By definition, eating is one of the purest "gut feel" things any of us do. But there's always been a fair amount of what we now call "analytics" in any human diet, long before computers, databases, and the rest of modern information technology emerged.
Measurement is the heart of analytics, and measurement has always been the essence of food preparation. That's because cuisines have always been the art of measuring, combining, processing, and consuming specific ingredients in specific proportions according to specific steps.
Every culture - in fact, every human - has criteria (often unstated) for assessing the "too much, too little, just right" dimensions of what they're putting in their mouths. Depending on the cultural context, these calculated assessments may or may not involve formal units of measure, but they usually aren't random in nature. That's why cookbooks exist: Recipes present recommended measurements based on what others have found most palatable.
You may have noticed the recent coverage of IBM "Chef Watson." It goes to show that measurements and analytics, in the big data sense, can enliven the postmodern palate.
Cooking has always relied on the food chain to deliver the ingredients for sustenance. Analytics in the modern industrial food chain are amazingly sophisticated. They are light-years beyond what our hunter-gatherer forebears practiced in the field. Every process in the "farm to fork" supply chain - cultivation, processing, packaging, distribution, and preparation - is managed and optimized through big data analytics.
We even have analytics on the consumption side, in the form of ingredients labels, online rating services, and other decision-support resources. Indeed, many modern consumers won't put anything in their grocery carts or go to any eatery unless they've checked it out thoroughly in advance. Not to mention that many of us take our consumption cues from the never-ending marketing campaigns targeted at our tastes and pocketbooks.
If you think about it, agriculture has always been focused on "campaigns," in the sense that structured sets of group activities (such as tilling, planting, irrigating, harvesting) focus on a very specific outcome (such as avoiding starvation for another year). As humans move away from traditional food gathering practices toward repeatable industrial processes, campaigning has become essential to introducing new practices throughout the supply chain. Every innovation in this chain - from cultivation of new crops, dissemination of new farming practices, development of new packaged foods, and popularization of new cuisines - relies on analytics-driven campaigns to overcome traditional practices and to gain widespread adoption.
Overcoming wasteful practices in the food chain is also the stuff of marketing campaigns. For example, the adoption of "precision agriculture" depends on demonstrating to agribusinesses and smaller farmers the value of analytics-intensive practices that rely on big data analytics, embedded environmental sensors, geospatial land-management applications, and more.
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