An IT Prime partner of ours sought out Xentity to support their Nationally renowned commercial client in solar energy. They wanted to leverage and explore how Geospatial data analysis can support many areas for optimization including sales  integration, facility, and fleet planning. 

Problem and Solution

The first challenge was to address fleet planning to optimize drive-times. This included looking at assignments of leads and orders to the best facilities. We established a new data flow and pipeline to a cloud-hosted data environment. Also, we connected to the ESRI ArcGIS Online environment. This enabled multiple apps and maps to support data scientists and analysts evaluate new service calculators to determine optimizations by regions, facilities, and zip codes.

The next challenge was to integrate additional layers which sales and marketing could consider for targeting optimal solar clients considering data in population, purchasing demographics, solar exposure, past and existing penetration with marketing campaigns and more. The analysts had conducted analysis by zip in spreadsheets, yet needed an overlap analysis capability to further explore by zip codes. By integrating geospatial data using ESRI and Open Source model workflows, the team was able to rapidly create this overlap providing the data back for geospatial visualization and traditional tabular analytics for the organization to further optimize targeting of specific zip codes.

Analysts were now able to leverage Geospatial Analytics to assist decisions in:

  • Drive Time decisions to assign new territories/zips for warehouses with known savings of times
  • Compare counts, revenue, drive time savings by changes
  • Optimize Max Time of Zips to any Warehouse
  • Include in Revenue, Costs, and Counts to garner total change impacts
  • Consider additional facets of counts and dollars by Projects, Leads, Opportunities
  • Consider warehouse integration/augmentation by location, space, and access
  • Balance revenue impacts by warehouse or zips
  • Explore understanding of Cost of Business to Revenue by Zip and Warehouse
  • Lead Optimization for cost of lead and Conversion Rates

Outcome and Benefit

The enterprise was able to leverage the new geospatial analysis for optimization of many areas. This included the consideration of closing/opening new facilities. Also, in re-assigning fleet orders, reduced fleet times, consider new fee models for extended routes. The analysts were able to present with confidence to business decision makers on topics. Topics such as warehouse consolidation, fleet order assignments with optimized drive times, and closing and opening zip codes for optimal marketing and sales purposes.