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Transform raw data into profitable insights
Technology Category
- Analytics & Modeling - Data Mining
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - Data Visualization
- Functional Applications - Product Data Management Systems
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Retail
Applicable Functions
- Business Operation
Use Cases
- Retail Store Automation
Services
- Data Science Services
The Challenge
Low data quality, stewardship and governance. Limitation of source system capability. Issues in business process harmonization,standardization.
About The Customer
Africa's largest multi brand retailer with 1200+outlets and having more than 10Bn USD as revenue
The Solution
REIMS(Retail Enterprise Information Management System) REIMS from Tech Mahindra, is a comprehensive solution for business intelligence in the retail sector. It is cloud and mobile enabled solution for Business Analytics on the move.It is a complete solution, combining data cleansing,verification,loading,deployable data marts and a flexible data model.
Data Collected
Buying Habits, Customer Satisfaction Score, Customer Visits, Human Behavior, Supply Chain Optimization
Operational Impact
Quantitative Benefit
Related Case Studies.
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Sennco wanted to help its retail customers increase sales and profits by developing an innovative alarm system as opposed to conventional connected alarms that are permanently tethered to display products. These traditional security systems were cumbersome and intrusive to the customer shopping experience. Additionally, they provided no useful data or analytics.
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Ensures Cold Milk in Your Supermarket
As of 2014, AK-Centralen has over 1,500 Danish supermarkets equipped, and utilizes 16 operators, and is open 24 hours a day, 365 days a year. AK-Centralen needed the ability to monitor the cooling alarms from around the country, 24 hours a day, 365 days a year. Each and every time the door to a milk cooler or a freezer does not close properly, an alarm goes off on a computer screen in a control building in southwestern Odense. This type of alarm will go off approximately 140,000 times per year, equating to roughly 400 alarms in a 24-hour period. Should an alarm go off, then there is only a limited amount of time to act before dairy products or frozen pizza must be disposed of, and this type of waste can quickly start to cost a supermarket a great deal of money.
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The client had previously deployed a one-meter-per-store monitoring program. Given the manner in which energy consumption changes with external temperature, hour of the day, day of week and month of year, a single meter solution lacked the ability to detect the difference between a true problem and a changing store environment. Most importantly, a single meter solution could never identify root cause of energy consumption changes. This approach never reduced the number of truck-rolls or man-hours required to find and resolve issues.
