A multi brand authorized warranty provider and service center increased revenue and saved time with new dynamic business analytics solution

Information

Customer Name: Confidential
Industry:  Information Technology
Function: Service, Inventory
Geography: India
Data Source Systems Applications:  Homegrown software, MS-Excel, CSV Files
Business Intelligence Platform: QlikView

The Challenge

Each brand had their own software which provided limited visibility into the overall business
Any analysis for a particular brand involved pulling data from the software and analysing the same in a spreadsheet
Any analysis across brands required to change formats and manipulate data before analysing in spreadsheets. This gave rise to errors apart from taking a lot of manual effort and time.
Analytic reports were created monthly which caused quite a few cases to get escalated.

The Solution

Galaxy implemented a Business Intelligence Solution that ingested data on a daily basis from the software of each brand into a common data warehouse. This data warehouse was then used for dashboards and analytic reporting. The dashboards were very easy to read and red flagged any KPIs that were getting missed out. Some of the highlights are

Number of open cases across various dimensions like brand, model, geography, reason, technician
Age of oldest case across brand, model, geography
Number of closed cases in the period across brand, model, geography, technician, TAT (turn around time)
Number of Repeat cases across brand, model, geography, technician
Daily cases compared to Average number of cases per day across brand, model, geography, technician
Cases attended by Technician
Average revenue per case
Inventory of fastest & slowest moving Parts
Top Parts consumption over periods
Cases % to models in field across geography, age

The Benefits

Improved customer satisfaction because Immediate action was taken on cases that needed attention
Cost savings due to better inventory management
Improved location and technician efficiency by providing daily visibility into cases closed
Improved overall efficiency by dynamically moving technicians between brands because analytics revealed a seasonality in cases that was not noticed earlier
Models on fields vs cases analytics gave insights into future visibility of cases.

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