Data-Driven Manufacturer: Managing Operations with Search-Driven Analytics
Customer Company Size
Large Corporate
Country
- United States
Product
- ThoughtSpot
- Cognos
- Oracle OBIEE
- QlikView
Tech Stack
- Search-Driven Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
- Waste Reduction
Technology Category
- Analytics & Modeling - Real Time Analytics
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Semiconductors
Applicable Functions
- Business Operation
- Quality Assurance
Use Cases
- Root Cause Analysis & Diagnosis
- Predictive Maintenance
- Supply Chain Visibility
Services
- Software Design & Engineering Services
- System Integration
About The Customer
The customer is a global semiconductor manufacturer that produces billions of computer chips annually. The company is focused on moving new ideas through the development process quickly and efficiently to maximize revenue. They operate in a highly competitive market where margins are thin, and the ability to bring products to market faster than competitors is crucial. The company is involved in various aspects of manufacturing, from supply chain and facilities management to product design and human resources. They are constantly seeking ways to identify bottlenecks and optimize production operations to maintain their competitive edge.
The Challenge
For a global semiconductor manufacturer, the challenge was to streamline engineering operations to build higher-performing products, reduce operational costs, and outpace competitors. The engineering teams were using multiple BI tools like Cognos, Oracle OBIEE, and QlikView to gain visibility into product and operations data. However, these tools were too complex for engineers, leading to a heavy reliance on the BI team to set up data and produce reports. This dependency created a bottleneck, slowing down production across product lines as the overworked BI team struggled to deliver data quickly enough.
The Solution
To address the bottleneck issue, the semiconductor manufacturer implemented ThoughtSpot, a BI solution that allows for easy analysis across multiple data sources. This solution enabled engineering management to analyze headcount, design goals, and project milestones by product and tier, optimizing the entire delivery process. With ThoughtSpot, engineers no longer have to wait for the BI team to create reports; they can use search to analyze and drill down into any metric themselves. This self-service analytics approach has become an integral part of the BI stack at the manufacturer, allowing various teams to perform root-cause analysis, optimize the supply chain, and identify trends in customer service.
Operational Impact
Quantitative Benefit
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