Download PDF
Using Analytics to Create a Performance Culture and Climb to the Top
Technology Category
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Visualization
- Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
- Retail
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Retail Store Automation
Services
- System Integration
- Training
The Challenge
Having experienced rapid growth of its business, Snow Peak recognized its retail operations were highly fragmented, with store managers provided a broad authority over store layouts and operations. Additionally, the organizational culture was not adequately rooted in performance and accountability as there were limited data points -POS data, the number of new customers acquired and a manual tracking of the number of shoppers per day -to measure store performance. In order to keep its attention keenly focused on providing the finest products and services to its discerning clientele, Snow Peak committed to establishing baseline retail operations metrics and creating and empowering an organizational culture based on performance, accountability and continuous improvement.
About The Customer
Founded in 1958 in Sanjo City, in the Chūetsu region of Japan’s Niigata Prefecture, Snow Peak is an innovator of outdoor apparel and gear, whose very name originates from the famous mountain Tanigawa, where Snow Peak’s founder Yukio Yamai repeatedly challenged himself, physically and mentally, throughout his early life. Those personal experiences drove Yamai to create innovative mountaineering equipment utilizing the region’s highly skilled metal technology. Over time, Snow Peak evolved by shifting its focus from the mountaineering equipment of its past to the camping equipment of its future, releasing a series of radically innovative products focused on quality, functionality, timeless-durability and considered design. Today, Snow Peak’s mission is to ‘restore humanity’ in our increasingly digitized world by connecting people with nature and other people by providing goods and services that enable an outdoor lifestyle.
The Solution
Snow Peak approached its efforts with a three-stage implementation plan: Stage one: Design and implement a fundamental baseline for store operations and performance. Stage two: Rollout baseline and identify organizational best practices. Stage three: Identify and capitalize on continuous improvement opportunities. Snow Peak utilized RetailNext in-store analytics to design its key performance indicators (KPIs) and implement its system across its company-owned stores, with critical KPIs including capture rate (percent of store passersby who enter the store), conversion (percentage of store shopper traffic who completed a purchase transaction) and the efficiency of staff scheduling. With metric-based systems in place at all retail locations, Snow Peak then conducted extensive training for managers and sales associates, including processes and systems, change management, and product and portfolio training. Furthermore, Snow Peak instituted monthly and quarterly reviews with RetailNext consultants to reinforce learning and develop data-based insights for performance feedback loops. Now in its continuous improvement stage, Snow Peak is further fostering its self-sustaining retail performance culture with KPI-based reviews, including store manager reviews, customer engagement reviews and staff coaching, utilizing analytic outputs like kinetic heat maps to judge the engagement effectiveness of store layouts and merchandising displays, and traffic reviews to identify the factors influencing shopper traffic to stores.
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.
