Oracle VoC Analytics:Automotive Quality Issue Detection

Oracle Automotive Quality Analytics Solution 2

DLX Auto

Oracle Automotive Quality Analytics SolutionAccording to the National Highway Transportation Safety Administration (NHSTA), more than 56 million vehicles were recalled in 2014. Recalls represent the most costly outcome of quality problems. Ideally, automotive quality issues should be caught as early as possible in the product development process, before newly launched vehicles actually enter into production. However, once vehicles enter the marketplace, warranty and recall costs are dramatically reduced the sooner quality-related issues are detected in the field.

Oracle Automotive Quality Analytics Solution: Rapidly Detect and Investigate Quality IssuesThe Oracle Automotive Quality Analytics Solution provides a robust platform to quickly detect and investigate quality issues within the field. The solution is comprised of the following components:

1. Voice of the Customer (VOC) Listening PlatformA robust platform to collect, categorize and standardize unstructured (text based) “voice of the customer” data from a wide variety of data sources (i.e. warranty records, chat logs, call center transcripts, technical assistance center records, dealership service records, social media comments, user forums, etc.). Once unstructured, text based data is standardized, it becomes much more suitable for quality issue analytics.

2. Quality Issue Early Detection Dashboard A Business Intelligence dashboard, organized around specific automotive functional areas, providing instant visibility to quality problems trending within the vehicle.

3. Quality Issue Rapid Investigation PlatformAn information discovery platform for rapid drill-down and investigation of specific quality related issues (i.e. investigate the impact of vehicle VIN’s, options, geographical regions, supplier parts, date of manufacture, etc.).

Oracle Automotive Quality Analytics Solution 3

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I. Voice of the Customer Listening PlatformWithin the automotive industry today, automakers are striving to get closer to their customers and provide a superior customer experience. The “voice of the customer” can be an important early indicator of product quality problems. Listening to what your customers say, lets organizations anticipate product and service issues but also understand customer interest, intent and engagement level.

The good news is that Voice of the Customer (VOC) data is more prevalent than ever. However, it comes in a growing number of forms and channels. The majority of VOC data is unstructured and text-based by nature, it is difficult to utilize in traditional analytics solutions, presenting challenges to effective VOC listening. Examples of unstructured VOC data include consumer posts within Social Media and user communities (blogs) and verbatim text note entries in Call Center, Technical Assistance Center, and Dealership Service system records.

The Oracle Data Cloud Voice of the Customer (VOC) Listening Platform provides state of the art capabilities to collect, standardize and categorize unstructured data, making it easy to recognize patterns, surface trends and uncover both positive and negative messages.

The solution processes data from a wide range VOC sources including customer conversations across major social networks, user forums and discussion boards, in addition to unstructured data from internal corporate sources such as customer call center record notes, dealer hot line notes, customer surveys, warranty record notes, etc. After this data is standardized and categorized, it can then be easily integrated into downstream data repositories and data visualization and analytics tools.

Comments from a variety of VOC sources

Brakes grind when I step on pedal

Engine whine is driving me crazy

Engine clatters when cold

Brakes squeal like a pig

Social + Web(Forums, Surveys, etc.)

Call Center

Service & Warranty

Unstructured Voice of Customer Data

Oracle Data Cloud

Structured Data, Suitable for Analytics

Structured and Categorized Data

LATENTSEMANITCANALYSIS

NATURALLANGUAGE

PROCESSING

BOOLEAN

PURESIGNAL

• Structured and categorized data• Suitable for analytics

• Unstructured, text based data• Only limited use for analytics

Oracle Data Cloud standardizes and categorizes VOC data, making it suitable for analytics

Oracle Automotive Quality Analytics Solution 4

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How exactly are VOC comments standardized and classified in Oracle Data Cloud? First, a categorization hierarchy is created based on automotive functional areas (brakes, engine, etc.). Then, specific listening filters are created within Oracle Data Cloud for each functional category. Listening filters are easily created by business users (not IT programmers) through a simple application user interface.

Automotive functional classification hierarchy

Listening filters in Oracle Data Cloud

Steering

Performance

Noise

Chassis Body Powertrain Interior Accessories Service

Automobile

Brakes

Transmission

Performance

Noise

Engine

Dashboard

Seats

Unique “Listening” Per Node*Keywords (Brake, Grind, Squeal, etc.)

Unique “Listening” Per Node*Keywords (Engine, Whine, Knock, etc.)

