siliconindia | | January 20199The most obvious fascination was that the entire setup was the result of analytics ­ data analytics at the minutest and at the most incredible levelsWith data from KOT (Kitchen Order Tokens) and online orders to reviews on websites, it figured out that the most commonly ordered dish in the restaurant was biryani; es-pecially, chicken boneless biryani. Through specific data touch points, it also found out that Tuesday saw the least takers for biryani. With the restaurant also serving north Indian, Chinese and south Indian dishes, data showed that biryani was the most popular order to be served.Moreover, I found that when serving multiple delica-cies often led people into dilemma. People thought over the food to order and had to consider starters or soups, a main course and more. But that wasn't the case with biryani. There was just one decision ­ biryani. This was one of the crucial pieces of insights that it uncovered with analytics.Next, it also set itself apart in its service by making it quick and making sure more people ate at a given time. The supply-chain management involved analytics, which made sure there were enough variants of biryani ready for takers, regardless of the volume. With analytics, again, it was found that an average table finished their meal within 25 minutes, including a beverage. For that, an order had to be taken by the stewards within 2 minutes of guest's arrival and be served in the next five minutes. Being the comfort food, guests usually shifted their focus to the food after it arrived and after the next 20 minutes, the table would be free for next service. Analytics & Portion ControlWhat was also interesting was the amount of wastage the restaurant managed to reduce. Though most of us never leave a single grain of biryani on our plates, we often leave garnishes, accompaniments and flavouring agents. The restaurant found a way to incorporate them into the food by blending them together and adding them with the ginger garlic paste so that along with the flavour, coriander leaves and other garnishes never went to the garbage bin.I was also surprised the first time when I noticed that no plate had cloves, mace, bay leaves, star anise and other dry spices. Besides, they even classified their serving portions to cater to the different takers of biryani and avoid further wastage. They introduced portions of quarter plate biryani to cater to food enthusiasts (not foodie) like me. Usually, it's after your plates over by 80 percent that our stomach begin to feel content. This restaurant allows you to eat just the right amount.Analytics & Production VolumeAnalytics is involved in every step of making biryani. More so, in its service too! Analytics is involved in deciding how much biryani has to be made each day and corresponding-ly decide on the volume of raw materials to be purchased. For a bulk production of 20 kilograms of biryani, analytics can tell you how much meat is required, the vegetables, the spices, flavouring agents and the volume of water and fuel. Raw materials, again, tie back to the crucial concept of supply-chain management, where stock is replenished as per the demand. Being a busy restaurant, the joint cannot afford to run out of ingredients and analytics will take care of the supply-chain management of all raw materials.Apart from the main ingredients, the ones for biryani's accompaniments have to be taken into consideration as well. Onion, for instance, has to be considered as a raw material for biryani and for an accompaniment as well.If you think these are the factors, the game is just half over. For it to get served onto your plate, a new set of an-alytics comes into the picture. A simple example is plates! The number of plates in the restaurant has to be thrice the number of restaurant's cover, considering the turnaround time for pot-washing. Imagine making a customer wait for food because there are no plates to serve! Also, fac-tors like breakage have to be considered to maintain the supply-chain.For a layman, it's that twenty minutes of me time with biryani. For a data scientist, it's how the plate got there. That's data science for you!
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