By SYLVAIN CHARLEBOIS (Senior Fellow)
Many Canadian consumers have noticed how the price of lettuce has skyrocketed in recent weeks, as has that of celery. Such fluctuations happen all the time, regardless of whether Canadians are willing to accept them. Nonetheless, technological advances could make these occurrences a thing of the past.
Artificial intelligence (AI) is a hot topic these days. It’s nothing new, really, but many agree that we are on the cusp of a revolution in how we make decisions, how we manage things — virtually every aspect of our daily lives. The agri-food sector is not immune to this phenomenon, either. While agriculture is an industry which has accompanied humanity since prehistoric times, cognitive technologies will quite simply change everything about how we feed ourselves, starting from the farm right down to the fork.
Let’s begin by looking at agriculture. Our planet will need to provide food for more than 9.7 billion people by the year 2050. We are on target to achieve this, for one good reason: how we embrace data in agriculture is changing at an astonishing rate. In order to increase yields, and to enhance plant and soil science practices, farmers need data, and lots of it. The average farm in the industrialized world generates a little over 200,000 data points per day. That may sound impressive, but by 2050, we can expect this number to be well over 4 million. To limit energy and waste, farmers will need to know in real time how much fertilizer to apply, or what seed to use and where, so they can get the most out of their fields. They’ll be able to make better decisions. Farmers need all the help they can get, what with climate change and nature being what it is. In Canada though, farms are behind in use of technology, compared to many in the U.S. and Europe. However, the recent investments in rural connectivity by both federal and provincial governments should help to bring Canadian farms up-to-date.
AI will also help to solve the problem of severe labour shortages in many rural operations. The UN predicts that almost 70% of the world population will soon live in urban areas. In Canada, we have exceeded 98%. While some Canadians do move back to the countryside to seek a different lifestyle, most of these will only keep a hobby farm, at best. With the help of cognitive technologies, many operations can be done remotely. We may be years away from the “farmer-less farm” concept, but the need to hire more workers could be alleviated. These measures will lead to more consistencies, and yes, fewer losses. Most important for consumers, retail price fluctuations could become a thing of the past, or at least less frequent.
Agriculture will not be the only sector affected by increased use of AI. Robotics, machine learning and AI will also be some of the key game changers for the retail grocery sector. Running stores by “gut-feeling” can only be so effective. People experience bounded rationality when bombarded with too much data. The average food store manager deals with over 50,000 products or SKUs, which is more than 6 to 8 times what it was a few decades ago. To optimize any food retail store, a typical management team will be required to make between 1,000 to 1,500 decisions on any given day. These decisions influence everything from merchandising to assortment strategies. If you consider the joint effect of directions from head-office with transient customer data and insights, instinctive decisions on the part of management just won’t work anymore. There are simply too many calls to be made manually, especially in an environment where margins rarely exceed 2%.
Food retailing, though, is a highly traditional sector. Many grocers have resisted digital transformational changes for years now. The industry is only starting to acknowledging that it simply cannot efficiently manage all the data points it has access to. What’s more, the level of interest in certain products throughout the week will vary greatly, due to the weather and other factors. Amazon, a non-traditional food retailer, just opened a new store where consumers can come in, grab what they want and leave without visiting a cashier. Over 100,000 sensors follow consumers in their journey through the store and will instantaneously charge them for products they put into their bags. Amazon gets to evaluate consumer decisions, subtle hesitations between products, and how someone moves around in a store. Just imagine the application of such data. With machine learning capabilities using sophisticated algorithms, some food grocers could very well understand consumers better than consumers understand themselves. Thus, AI will allow the industry to better forecast and predict consumer behaviour.
The most visible change for consumers coming from AI will likely be pricing optimization. Imagine a world of food retailing free of sticker shock. No more sudden appearances of $8.00 heads of cauliflower, or overpriced lettuce or celery due to unforeseen macro-systemic circumstances. With AI, grocers can set acceptable price ranges for any product, and prices could change by the hour, depending on inventory levels and fluctuations in demand. Since fresh produce constitutes about 40% of sales from an average food store, striking the right balance is key. The window in which to course-correct if an item does not sell could be measured in minutes or hours, rather than in days or months. For example, a chilly overcast Victoria Day weekend does not generate the same sales as when the weather is sunny, hot and humid. Procurement, promotions — everything will require tweaking.
With AI, our relationship with food retailing will dramatically change over the next decade or so. Therefore, in a few years time, if you think a certain fresh item in a food retail store is overpriced, keep in mind that a computer probably told management that there’s a market for it.
Sylvain Charlebois, Dean of the Faculty of Management, Professor in Food Distribution and Policy, Dalhousie University, author of Global Food Safety, Risk Intelligence and Benchmarking, published by Wiley-Blackwell (2017). He is also a Senior Fellow here at AIMS.
