Digital Transformation in Retail: A Case Study of a Multi-Brand Beauty Retailer
Technology Category
- Application Infrastructure & Middleware - Data Visualization
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Consumer Goods
- Retail
Applicable Functions
- Logistics & Transportation
- Sales & Marketing
Use Cases
- Leasing Finance Automation
- Supply Chain Visibility
About The Customer
The customer is a multi-brand beauty retailer with over 600 stores spread across the Americas. The company was struggling with inefficient planning processes, lack of collaboration between central and local teams, and inability to conduct real-time scenario planning. Their existing systems were a mix of legacy tools, data exports, and disparate Excel spreadsheets, leading to inefficiencies and siloed operations. The company's margin planning, crucial to their global financial performance, was also problematic due to their inability to plan and review margin components and impacts effectively.
The Challenge
The multi-brand beauty retailer, operating over 600 stores across the Americas, was facing significant challenges in its planning process. The company was unable to collaboratively plan between central and local teams and conduct real-time scenario planning. The existing Merchandise Financial Planning (MFP) ecosystem was a combination of a legacy planning tool, data exports, and disparate Excel spreadsheets, leading to inefficiency throughout the planning process. The company's margin planning, a critical link to their global financial performance, was also problematic as they could not plan and review margin components and impacts. Furthermore, the marketing, sales, finance, and supply chain functions were operating in relative silos, each having their own assumptions and versions of the truth.
The Solution
The company adopted o9’s Digital Brain to streamline and automate the collaboration between different teams and remove repetitive manual inputs from individual planners. This solution provided the ability to plan sales and gross margin by type and manage gross margin across channels with increased visibility and collaboration. With the o9 Digital Brain, users can now plan in local currency based on their scope of responsibilities and convert any of their actual or plan measures between currencies with the click of a single button. The company also used o9 as their differentiated collaborative platform for Integrated Business Planning, driving more fact-based decision-making, enabling faster execution and better accountability. The company implemented the o9 Enterprise Knowledge Graph to run Strategic Planning, Pre-Season Planning, and In-Season OTB, one single integrated collaborative platform, bringing one single source of truth.
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.
.png)
Case Study
Improving Vending Machine Profitability with the Internet of Things (IoT)
The vending industry is undergoing a sea change, taking advantage of new technologies to go beyond just delivering snacks to creating a new retail location. Intelligent vending machines can be found in many public locations as well as company facilities, selling different types of goods and services, including even computer accessories, gold bars, tickets, and office supplies. With increasing sophistication, they may also provide time- and location-based data pertaining to sales, inventory, and customer preferences. But at the end of the day, vending machine operators know greater profitability is driven by higher sales and lower operating costs.
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
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
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.
