A shot of AI for coffee industry.
Written by Kunhee Lee – Director of R&D U squared
Enter a café in London, it is common to find people of all age, gender, religions, sexual orientation, political preference and more. Despite of our differences, our love for coffee is ubiquitous. It is a wakeup call, productivity companion, and medium of social gathering. With recent studies showing its benefits for our brain and heart, we are blessed with yet another excuse to go for a coffee, and maybe procrastinate.
A group of presumably coffee-loving researchers shares with us that it is the sensitivity towards bitterness that makes coffee taste so good, through thisnature article. With personal taste profile growing more complex, Moustache Coffee Club uses AI to vendor beans tailored to your taste preference. Bext 360 uses computer vision and machine learning to estimate its mineral content and price beans at source.
In response to our insatiable demand, coffee industry often adopted new technology. From Nescafé bringing barista espressos home, to Costa using virtual reality to train its staff. More recently, Starbucks used AI and big data to understand its customers to personalises its services and suggests locations for its new branch.
To cater for our needs, 25 million farmers across 60 tropical countries grow coffee over an area almost 60 Londons. However, the force of nature is immutable. Coffee crops are sensitive to annual weather fluctuations, not to mention major meteorological events such as, Brazil frost, draught, storms like El Niño. The supply is so unreliable, that an economist identified it a major factor in encouraging Starbucks to raise prices, despite fall in the price of beans. Furthermore, a study by Stanford found a direct relationship between coffee prices and child deaths in Columbia. With climate, economic, social, business factors, this multivariate system is difficult to cope with.
So far, AI has often been used for standalone functions rather than integrating with the existing business structure. Supply chain is a complex system with lots of data. Use of AI in supply chain has already been demonstrated at various levels and is more plausible with IoT capabilities.
With particularly inconsistent supply with natural factors, the next step for digitising coffee industry may be in its supply chain. A tailored solution, rather than off-the-shelf box, can take advantage of science of meteorology to provide more accurate prediction of bean prices.Tags: AI, Big Data, Business, Coffee, Consulting, Data Science, Machine Learning