Traditionally, food consumption meant a long process for the consumer: deciding the menu (recipes), compiling lists of ingredients, buying the ingredients (supermarket), preparing the ingredients (kitchen table), storing the leftovers (fridge), cooking ingredients (stove), and eating. And the food supply chain that precedes that process is even more complex: production, processing, and distribution. It’s these complexities that make innovating in the food space so alluring. Hundreds of food startups have emerged as breakthrough solutions to streamline different parts of the processes, all trying to get a piece of the pie. But perhaps one of the most successful is the dinner-kit delivery service, Blue Apron. Because of its disruptive stance to untangle the entire process through an unconventional user experience, and use of data analytics, it’s managed to expand exponentially.
The Future of Consumption
Blue Apron started in NYC in 2012 as another food-tech solution to determining what will go on consumer’s plates. What makes it different from most delivery systems, is curation. Meal/restaurant delivery systems like Grubhub, Delivery.com or Maple delivery ready made meals, prepared either by a restaurant or commercial kitchen, and grocery delivery systems like Fresh Direct, or Instacart deliver bulk, a la carte ingredients to the home. Blue Apron strives to insert itself at the intersection of the two: delivery of recipe-specific pre-portioned ingredients that just need to be cooked. This is its largest value creation point. For the first time, consumers can receive fresh food that’s exactly what they need for predetermined recipes. Their search is over.
The way Blue Apron captures value is through a modified subscription model. They consumer signs up to receive their first delivery (usually free through recommendations from friends already on the service), and is automatically enrolled to receive a package every week at the meal plan they selected to receive. The plans range from a 2 person plan with three recipes, or a family plan with either 2 or 4 recipes, amounting to approximately $9-$10 for each meal. When compared to how much a family spends on groceries, this is a little bit higher, but convenience and lack of food waste makes it alluring.
The Food Chain 2.0
Core to the success of the system, is a robust data analytics structure. The knowledge of variables and their relationships is necessary for Blue Apron to sustain the fluidity of its system. The way in which the startup navigates its offerings is through the complex balancing act between supply chain,
Supply: Currently for farmers, it’s hard to predict demand on their specific crops, but with a system like Blue Apron and the fact that it has a subscription service, they can start to guarantee demand for farmers. Because Blue Apron has pre-set menus every week, they partner with farmers directly to receive large supplies of specific food to fulfil the dinner-kits. To avoid shortages of ingredient supplies, Blue Apron works with suppliers when planning menus, taking into consideration the variables of seasons for the crops, size of crops, availability, and storage time. Because of this, they often work with the farmers to plant crops specifically for the service in advance, in anticipation of the growing seasons, and coordination of crop rotations and harvests.
But, what is interesting is that there is a limitation of the types of crops that could be included in the recipes as well. There is also the variable of the portion sizes that are appropriate for the dinner-kit packs. For example, a crop like a squash could perhaps grow too big of a size to be included in the delivery, so the company has to also factor in the ideal crop size. In applying data analytics to the supply chain system, Blue Apron also has the ability to work with the workflow of the farmer. This allows for less waste of crops, because they can order produce that is in season, and minimize cost of distribution for out of season crops.
Demand: There is a delicate balance between the food that’s being supplied, and the meals that consumers want. The logistics behind meal selection range from predictive popularity, to restricting pairing of the popular meals in real time, and anticipatory demand per week. Users have the ability to choose 3 meals from a range of 6, but as they consumer clicks through one meal, one grays out. This is a real-time adjustment for overselection of the most popular recipes, which would result in a shortage of some ingredients and surplus of others. There is an algorithm that attempts to predict, based on previous purchases, the popularity of specific ingredients, so that future recipes would appeal to a greater consumer pool. And in the event that there is a surplus of ingredients, there needs to be a readjustment of recipes to account for the ingredient in excess, so that there isn’t any wasted food.
What is different about Blue Apron, than the traditional methods of food or ingredient delivery, is the fact that with metrics, it can have each side of the supply-demand chain determine the necessities for the other side. A surplus could be easily corrected by the item utilization in a recipe. High demand of a recipe could be balanced out by the limitations of combinations. This isn’t necessarily easy for other delivery systems to achieve. For example, GrubHub can’t easily promote restaurants that need more customers, the same way that Fresh Direct can’t control which ingredients customers could buy based on the supply, because they don’t work with the supply directly.
How to innovate
The beauty of Blue Apron is its “no frills”approach to a home-cooked meal, and the way it can gracefully balance out its offerings to work with the ingredients it has available. But some of the future issues it could potentially have lie in the nature of its user experience. Because it’s so dependent on making sure that there is a near zero difference between the subscribers and the food it predicts will be ordered, there needs to be a guaranteed constant consumer base. When the members have the option of skipping weekly meals, without any penalty or restriction, there is less stickiness in the service. If Blue Apron perhaps had a minimum number of meals, or a true subscription model, then people might not drop off as often, and feel more committed to it as a habit rather than just a luxury. Another challenge is the possibility for people to get good enough at cooking after taking off the “training wheels” that Blue Apron offers, and start to purchase their own groceries. This could pose a significant issue especially because there isn’t enough stickiness in the service, except for convenience. If Blue Apron perhaps migrating to offering an a la carte ingredient marketplace (pre measured for recipes selected by consumers), then perhaps it could grow to be relevant for the user base that has “graduated.”