AHG Expands its Deep Analysis Capabilities through Data Extraction, Transformation and Visualisation

Forest Grove23rd March 2022

Automotive Holdings Group (AHG) is a diversified automotive retailing and logistics group headquartered in Perth, Western Australia. As Australia’s largest motor dealership group, AHG owns over 180 car and truck franchises and offers a wide range of services including finance, aftercare, insurance and equipment.

Problem

AHG’s National Trucks Division regularly undertakes analysis to identify opportunities to transfer spare parts between dealerships in order to minimise the write-downs that occur when parts age without being utilised. Historically the analysis was completed on a monthly basis via an inefficient, cumbersome and manual two-week process that originated with CSV extracts.

Solution

Forest Grove developed an end-to-end automated data wrangling and reporting engine to expand AHG’s capabilities in deep analysis through the process of data extraction, transformation, reporting and visualisation. 

The solution is scalable, flexible and transparent and can be easily updated to suit changes to the data environment and user requirements. The solution comprises five components:

  1. Automation of data aggregation from the dealer management system
  2. Cleansing, blending and transformation of raw data
  3. Storage of raw data in a cloud data warehouse
  4. Creation and update of warehouse tables for reports
  5. Presentation of data in interactive and scheduled dashboards

 

High level KNIME workflow

AHG’s high-level KNIME workflow

 

Results

Forest Grove’s solution has vastly expanded AHG’s deep analysis capabilities and represents a major milestone in its journey from descriptive to prescriptive analytics.

By automating the data interpretation process with KNIME, managers are now able to identify potential transfer opportunities in minutes rather than weeks. 

Key Benefits:

 

  1.  Single data repository for all reports
  2. Semantic layer for intuitive data interpretation
  3. Scheduled data extraction and aggregation process with detailed governance (validation) checks
  4. Significantly reduced time to insight with an infrastructure solution that supports deeper analytical dives
AHG's detailed KNIME workflow example

AHG’s detailed KNIME workflow example


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