Qlik > Case Studies > Mercedes-Benz saves 25 man-days annually on QA refreshes

Mercedes-Benz saves 25 man-days annually on QA refreshes

Customer Company Size

Large Corporate

Region

America

Country

United States

Product

Gold Client Solutions software
Data Echo
Data Recast
Data Wave

Tech Stack

SAP
ERP
CRM
GTS
SRM Business Suite on HANA

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Productivity Improvements
Cost Savings

Technology Category

Functional Applications - Enterprise Resource Planning Systems (ERP)
Functional Applications - Enterprise Asset Management Systems (EAM)

Applicable Industries

Automotive

Applicable Functions

Discrete Manufacturing
Quality Assurance

Use Cases

Predictive Maintenance
Manufacturing System Automation

Services

System Integration
Training

About The Customer

Mercedes-Benz USA (MBUSA), headquartered in Montvale, New Jersey, is responsible for the distribution, marketing and customer service for all MercedesBenz and Maybach products in the United States. MBUSA offers drivers the most diverse line-up in the luxury segment with 12 model lines ranging from the sporty C-Class to the flagship S-Class sedans and the SLS AMG supercar. MBUSA is also responsible for the distribution, marketing and customer service of Mercedes-Benz Sprinter Vans in the US. More information on MBUSA and its products can be found at www.mbusa.com and www. mbsprinterusa.com.

The Challenge

Mercedes-Benz USA implemented SAP Finance and Controlling in 2000, followed by Parts Logistics, Materials Management, Sales and Distribution, and Production Planning in recent years. With five business units running on two instances of SAP, the environment has become progressively more complex. The total SAP system now houses two terabytes of data, with pricing tables alone adding up to 400 million records. The primary issue caused by the refreshes was that they took the non-production systems offline for several workdays in the middle of the week, which would negatively affect ongoing projects. Mercedes-Benz wanted to be able to provide developers with the data they needed for testing on an as-needed basis while reducing the number of full refreshes required per year. The company also wanted to be able to protect version information.

The Solution

After thoroughly investigating its options, Mercedes-Benz determined Attunity Gold Client Solutions would best fit their needs, allowing data selection on virtually any parameters developers needed between full refreshes. It would also allow the company to keep costs down by utilizing existing infrastructure rather than purchasing new servers. Another determining factor was the software’s ability to maintain number sequences for entries such as sales data. Implementation took roughly one week, including training BASIS team members on using the tool in day-to-day scenarios. The Client Construct part of Attunity Gold Client Solutions allows the company to refresh full master data in QA, while Data Echo provides the ability to select more targeted data for specific purposes.

Operational Impact

Gold Client Solutions software has significantly cut the time to deliver the data required by some groups. In fact, these groups can pull master data in less than an hour using Gold Client’s Data Snap feature.
Faster problem resolution is realized as the developers can now copy the erroneous transactional data from the production system to the DEV or QA environment. The application fix can now be tested on exactly the same data that caused the error in Production. If needed, this transactional data can also be quickly reloaded in DEV or QA as the fix is further refined and tested.
Gold Client has improved the efficiency and overall time of QA refreshes. The tool saves time for developers and functional users by letting them preserve custom testing data out of QA prior to a refresh. Those groups are now able to store custom tables before refreshes, and then restore them afterward. Before, the BASIS team had to rebuild those custom tables manually.

Quantitative Benefit

Reduced time from three days to two days on refreshes
Reduced the number of resources working on QA refreshes from four down to two
Saved six to seven man-days worth of time on each refresh—four times a year—which adds up to 25 days a year