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. To meet fickle consumer tastes, food and beverage (F&B) companies are looking 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 ways AI can impact how fast-moving consumer goods (FMCG) are produced, packaged, stored, distributed, marketed, and consumed. Artificial intelligence and machine learning are fundamentally changing 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 toward local, artisanal providers. Consumers 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 in an interview with TOPBOTS. (Stiller heads digital transformation and analytics for Deloitte’s Consumer Products Business.) 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 (or the recipe)
- Raw materials (or the ingredients) to create the product
- Equipment, tools, and machinery to scale production
- Venue (processing plant, factory floor, etc) where a company assembles/processes goods
- Safety and quality control implementation
- Compliance with 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
This is a 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, even when the products in question have been passed along to retailers and are no longer within their control.
Can AI be the magic elixir?
Shampoo, soda, and mayonnaise may be everyday products, but the infrastructure behind the production and consumption of CPG products is much more complicated than you may imagine.
“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 Ohio-based specialty food maker Lakeview Farms achieve significant reductions in line downtime (34 percent), equipment repair costs (15 percent), and worker overtime ratio (17 percent).
Read the source article in VentureBeat.