Belk Fashions an Analytics-driven Solution Worth Millions in Bottom-line Value
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Antuit's demand forecasting solution
- SAS analytical toolset
- Oracle Replenishment and Allocation
Tech Stack
- Machine Learning
- AI
- SAS Planning
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Revenue Growth
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Inventory Management Systems
- Application Infrastructure & Middleware - Data Visualization
Applicable Industries
- Retail
- E-Commerce
Applicable Functions
- Sales & Marketing
- Warehouse & Inventory Management
- Business Operation
Use Cases
- Predictive Maintenance
- Inventory Management
- Demand Planning & Forecasting
Services
- Data Science Services
- System Integration
- Software Design & Engineering Services
About The Customer
Belk is a leading retail department store with almost 300 stores in 16 states and an online storefront offering fashion apparel, shoes, accessories, and cosmetics. With a history spanning more than 125 years, Belk has established itself as a significant player in the retail industry. The company has millions of SKUs and transactions, making it highly reliant on data and analytics to forecast, plan promotions, manage inventory, and interact with customers. Despite its long history, Belk recognized the need to modernize its operations by embracing advanced analytics and predictive technologies to improve business performance and better serve its customers.
The Challenge
Belk, a historic retailer with almost 300 stores and an online storefront, faced challenges in modernizing its internal planning and fulfillment systems. The company’s previous forecasting practices did not incorporate statistical modeling, relying instead on the average rate of historical sales (ARS). This made it difficult to capitalize on upward trends and minimize the impact of downward trends. Recognizing the value of advanced data-driven decision-making, Belk embarked on a $130 million smart technology initiative to better serve its customers. Building a predictive analytics capability was identified as a top priority, but the company also understood the challenges of changing long-held organizational processes.
The Solution
Belk partnered with Antuit to build an end-to-end solution backed by a single analytical foundation. Antuit's demand forecasting solution, built on the SAS analytical toolset, was implemented across all of Belk’s planning and fulfillment functions, including financial planning, allocation, and replenishment. This solution provided Belk with one enterprise demand signal feeding into each function, ensuring consistent decision-making across the organization. The forecast now accounts for seasonality, promotions, events, and other relevant variables, resulting in a stable and accurate forecast. The company has automated the calculation of replenishment orders with confidence. Accurate financial forecasts allow Belk’s merchants to plan future product purchases by vendor and allocate appropriate amounts of product to each store to maximize sell-through. During the open-to-buy process, reliable forecasts enable merchants to make better and faster business decisions and react quickly to emerging trends. To achieve a seamless, sustainable, and scalable process, Antuit integrated its solution with SAS Planning, Oracle Replenishment and Allocation, and Belk’s internal Assortment Planning system.
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
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.
