Technology Category
- Analytics & Modeling - Predictive Analytics
- Sensors - Level Sensors
Applicable Industries
- Apparel
- Retail
Applicable Functions
- Sales & Marketing
Use Cases
- Demand Planning & Forecasting
- Inventory Management
About The Customer
Buffalo David Bitton is a leading fashion brand founded in Montreal, Canada, in 1985. The brand sells denim collections targeted at men and women ages 18 to 34 in stores spanning 18 countries and 3,000 locations worldwide, as well as online. The company operates in a fiercely competitive apparel industry, making it vital to make the right style, color, and size choices, and ensure that the right amount of stock is allocated to the right sales channels at the right times.
The Challenge
Buffalo David Bitton, a leading fashion brand, was facing challenges in analyzing, planning, and forecasting demand and inventory for its wholesale, online, and in-store channels. The company's sales channels were run on different software systems, and its financial data was managed in another system. This disparity made reporting a laborious process, hindering the company's ability to make timely decisions. The company needed a solution that would provide a holistic view of sales trends across all channels, ensuring the right products were always available to appeal to each customer. The existing systems, while efficient for day-to-day operations, had limited reporting capabilities, making it difficult to gain an overall view of the business or to analyze data in detail.
The Solution
Buffalo David Bitton, with the support of IBM Business Partner Knowledge Providers Inc. (KPI), deployed IBM Cognos TM1, an integrated suite of analytics and planning tools. This solution could handle demand planning, forecasting, budgeting, and scorecarding. KPI helped Buffalo implement financial and operational reporting, analytics and budgeting, demand planning, and dashboarding. The solution allowed all these applications to communicate with each other and be leveraged across all parts of the business. By harnessing IBM analytics and performance management tools, Buffalo transformed its ability to support decisions with timely, accurate data. The company could now see vendor performance or product performance at the style, color, and size level, and automatically feed that information into reports, dashboards, and planning and budgeting applications.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Fire Alarm System and Remote Monitoring Sytem
Fire alarm systems are essential in providing an early warning in the event of fire. They help to save lives and protect property whilst also fulfilling the needs of insurance companies and government departments.Fire alarm systems typically consist of several inter-linked components, such as smoke detectors, heat detector, carbon monoxide, manual call points, sounders, alarm and buzzer. The fire alarm system should give immediate information in order to prevent the fire spread and protect live and property.To get maximum protection a shoe manufacturer in Indonesia opted for a new fire alarm system to monitor 13 production sites spread over 160 hectars. Although the company had an existing fire alarm system, it could not be monitored remotely.It was essential that the new system would be able to be monitored from a central control room. It needed to be able to connect to the existing smoke detector and manual call point. Information should be easily collected and passed on to the Supervisory Control and Data Acquisition (SCADA) system. Furthermore, the system should have several features such as alarm management, auto reporting, being connected to many client computers without additional cost, and run 24/7 without fails. The company also needed a system which could be implemented without changing the architecture of the existing fire alarm system.
Case Study
IoT Applications and Upgrades in Textile Plant
At any given time, the textile company’s manufacturing facility has up to 2,000 textile carts in use. These carts are pushed from room to room, carrying materials or semi-finished products. Previously, a paper with a hand-written description was attached to each cart. This traditional method of processing made product tracking extremely difficult. Additionally, making sure that every cart of materials or semi-finished products went to its correct processing work station was also a problem. Therefore, the company desired an intelligent solution for tracking assets at their factories. They also wanted a solution that would help them collect process data so they could improve their manufacturing efficiency.
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.