Thomas & King Optimizes Store Performance with Next-Gen BI Solution

Thomas & King, headquartered in Lexington, Kentucky is the eighth largest restaurant franchiser in America with more than 7,500 employees, 90 Applebee's restaurants and seven Carino's Italian Grill restaurants. Exceeding the expectations of restaurant customers and employees has always been a large part of Thomas & King's workplace culture, but when it came to store reporting and leveraging information to optimize store performance, the processes were outdated and in need of an overhaul.

There was a wealth of data for decision-making but no coherent data structures across brands. The outdated spreadsheet-based reporting that was in place was not only one-dimensional, but it did not easily support drill-down analysis. Only the IT and accounting departments could respond to any type of new reporting and analysis requests, which were always needed immediately and diverted costly work hours from other projects and responsibilities. Above Store Reporting (ASR), driven by Business Intelligence (BI) technology, was becoming a threat to Thomas & King's growing position in a hyper competitive market, and there was a clear need for an ASR and quickly.

Lacking the time and resources to implement traditional OLAP tools, Thomas & King turned to the QlikView associative for in-memory analysis during evaluations of the leading BI products in Q4 of 2006 for the 2007 budgeting. It was hoped that QlikView would support both consolidated high level views of information for executives and deep granular data cuts for analysts.

Thomas & King's first QlikView dashboard took only eight workdays to develop and it delivered immediate value. Today, doing data comparisons that result in smarter business decisions with data views are no longer an idea to reach for. The QlikView dashboards support multiple organizational hierarchies and hierarchies within data sets for every imaginable metric down to store level.

QlikView's short development cycle has enabled Thomas & King to quickly respond to business needs. The average implementation time for a new type of analysis is two weeks and now power end users, who are business not technical people, can have solutions up in days. Any end user can customize a dashboard or analysis that someone else created to their own specific needs.