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Once VOC comments are filtered through Oracle Data Cloud, they are placed into the correct automotive functional category, providing analytics relevance and the ability to roll-up and highlight “trends” for comment

occurrences within the category.

II. Quality Issue Early Detection DashboardOnce VOC data is standardized and categorized, it now exists in a format suitable for analytics. The next challenge involves visualizing the VOC data in a dashboard that provides instant visibility to trending quality

problems. This is the role of the Quality Issue Early Detection Dashboard.

Steering

Performance

Noise

Chassis Body Powertrain Interior Accessories Service

Automobile

Brakes

Transmission

Performance

Noise

Engine

Dashboard

Seats

Unique “Listening” Per Node*Keywords (Brake, Grind, Squeal, etc.)

Unique “Listening” Per Node*Keywords (Engine, Whine, Knock, etc.)

Brakes grind when I step on pedal

Engine whine is driving me crazy

Engine clatters when cold

Brakes squeal like a pig

Oracle Data Cloud filters and categorizes VOC data into the appropriate functional category

Quality Issue Early Detection Dashboard provides instant visibility to trending quality issues

Oracle Automotive Quality Analytics Solution 6

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As noted in the figure on the previous page, the Early Detection Dashboard provides immediate visibility to data trends occurring within each category. For example, in the “Chassis” category, the “Comments Trend” has shown the most activity, increasing by 30%. Consequently, it is flagged in “Red”, indicating the need for further attention. Note that VOC comment details are provided, including Comment Trend Rate, Comment Sentiment, Comment Type (i.e. Brake Noise, Brake Performance) and trending message themes.

Users can then “drill-down” from first-level categories (i.e. Chassis) to lower categories to discover the exact origin of the quality problem. The figure below illustrates detailed VOC data within the “Brake” sub-category. In short, quality trends within each category are visible at a glance, providing the foundation for the early detection of quality issues.

III. Quality Issue Rapid Investigation PlatformOnce quality issues have been identified in the Quality Issue Early Detection Dashboard, further investigation is required to determine the extent and impact of the quality issue. The Oracle Automotive Quality Analytics Solution provides a Quality Issue Rapid Investigation Platform for exactly this purpose.

Leveraging this Rapid Investigation Platform, users can investigate the details surrounding specific quality issues including: vehicles impacted (year/make/model); VIN numbers impacted; regions of country impacted; vehicle options impacted; parts impacted; suppliers impacted; seasonality effects; or analysis by any other data attribute included within the data collection.

The Quality Issue Rapid Investigation Platform provides detailed analyses of quality issues

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Copyright © 2015, Oracle Corporation and/or its affiliates. All rights reserved. Last Modified: August 10, 2015 3:18 PM

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Solution Benefits

The Oracle Automotive Quality Analytics Solution provides value to the following organizational stakeholders:

• Directors of Quality and Customer Service can combine, categorize and analyze widely ranging VOC data to identify emerging quality problems, before they evolve into costly warranty or recall issues. Dramatic improvements in quality issue detection times can be achieved – what previously required up to 6 weeks to detect, can now be achieved within 1 day. Assuming a 6 week reduction in quality issue detection time, a $200 cost per warranty fix and 10,000 vehicles produced per month, this can equate to tens of millions of dollars in warranty cost savings.

In addition, the solution provides the ability to track consumer sentiment for both the product and service experiences associated with a brand, providing the foundation for sentiment tracking and improving overall brand equity.

• Directors of Product Development can continuously listen, via social listening, to comments regarding their vehicle brand or models. By understanding customer needs, likes and dislikes, vehicles, systems and features can be tailored to customer needs. This can be executed at the overall vehicle level, or at a specific vehicle functional area level, forming the basis for both competitive analysis and continuous design improvement.

Oracle Automotive Quality Analytics Solution Reference Architecture

Oracle provides all back-end hardware, software, analytics applications and data to enable a complete solution for early detection of quality issues in the automotive industry.

Oracle Automotive Quality Analytics Solution Reference Architecture

Service Information

Call Center Information

Warranty Information

Social + Web• Social• User Forums• Blogs

From Unstructuredto Categorized Data

Early Detection ofQuality Problems

Investigate IndividualQuality Issues

Voice of the Customer Data

Voice of the Customer

Listening Platform

Quality IssueEarly Detection

Dashboard

Quality IssueInvestigation

Platform

External Data

Internal Data

• By Vehicle Make/Model/Year• By Vehicle Functional Area• By Number of Occurrences• ByTrending• Etc.

VOCDATA