Geo-Analytics and Network Build Out Automatic Reporting

Geo-Analytics and Network Build Out Automatic Reporting

Prior Situation / Scenario:

  • Distribution Point (DP) mapping file was manually updated and categorized each month
  • HFC polygons were incorrectly georeferenced and not aligned with local parcels
  • Manual process for files sent to BI team by email, then loaded into database for reporting

Client Challenges:

  • Long time to process a monthly report.
  • Replace time-consuming manual process, prone to error
  • Inaccurate geo-referencing of customers and network polygons
  • BI team reliant on availability of Network team for updates

Strata Solution/ Key Enablers:

  • Developed algorithm to identify parcels to correctly align network nodes with HFC polygons and map to customers
  • Script written to get billing system data and applied to final reporting, used data from GIS to classify DP layers, and data entered into database for reporting purposes
  • Technologies used: ArcGIS, Python, AWS ,Tableau for Dashboarding and Tibco SpotFire for Geo Mapping reports

Outcome:

  • Customers were geo-referenced, allowing geo-targeting sales campaigns
  • Over 90% of HFC polygons were corrected
  • 89% of DP’s were automatically classified (will increase as data quality improves)
  • Report is updated automatically on a weekly basis

Results:

Increased accuracy on network expansion plans, better ROI on network investment where there is a clear, unmet demand and substantial increase on sales effectiveness by geo-referenced marketing efforts.