2015 QPRC

How to Early Detect Pervasive Quality Issues: A Business Case in Using Perceptual Quality Control Methods with SAS Text Analytics, Murali Pagolu, SAS Institute and Mohammed Chaara, Lenovo

Abstract:

Quality issues can easily go undetected in the field for months, even years. Why? The list is long, but generally it’s due to:

• Internet: Customers are more likely to complain through their social networks than directly though customer service channels.
• Organizational Silos: customer complaints are often handled by marketing or customer service and aren’t shared with engineering.
• Technology: systems are designed with business rules to find “out of spec”, or trigger when a certain threshold of reported cases before engineering is involved.
• Data: organizations can only react to what they know about.

So what if you could infuse the voice of the customer directly into engineering and detect emerging issues months earlier than your existing process? Your costs will go down. Your customer satisfaction will go up. Join our conversation and learn how you can get started. We’ll cover:

• What is perceptual quality
• Why you should care about perceptual quality
• Where to look for perceptual quality data
• How Lenovo is seizing the opportunity
• Best practices for starting your own perceptual quality program