The Role And Evolution Of Advanced Analytics In The Process Industries

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To improve a plant’s operation, it is important to understand it’s potential for improvement so that the right actions can be taken. Plant data and advanced analytics are the keys to maximizing plant performance. This keynote presentation will highlight the role of advanced analytics and its evolution in the years to come.”

Technologie

Steven “Steve” M. Sliwa, Ph.D.
Chief Executive Officer
Seeq Corporation
November 12, 2020
The Role and Evolution
of Advanced Analytics in
the Process Industries

Outline
1. Background & Challenges
2. Evolution of Advanced Analytics
3. Digital Transformation Implications
4. Key Enablers
5. Examples
6. Conclusions

Sensor Data Unaddressed by Modern BI Tools

Motivation for Advanced Analytics
1 & 2 MIT Technology Review, May 2013; 3 McKinsey, “TheInternet of Things” 2015

Advanced Analytics Stages of Actualization

Implications for Digital Transformations

Key Enablers
 Convergence of Digital Science & Operation Technology (OT)
 Self-Service Data Analytics
 Data Analytics & OT Collaboration
 Speed Adoption of New Algorithms
 Growth Beyond Subject Matter Experts
 Knowledge Captured & Integrated
 Business Process Owners Can Exploit
 Virtual Collaboration

Example 3: Rapid Deployment of Algorithms

The names of corporations, organizations, products and logos herein are either registered trademarks or
trademarks of Yokogawa Electric Corporation and their respective holders.
Future of Advanced Analytics
Process Data Value Proposition Points
to Significant Upside
Advanced Analytics Drives Data to
Information to Insights to Profits
Needs to Be Included with Digital
Transformation Projects

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