IBM Case Studies China Merchants Bank Enhances Operational Efficiency with IBM IT Operations Analytics Software
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China Merchants Bank Enhances Operational Efficiency with IBM IT Operations Analytics Software

IBM
Functional Applications - Computerized Maintenance Management Systems (CMMS)
Platform as a Service (PaaS) - Application Development Platforms
Construction & Infrastructure
Finance & Insurance
Maintenance
Product Research & Development
Demand Planning & Forecasting
Inventory Management
System Integration
China Merchants Bank, under the leadership of Zhang Xiang, executive of open platforms, was facing a significant challenge due to the rapid changes in online and mobile requirements for banks. The competitive landscape necessitated the bank to increase new product development and enhance operations and maintenance agility. The traditional waterfall approach was proving increasingly inadaptable due to rapid transformations and growth in the bank's business. This led to more demands on IT infrastructure management. The bank needed to ensure stability and efficiency over the long term, while also being agile enough to launch applications fast, diagnose malfunctions in a timely and predictive way, and schedule apps based on wide variations in transaction volumes. To achieve these objectives, the bank had to conduct a performance capacity assessment, which required collecting huge amounts of historical data showing transaction volumes during normal and peak times, as well as growth trends.
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China Merchants Bank is one of the leading banks in China, constantly striving to stay ahead in the competitive banking landscape. The bank is known for its innovative approach to banking solutions and its commitment to providing superior customer service. Zhang Xiang, the executive of open platforms in the IT operations and maintenance management department, plays a crucial role in the bank's IT operations. He is responsible for ensuring the bank's IT infrastructure is robust, efficient, and agile enough to meet the rapidly changing demands of the banking industry. His role involves managing the bank's IT operations and maintenance, launching new applications quickly, diagnosing malfunctions in a timely manner, and ensuring the stability and efficiency of the bank's IT infrastructure.
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To address these challenges, China Merchants Bank deployed IBM Operations Analytics Log Analysis software. This software facilitated the acceleration of collection, analysis, and calculation of key performance indicators (KPIs) relating to a massive volume of activity logs. The bank had previously run a pilot program with an open source platform based on an operational intelligence framework, called Splunk. However, due to its close integration with the bank’s existing suite of IBM application performance management solutions, the bank selected Operations Analytics Log Analysis software. This provided the bank with a unified platform for gathering and analyzing relevant logs and unstructured data. The team also used the IBM solution to quickly and proactively locate faults by taking advantage of the solution’s log management module. The IBM system helped the bank distinguish key events from the bank’s high volume of standard IT infrastructure-related events, accelerating the process of diagnosing and analyzing problems and their root causes, and in some cases even predicting issues before they emerge.
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The deployment of IBM Operations Analytics Log Analysis software transformed the bank's IT operations from reactive to proactive. The software's early warning capabilities and log analysis functions improved the service quality provided by the bank's IT team. The bank was able to distinguish key events from the high volume of standard IT infrastructure-related events, which helped in closing the loop on IT operations and maintenance. The software integrated all business-related infrastructure information, which accelerated the process of diagnosing and analyzing problems and their root causes. In some cases, the bank was even able to predict issues before they emerged, thus enhancing operational and maintenance efficiency.
The IBM solution facilitated a 98 percent decrease in problem query cycle times.
The solution significantly reduced the mean time to recovery.
The bank was able to speed up troubleshooting processes.
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