Chain Store Performance Monitoring Solution: Case Study
ChallengeA major fast food company, with annual revenue exceeding billion dollars a year, has thousands of chain store restaurants located in multiple countries around the world. These restaurants sell fast food, desserts, and other beverages to hundreds of millions of customers, who give millions of voice of customer (VoC) feedback through surveys and call centers, every year. This fast food company wants to be known for quality. To continually improve overall quality, and in turn, customer satisfaction, the company decided to measure and track the performance of each store. The company wanted to implement this decision by analyzing VoC feedback, weighing the analysis results against hundreds of criteria, and tracking the performance over time. As a leader in the fast food industry, the company is under the media’s watchful eye where bad news travels fast and can immediately damage its brand image. The company realized its need to identify and monitor the emergence of critical issues that required the immediate attention of its management teams. This required scanning approximately 4,000 responses of text feedback received from customers every day. From an operational perspective, the company wanted a customizable and automated solution to process millions of VoC feedback from thousands of stores as well as to accommodate the requirements of its ever expanding and dynamic business operations: opening new stores, adjusting administrative regions, and making changes to store management. The company desired uniformity and transparency in the performance measurement process. It was essential for the company to have management reports that were easily accessible and interpretable to meet the needs of its managers from seven different departments.
SolutionWithin two months of launching the project in October 2014, Megaputer Intelligence (Megaputer) developed and deployed the Store Performance Monitoring Solution (SPMS): a custom solution that generates scorecards for each store based on the analysis of customer feedback. The solution employs a combination of innovative linguistic, semantic, and machine learning techniques to analyze and score textual customer feedback against multiple criteria defined by the fast food corporation. Megaputer was able to develop SPMS quickly as the solution was based on its proprietary data and text analysis software, PolyAnalyst. The customized solution provided comprehensive data management, text analysis, and reporting capabilities. SPMS automatically downloads the data from the company’s secured site at 4:00 am daily. The system verifies and analyzes this data to generate the case-based alert reports that designated managers have access to through a link in emails sent out by the system. These designated managers are now empowered to start addressing the alert issues as early as four hours after receiving the VoC feedback.
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ResultsThe implementation of SPMS yielded a multi-purpose solution with no limitations to the number of VoC feedback records processed or the number of store locations. It allowed real time performance monitoring, facilitated increased customer insights and ensured consistency and transparency of results. The system also provided an interactive user interface with multiple data views, drill-downs, and data export capabilities. Managers at the fast food corporation can now make better business decisions based on reliable, accurate, thorough, and timely reports. The improved level of reporting detail and accessibility enabled
BenefitsSPMS helped the client successfully address multiple challenges simultaneously. Key current and potential benefits from implementing SPMS include: Crisis Alert Management. SPMS monitors all VoC records and generates an alert report every morning to highlight any potential crisis situation or issues originating from the previous day. The system delivers the alert report to managers, enabling them to intervene and fix issues in a proactive manner to ensure brand image and customer satisfaction are upheld. If the corporation’s management decides to shorten the reaction time, the system can be configured to generate reports multiple times every day. The system can also be set up to monitor and analyze comments on the company’s social media sites. Increase Customer Loyalty. SPMS analyses VoC text feedback in sufficient detail to give direction to the fast food company on what is working and what needs improvement. This can help the company identify root causes of customer churn. Now the company can find and implement Best Practices across all its stores, thus increasing customer satisfaction and customer loyalty. Performance management. SPMS enhances the company’s capability to perform real time performance management. It generates a series of daily, weekly, and monthly reports for managers from seven different departments and makes these reports available through a secure online connection. These reports are interactive, flexible, and extremely convenient to view and use. It is easy to extract and compare performance over time at a store, city, region, or franchisee level. Moreover, the automated solution establishes consistency of analysis throughout time and across organization. New Launch Performance Tracking. The VoC feedback for a new product or store launch can be filtered and tracked on a daily basis. This makes the company aware of the performance on a real time basis and helps the managers minimize risks associated with new launches. Relevant Menu Offerings. SPMS can analyze VoC records to find the pulse of the customers: what they like and what they do not like to eat. This can go a long way in keeping the menu relevant by introducing food offerings (including combinations) that people like as well as removing menu items that people do not like. This exercise can be done at all levels: national, region or even at a city level. The implementation of SPMS resulted in increased customer satisfaction. The fast food company now tops its competitors in the customer satisfaction index. This is game changer for the company in an industry where customer satisfaction and customer loyalty are immensely important. Overall, the company’s same-store sales increase in 2014 was more than twice the industry average. Encouraged by the ease in measuring and tracking the performance of stores as well high accuracy of results generated, the company is planning to open hundreds of new franchisee store locations by the middle of 2016.
Now you’ve read this case study, comment on the usefulness of Chain Store performance Monitoring Solution for a large food and retail company. Think about how data analytics and performance monitoring could be used to tailor the needs of your business.
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