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BI Tech Helps Restaurants Round Out a Robust Back-Office

The 2014 Restaurant Technology Study reveals that operators are looking to invest in measures to give managers mobile access to data, boost CRM and improve intelligence. As reporting functionality grows, mobile access to data and operational systems will allow managers to spend less time in the back-office and more time on the floor.

From the front to the back of the house, as technology is creeping into every aspect of operations and customer engagement, information is piling up and at times becoming unwieldy. The amount of data now capable of being collected is staggering, and restaurants are seeking enhanced tools for reporting and intelligence. To track this trend, this year’s study includes a detailed look at current and planned adoption for a variety of reporting and business intelligence (BI) tools. BI and reporting solutions allow restaurant operators to analyze data collected by POS, CRM, and back-office systems in order to spot trends and opportunities, segment top-selling items, analyze customer behavior, target promotions and more.

Current adoption rates for reporting and intelligence tools are behind that of other BOH systems, but there’s a good deal of activity anticipated. Enterprise reporting is the most-used technology on the list (55%). Real-time, web-based reporting systems are used by 45%, and an additional 39% are planning a roll-out. More sophisticated reporting technology, including enterprise management/enterprise resource planning (ERP) and BI systems are currently used by approximately one-third of those surveyed. BI systems will also see significant growth, with 34% planning a roll out. The holy grail of intelligence – Big Data – remains elusive. Just 21% of restaurants in the study have achieved this level of insight. Operators are bullish in this capability, however, and 39% anticipate rolling out Big Data capabilities by 2016.

By digging deeper into data, operators can improve sales and the overall bottom line. At the end of 2013, Pizza Hut reported a consistent sales growth of 5% and 12 times a return-on-investment using a behavioral intelligence tool that targeted campaigns to certain segments of its customer base. The chain was able to segment customers based on purchase tendencies, characteristics and behavioral indicators, helping the company predict future purchases, and target campaigns to a customer’s preferred time and channel, such as email or direct mail.


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