The nature of modern life is that data is everywhere - visible and hidden, structured and unstructured. Data about food is no exception.
The nature of modern life is that data is everywhere - visible and hidden, structured and unstructured. Data about food is no exception.
From high-tech GPS-enabled tractors, to supermarket distribution and shopping loyalty cards, data is created and used all along the food chain. But little of this data is shared openly, and very little is being used by consumers when they shop. Could the future of food look very different if this data were shared in different ways?
One of the things that data can do well - if used judiciously - is to help detect patterns and optimise outcomes based on correlations. Data about our food is being used in this way by farmers, agriculture companies, supply chains and supermarkets. Farmers can use weather forecasts, along with yield data and forecast demand to decide where and when to plant crops. Supermarkets can crunch their sales data to decide where to position food in the store, or what to run a promotion on, and how much additional stock to bring in. Your online shopping site or your loyalty card is likely to suggest discounts and offers that are tailored to you, based on the data they hold about what you've bought in the past, and what other products people like you have purchased.
Data has accompanied our food on the journey from farmer and producer to our table for centuries in some form. Originally this was in the form of notes for tax authorities, invoices and bills of lading. The need to trace food products back to their origins, especially in the case of easily contaminated meat and dairy, means that in modern times, recording the chain of custody has become increasingly important. The labelling and distribution of these products are therefore tightly regulated. This becomes a challenge when it includes multiple suppliers, imports and exports, and many intermediate processing steps - such as those for making breakfast cereals, or meat products like burgers. When Irish inspections found horsemeat in the food chain, and alerted retailers, it took months to trace all the supply routes that meat took. Even today, a grain passport that travels with raw grain from the farm, to identify what treatments have been applied, is a paper document that must be handed over at each stage of the chain of custody.
In addition to data that is still captured on printed pieces of paper, there are vast amounts of food data that remain behind closed doors. In the cut-throat competition of food retailing, where every penny of price difference seems to count, and where suppliers are pushed to deliver the lowest prices, opening up data on your business seems a ridiculous thing to do.
But locked in these vaults are treasure troves - where our food comes from, how far it has travelled, who produced it. And there are answers about ourselves: how much food we buy, where and when, if a sunny day makes us reach for the strawberries, or a cold wind means a spike in takeaway curry. Better access to this data might improve our ability to forecast, and reduce the huge amount of food waste created at different steps in the chain.
It might also change the economics of food production. Where we have seen massive consolidation in the past decades, into larger farms, distributors and retailers, data optimisation, combined with the ability to aggregate orders, design delivery routes and order direct from small suppliers might make it viable to be small again.
And while the giants of agriculture and food retail have vast datastores and many people to do the analytics, take-up of these methods by smaller producers, distributors and retailers is very uneven. The capacity and knowledge to take advantage of these new processes is hard to come by, but can confer big advantages (as Nesta's work on 'Datavores' in a range of industries has shown).
But although a vast amount of data is generated in the journey from farm to field, little of this data permeates through to the consumers, the eaters. We now have a more consistent traffic light system for nutritional labelling, but lots of other details about the ingredients and origins of food, especially processed foods, are hidden in a maze of codes or are not required to be declared at all. While consumers report that they want to know more about where their food comes from - especially in the wake of the horsemeat scandal - that information will be ignored if it is not presented in the right way.
If we are not to overload packaging with a blizzard of codes and traffic lights, how can we still get at data that is useful to inform what we buy?
Last year, we ran an Open Data Challenge with the Open Data Institute to prompt better use of some of the open data available on food. From allergens to calories to sources, at least some of this data is out there and available to the public, but very little of it actually gets used. The winners, FoodTrade Menu, provide a service to food vendors that helps them to manage the allergen and dietary content of their menus, and also uses this as a starting point to link them to relevant local food producers. It uses a combination of Food Standards Agency data with user input, and also commits to publishing their own open data as well.
Other organisations have also been imagining what could be done with more data in the food system. The Institute for the Future has produced a Field Guide to the future of food that includes an imagined app that will tell you how ripe the tomato in front of you is, what recipes you can use it in, what else it goes with. A video of shopping with Google Glass offers another way to present extra information about the products in front of you.
Another approach would be for manufacturers and retailers to summarise the information they hold using a balanced scorecard approach, like the one used by Defra to assess caterers. This could give a single score that brought together a number of dimensions - you could look for a green for health indicator, or one for environmental sustainability, or local supply.
As the amount of data we gather increases, we will need smarter systems to crunch it back down to manageable figures that make it usable.
And with the advent of cheap, ubiquitous sensors in our phones and the new smartwatches, we might soon have much more information: which foods raise our blood sugar, which ones raise our cholesterol , how our heart rate responds to caffeine throughout the day. The same sensors can also transform the production of food – such as tracking how efficient your chickens are at laying eggs.
In this world, our data might have a much more immediate impact on what we choose to eat, and where it comes from.
Photo credit: Rachel Gardner on Flickr https://flic.kr/p/PaGn1