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That Time Data Integration Software Helped Turn Around the Sears Auto Center Business
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Automotive
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Predictive Maintenance
Services
- Data Science Services
The Challenge
In 2014, Sears Auto Center was facing declining sales and margins. The company had useful operations data, but it was inconsistent, difficult to analyze, and open to misinterpretation. The operations performance, particularly at the regional retail level, was difficult to analyze. Different management layers had different reports, and even shared data was open to misinterpretation. In a competitive business environment, static monthly reporting was not dynamic enough to enable Sears Auto Center to respond to in-market regional trends. When a location’s business was struggling, it was tough to fix things when you couldn’t agree on what the data tells you.
About The Customer
Sears Auto Center is the automotive service division of Sears, a still-dominant retail giant with extensive North American retail and service reach. The Auto Center operates some 650 service centers around the United States, offering services such as oil changes, taillight fixes, tire rotations, and battery replacements. In 2014, the division was facing declining sales and margins. The president of the Sears Auto Center division, Brian Kaner, had to confront these sobering realities and find a way to turn the business around.
The Solution
To address the challenges, Brian Kaner teamed up with Joe Richards, who had come over from the Stanley/Black & Decker organization. Their initial objective was to establish a “single source of truth” for Sears Auto Center through data integration software, in this case, Domo. Over the course of a few months, and working with Domo consultants, they prototyped and then deployed a data-integration solution that pulled from existing systems, including HR, POS, financial, and online. The Domo deployment highlighted operational bottlenecks, limitations, and gaps they had suspected but until then had not been able to address with any certainty. They looked at cycle times, employee productivity, even retail product mix data.
Operational Impact
Quantitative Benefit
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