Visualize and Optimize IT Service Management Processes End-Toend in Real Time.
公司规模
Large Corporate
地区
- Europe
国家
- Germany
产品
- Celonis Process Mining (CPM)
技术栈
- Big Data Analytics
- Process Mining
实施规模
- Pilot projects
影响指标
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 大数据分析
- 分析与建模 - 预测分析
- 功能应用 - 企业资源规划系统 (ERP)
适用行业
- 零售
适用功能
- 商业运营
- 质量保证
用例
- 预测性维护
- 过程控制与优化
- 实时定位系统 (RTLS)
服务
- 软件设计与工程服务
- 系统集成
关于客户
EDEKA Minden-Hannover is a prominent regional company within the German EDEKA corporate group. With approximately 1,550 marketplaces, 1.8 million square meters of retail space, seven production facilities, nearly 67,000 employees, and a turnover of 7.5 billion euros, it is the most profitable regional entity in the group. The company is on a growth trajectory and places a strong emphasis on the performance of its processes, particularly in IT support. The IT Service Desk handles a significant volume of tickets each month, necessitating timely and relevant insights to efficiently process these tickets and maintain smooth operations.
挑战
EDEKA Minden-Hannover faced a significant challenge in managing the daily influx of IT service tickets, which included hardware failures and ERP software issues. The IT Service Desk was overwhelmed with around 15,000 tickets per month, making it difficult to identify relationships between individual and systematic errors. The company needed a solution to efficiently process these tickets, uncover optimization potential, and improve workforce planning. The goal was to have a scalable, on-demand visualization of processes to fully exploit the hidden potential of ticket data, thereby optimizing efficiency and reducing costs.
解决方案
EDEKA Minden-Hannover implemented Celonis Process Mining (CPM) to address their IT service management challenges. CPM acts as a real-time search engine for processes, reconstructing as-is processes using digital footprints stored in the company's IT systems. This allows for real-time visualization of processes and quick identification of inefficiencies. The solution provided full transparency, reduced complexity, and increased process quality. EDEKA's IT experts appreciated the scalability of CPM, which allowed for customized filters and detailed analysis down to individual tickets. This newfound analysis efficiency benefited EDEKA retailers by reducing solution times for IT errors.
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
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.
