Download PDF
PLASTIC JUNGLE cut through the wild world of data.
Technology Category
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Retail
- E-Commerce
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- Software Design & Engineering Services
- System Integration
The Challenge
Plastic Jungle’s business success is predicated by its ability to move faster than the competition. When the company brought in a new CFO in 2012, he aimed to deploy a data solution that would match the company culture. Speed, accuracy and agility were the key tenants for the company data approach. “We wanted to make sure we didn’t paint ourselves into corner by taking a traditional approach to data warehousing.” That meant a solution that could grow to massive amounts of data, and allow regular business users to work with data quickly without requiring a huge investment that would leave them beholden to the product.\n\nPlastic Jungle's BI requirements included the ability to:\n• Manage and sustain the entire operations aspect of Plastic Jungle’s data warehouse with little or no operating support from the engineering and IT staff\n• Allow business users to create any ad-hoc reports they required\n• Provide the abstraction layer between the schema and the metrics that the business sought\n• Refresh in close to real-time – a minimum of once per day, and ideally every couple of hours\n• Not incur a significant capital outlay
About The Customer
Plastic Jungle was founded to help customers tame the plastic gift card jungles of their junk drawers. The company’s unique service allows people to trade unwanted gift cards for the gift cards they actually want to use. To date, the company has sold over $30M worth of gift cards and 400 merchants partner with Plastic Jungle, whose technology has verified, traded, and sold millions of gift cards to date. The company aims to provide a seamless and efficient platform for users to manage their gift cards, ensuring they can easily exchange them for more desirable options.
The Solution
After conducting extensive research, Bhattacharya had narrowed down options to an open source BI tool, a leading commercially available tool, and Sisense. The team chose Sisense because of the technology’s immediate return on investment. Sisense did not require a dedicated IT person to support its deployment and use. “The other tools seemed to require a technical or development team to implement and manage,” he said. Plastic Jungle didn’t believe that success in the world of data should require people in addition to software. The old approach to data simply didn’t fit with the company’s efficient and forward-looking operations.\n\n“The other great advantage”, says Bhattacharya, “is Sisense’s approach to complex data operations. You don’t have to be a PhD of Analytics to build and maintain a Sisense solution. Even for ETL, Sisense’s flexibility allows anyone to work with data in a few clicks. The company’s secret sauce, the ElastiCube, is simply superior.”
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Improving Production Line Efficiency with Ethernet Micro RTU Controller
Moxa was asked to provide a connectivity solution for one of the world's leading cosmetics companies. This multinational corporation, with retail presence in 130 countries, 23 global braches, and over 66,000 employees, sought to improve the efficiency of their production process by migrating from manual monitoring to an automatic productivity monitoring system. The production line was being monitored by ABB Real-TPI, a factory information system that offers data collection and analysis to improve plant efficiency. Due to software limitations, the customer needed an OPC server and a corresponding I/O solution to collect data from additional sensor devices for the Real-TPI system. The goal is to enable the factory information system to more thoroughly collect data from every corner of the production line. This will improve its ability to measure Overall Equipment Effectiveness (OEE) and translate into increased production efficiencies. System Requirements • Instant status updates while still consuming minimal bandwidth to relieve strain on limited factory networks • Interoperable with ABB Real-TPI • Small form factor appropriate for deployment where space is scarce • Remote software management and configuration to simplify operations
Case Study
How Sirqul’s IoT Platform is Crafting Carrefour’s New In-Store Experiences
Carrefour Taiwan’s goal is to be completely digital by end of 2018. Out-dated manual methods for analysis and assumptions limited Carrefour’s ability to change the customer experience and were void of real-time decision-making capabilities. Rather than relying solely on sales data, assumptions, and disparate systems, Carrefour Taiwan’s CEO led an initiative to find a connected IoT solution that could give the team the ability to make real-time changes and more informed decisions. Prior to implementing, Carrefour struggled to address their conversion rates and did not have the proper insights into the customer decision-making process nor how to make an immediate impact without losing customer confidence.
Case Study
Digital Retail Security Solutions
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.
Case Study
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.
Case Study
Supermarket Energy Savings
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.