or the ingredients) to create the product
  • Equipment, tools and machinery to scale production
  • Venue (processing plant, factory floor, etc) where the product is assembled/processed
  • Safety and quality control implementation
  • Compliance to government/international regulatory standards (health, environmental, safety, financial, zoning, etc.)
  • Product packaging and tracking system
  • Inventory management for storage and distribution
  • Logistics and transport for distribution
  • Marketing and public relations
  • Long-term engagement with partners and intermediaries for sale
  • Back office operations
  • Sales and order tracking that follows the brand’s supply chain, manufacturing, and logistics processes

Long list of problems, isn’t it? In addition to minding all the possible points of failure mentioned above, food and beverage companies need to mitigate significant risks like contamination and spoilage control, even when the products in questions have been passed along to retainers and no longer within their control.

 

Can AI Be The Elixir?

Shampoo, soda, mayonnaise all seem like simple, everyday products, but the underlying infrastructure that enables the production and consumption of CPG products is much complicated than you may imagine at first.

“Once the ingredients and materials get into the building or assembly line to build the product, that’s where the challenge begins,” reveals Leading2Lean CEO Keith Barr. “Machines were designed back in the day to run a certain way. If anything doesn’t meet the exact standard to run that way (e.g., materials don’t show up in time or are out of spec) they just won’t run. Then when it stops, you have to manually stop and fix it.” Another challenge is that older factories lack sensors and tracking equipment, so these abnormalities aren’t logged and therefore continue to plague the food production process.

A developer and provider of streamlined manufacturing software and cloud-based solutions, Leading2Lean helps businesses achieve sustainable process improvements through data analytics. Using data analytics to detect and eliminate inefficiencies, the company helped Lakeview Farms, an Ohio-based specialty food maker to achieve significant reductions in line downtime (34%), equipment repair costs (15%), and worker overtime ratio (17 percentage points).

The pressure to seek out providers of automation and AI-driven solutions like Barr’s company is considerable in the CPG space. Reasons abound:

  1. There are more marketing and distribution channels to engage.
  2. Competition has gone from brisk to brutal.
  3. Unified, synchronized data across all departments reduce errors, downtimes and costs.
  4. Visibility across all stages of the business process serves as a key competitive advantage.
  5. Real time data on customer behavior and market trends help future-proof businesses.

Dr. Tom Bradicich, VP and GM for Servers and IoT Systems at Hewlett Packard Enterprise puts it in another way: “Customers can’t stop their businesses, so they are challenged with how to keep it going while improving operations all at the same time.”

Currently working with a major F&B CPG company to integrate new technologies to the quality of production, Dr. Bradicich believes automation, edge computing, and artificial intelligence are game changers for the sector and are set to dramatically reduce human errors, hike quality, and increase sales. His team is currently rolling out a new product class called Converged Edged Systems that aim to establish production environments that provide higher reliability while requiring less energy, space, and costs.
 

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A Buffet Of Automation Options

AI has been used by enterprise to tackling challenges ranging from gaming to dating, and from banking to healthcare. Despite the wide range of applications, F&B companies tend to stick to specific use cases according to Lori Mitchell-Keller, Global General Manager of Consumer Industries at SAP.

Describing how the capabilities of SAP’s new Leonardo Machine Learning Foundation are being harnessed by clients, Lori Mitchell-Keller cited key AI applications that positively impact the front- and back-end processes of F&B companies:  

  1. Shelf management. F&B retailers use AI to automate inventory management. One use case is to have staff take photos of store shelves to initiate a machine-learning process that automatically detects missing or misplaced items and notifies stakeholders to restock or make corrections.  
  2. Image-based procurement. AI and image-recognition technologies can ease the procurement process and reduce the time it takes to send an order. Employees can just take a photo of an item to activate an automated database search for the exact item or an equivalent product.
  3. Personalized customer service. Using chatbots or voice assistants powered by natural language processing and machine learning, companies can tap consumer shopping data and history to provide hyper-personalized and automated customer service experiences.  
  4. Heightened consumer engagement. CPG players can use AI to maintain strong empathy with their audience. By closely monitoring conversations on social media, AI can be used to analyze consumer data and identify sentiment or behavior that are crucial not only in building positive experiences but also in the development and design of new product lines.    

Other applications of AI some CPG businesses are already implementing include financial and sales planning, chemical/contaminant monitoring, and back office paperwork automation.

 

Choking On Change: Challenges Of AI Adoption

Having a full plate of options may seem tantalizing, but challenges abound for potential adopters. Cost is a leading factor. With margins already thin, F&B companies simply don’t have the deep pockets to make AI investments like Google or Amazon.

Whether to build or buy is another critical decision. In the ideal world, F&B brands would build tightly integrated, customize in-house technology that reflects the unique needs of their company. In the real world, the battle for AI talent is so severe that leading technology companies spend over $650 million annually to woo desirable candidates. Companies with the fortune of having established data analytics capabilities and a team of competent in-house developers may safely build their own AI platform. Players without such resources must instead seek out solutions and providers based on clearly defined needs, goals and budgets.

Even for F&B companies who have found the perfect vendors, integrating a new AI system into existing technology stacks can be a headache, especially among large conglomerates with fragmented systems. Ken Wood, EVP of Product Management at logistics technology company Descartes warns: “It’s painful to wire systems together — our customers tell us that consistently. The more vendors, the harder the project. The more systems you have to cobble together, the more expensive and longer time it takes.”

The final challenge remains the AI technology itself which presents at least two issues for the industry. Without the right proprietary data, a F&B company may not be able to build machine learning models that perform. Matt Talbot, CEO of GoSpotCheck, describes this as “a huge obstacle without a cost-effective solution.” PepsiCo, Dannon, and Anheuser-Busch use GoSpotCheck’s AI-powered inventory software to maximizes supply chain efficiency and provides business insights to sales reps.

Food and beverage companies are known to guard their secret recipes fiercely, but machine learning models should not be a mystery. Unfortunately, even with the right data, many AI solutions offered by vendors work like black boxes. Without clarity and transparency into how algorithms are making decisions, F&B executives have a hard time determining whether a technology is truly adding value and how sustainable that value-add is.

CPG companies have experienced dismal growth in recent years. From 2013 to 2016, the industry grew less than 1.8% on average each year. Complications of AI adoption aside, one fact is clear: F&B companies must invest in new innovations to cut costs, grow revenue, and stay current with consumer trends. Those who do may live to thrive another day. Those who don’t may find themselves put out of business by Amazon.