Marcus Schwill and Friedhelm Inama von Sternegg, Daimler AG
Daimler Drives High Performance
Improved analytics enables the automaker to advance quality assurance and profitability.
Synonymous with high-performance automobiles, Daimler AG continues to set new standards. In 2011, the German automaker is taking a significant leap in improving its ability to analyze high volumes of warranty and diagnostic data, as well as diverse vehicle configurations, models and variations, all with the goal to continuously improve quality and, ultimately, customer satisfaction.
At the heart of Daimler’s business is quality assurance—and guaranteeing complete customer satisfaction is evident in everything the organization does. “Some of the main areas where Daimler collects quality assurance data are from the vehicles, garage service and related operations,” explains Winfried Günther, manager of After-Sales Quality Analysis. “And what we relied upon most were two sets of data stored in separate data marts: warranty and billing information and diagnostic data downloaded from on-board vehicle systems, and performance data gathered during service checks.”
Over a three-year period, the automaker (with the support of Teradata Professional Services) moved from an older data platform to a new, high-performing enterprise data warehouse (EDW) to enable timely, ongoing quality assurance.
Out With the Old
Dating to the 1990s, Daimler’s warranty data had been housed on its Quality Information System (QUIS), a mainframe-based platform. In addition to performing analysis on QUIS, users from many departments drew data from it with a variety of tools. The enormous demand for information combined with the use of different analytics tools created inconsistent data. “It was clear that we needed to consolidate at the database level,” Günther says. “Additionally, our users weren’t pleased with the then-current analytical tools and wanted a new front-end tool.”
At the same time, because the diagnostic and warranty data were siloed, they could not be evaluated collectively, hampering the organization’s ability to take full advantage of its data. Since the diagnosis platform had reached the limits of its capacity, combining the two systems as part of a data warehouse consolidation was the obvious solution.
In With the New
In mid-2007, Daimler decided to consolidate its quality-related data on a Teradata Active Enterprise Data Warehouse, making this data available to users through a shared interface. The new system was dubbed Advanced Quality Analysis (AQUA).
“We wanted AQUA to provide support for two strategic goals: first, to increase customer satisfaction, and second, to reduce costs,” Günther notes. By creating a “single point of truth”—a global, standardized perspective on all vehicle-related data—the new Teradata system could help Daimler better analyze both product and diagnostic effectiveness, as well as ensure the quality of repair and maintenance.
Additionally, sophisticated real-time analyses on AQUA will improve and extend existing early-warning systems. Finally, eliminating legacy systems is projected to reduce IT operating costs.
“Our performance has doubled compared to the old system and we’re now five times faster than we were in the summer [of 2010].”
After selecting the EDW and a MicroStrategy interface for AQUA, the business intelligence (BI) team sought a quick win to showcase AQUA’s benefits. In a yearlong project, Daimler’s diagnostics data was migrated to the EDW, and the older system was switched off. At the same time, the team began to incorporate other source systems into the EDW.
Since early 2010, users have been receiving warranty and goodwill reports via AQUA, and the data has created an opportunity to implement an enhanced early-warning system. Overall, Daimler has seen significant performance improvements.
“Our performance has doubled compared to the old system and we’re now five times faster than we were in the summer [of 2010],” Günther says. In addition, the warranty and goodwill data have provided a basis for implementing the enhanced early-warning system and the “First Fixed Visit” tool, which identifies recurring repairs based on data collected on vehicles in dealership service stations.
Since implementing AQUA, Daimler has effectively managed its extreme data growth, particularly from its garages worldwide. “The Teradata system allowed us to catch up,” Günther says. “We’re no longer running logs on the weekends.” But that’s not all:
After integrating its data-mining tool into AQUA, Daimler no longer needs to copy data. This translates into much speedier searches and reduced follow-on costs. “The faster we can eliminate a problem in production, the easier it is to avoid future warranty and goodwill costs,” says Friedhelm Inama von Sternegg, head of IT at the Center of Competence for Service Marketing and responsible for the AQUA project. “In view of the quantity of units we produce, not to mention our manufacturing costs, this amounts to a considerable savings.”
The AQUA Miner provides a step-by-step approach to identify the individual features that contribute to a higher rate of part defects. To do this, the engineer chooses a specific series type, failure codes or special options suspected of contributing to a particular defect. Interactive decision trees in the AQUA Miner then identify subgroups where such defects appear more frequently than in the remainder of the vehicle fleet.
Eventually, AQUA Miner will access not only warranty and goodwill data but also vehicle electronic control unit records. And in addition to diagnostic data, load collectives such as revolutions per minute, vibration behavior or temperature can be analyzed. This will help uncover the causes of defects based on actual driving experience and influence the design of future vehicle models.
“For the first time we have a data source that provides all quality-related information across a complete range of components and model lines,” says Steffen Kempe, Research and Technology GR/ PRQ Quality Analysis. With this data, developers and engineers can create thousands of user-configurable calculations of the repair frequency of all components and can be automatically informed of any significant deviations. Since AQUA is updated with current data at shorter intervals—sometimes even daily—these warnings can be received up to two weeks earlier than before.
“The faster we can eliminate a problem in production, the easier it is to avoid future warranty and goodwill costs.”
—Friedhelm Inama von Sternegg,
As a result, Daimler can pinpoint potential problems in vehicles that have been on the road for only a month and can correct its production processes accordingly. This has had a positive effect on reducing long-term warranty costs. “The system also increases analysis efficiency so that our engineers have more time to deal with error analysis and can eliminate many more problem areas,” Günther says.
Compared with the old system, AQUA provides approximately five times the storage space for diagnostic data from both cars and trucks. Daimler now has a comprehensive and detailed view of all vehicles. “Today, we are in a position to both gather and control these enormous amounts of data. With the old system, this was just not possible,” notes Ralf Keefer, manager diagnosis doors, Feedback System.
With the early-warning system, alerts can be received about a model series or even individual vehicles that have been on the roads for only a few weeks. “Being able to bring this information together to find patterns and failures before something happens is a major change that we can take advantage of in the Teradata data warehouse,” says Stefan Kralisch, Manager AQUA Warranty and Goodwill.
Down the Road
Because Daimler only recently completed the AQUA transition, it’s too soon to fully gauge all of the analytical and business benefits of the consolidated platform.
Looking forward, the automaker continues to acclimate its users to the Teradata system. “We want to incorporate the new warranty, diagnostic, early warning, quality—and other data resources—to tailor Daimler’s offerings more accurately to respond to customers’ needs,” adds Günther. “As a result, we’ll be able to develop new competitive advantages throughout the company, all based on Daimler’s ongoing quest for quality leadership.”
With the new system, Daimler has opened up the high performance of its data and allowed the automaker to achieve deeper insights into how to optimize production. Defects can be more quickly detected, resolved and considered in terms of further development.
Coming to the end of this phase of implementation, Daimler has found that AQUA supports its strategic goals of quality leadership, customer satisfaction and profitability—all the while allowing Daimler to lay the foundations for future analytics projects.
“We have achieved precisely what we set out to achieve,” says Marcus Schwill, senior manager, Global Service and Parts.