Every customer walking in, every food item ordered, each new tweet or Facebook post, every transaction recorded, each shift of employees working, any promotion offered are all the myriad forms in which valuable data is manifesting today. The actual challenge is to record the data so that it is put to good use for various business decisions, thereby generating extra dollars from the data. Experience suggests that about 7 percent lift in top-line and 2 to 3 percent improvement of bottom-line can be achieved if the data is used well.

It is a gold mine waiting to be tapped, but how to do it best?

There are two key steps to enable your data generate dollars in the future:

Data Cleaning and Preparation

Cleaning and preparing the data poses a huge challenge and requires expertise to merge different data sets, convert them to usable formats, filter out the bad data and then set the ball rolling for meaningful analysis to be done on the prepared data. Therein lie the first two lessons for good data analytics: A. capture and keep your data at the transaction level. The more detail you have the better your analytics can be; and B. data cleansing is an important first part of analytics. Garbage in equals garbage out and hence good cleansing is must. Issues of multiple data sources with conflicting data, improper details being captured, frequency of data capture, readable formats/structures, data hierarchy are the most common issues and take the maximum time to clean and structure the data. Although few tools are available but usually the challenges of improper data are unique to every organization and requires significant time and effort to sort out.

Analytics-Driven Business Insights

Hypothesis driven approach toward data analytics always proves to be the best when evaluated basis the returns on investment. This is also where the business understanding and judgment comes into picture. Senior management will have the best view of areas of inefficiency in the business. Starting with a set of hypothesis, the data ninjas can slice and dice the data into meaningful chunks to draw insights worthy for making business decisions. Some of the most common approaches and analytics used by various quick service establishments are the following: Clustering the different menu items basis their sales and margin performance; dividing store locations into performance buckets based on location, pricing, competition etc. Some of the business levers that can truly be affected by pin-pointed analytics are pricing and promotions, forecasting, menu optimization, customer loyalty, and operations optimization. Let’s break them down.

Pricing and Promotions

There are opportunities to rationalize prices based on competition—especially with different sized products. Promotions can be developed to increase sales during non-peak hours and frequent items bought together can be identified and bundled to increase ticket sizes. Realizing the best and toxic promotions helps to reduce dollar wastage on promotions that do not yield desired outcomes.


High accuracy sales forecasts enable the team to plan for raw materials as well as staff requirements. This not only helps to reduce wastage, but products or stores that are prone to run out of high margin food items toward the end of the day can be tracked and sales lift can be achieved. Forecasting also improves the inventory planning and ordering more so in case of perishable products with smaller shelf lives. Ability to increase or reduce manpower with every hour can help to reduce overtime/employee costs. Hourly trends on transaction and footfall can be used to forecast staffing needs.

Menu Optimization

A lot of slow moving, low margin items can be identified and removed from the menu to increase focus toward better selling and higher margin products. Ensuring right balance of items across different segments of the menu creates proposition to attract all sets of customers. Striking differences in the perceived and actual performance are of various items is very common when it comes to menu re-engineering.

Customer Loyalty

Capturing information about customers and personalizing offers, products, rewards for every customer is the way forward. Mobile apps and loyalty card programs are the best way to gather customer behavior and preferences to begin with. Ability to identify trends and segment customers into buckets helps targeting and setting business strategy easily. The quick-service world is moving fast toward loyalty to enhance customer stickiness with a high degree of personalization, all powered with data analytics

Operations Optimization

Operational challenges like queue lengths, internal processes, quality enforcement, pilferage checks, etc., can be built using advanced analytics tools and processes. They go a long way in streamlining the operations and also reduce the administrative overload in restaurant operations.

Analytics can be quite helpful to boost revenues as well save costs for any business, particularly restaurants. The fact that analytics models and practices are scalable across any number of stores/locations/items makes it even more attractive for restaurant and food chains to adopt in the digital age.

Prashant Agrawal is the Founder and CEO of Impact Analytics. He has 20-plus years of professional experience across Management Consulting (with McKinsey and Boston Consulting Group) and Private Equity. In past, he has been a contributor to the Wall Street Journal, The New York Times, and Hindustan Times.”
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