The client was a $50B telecommunications company in the Southeastern United States.

The client had significant challenges in tracking and planning necessary materials to complete projects, consistently battling inventory levels, and steep financial penalties as a result of their inability to efficiently execute customer work.


Sparkhound worked with client leadership to significantly improve their forecasting processes:

  • Implemented an integrated demand forecasting solution using advance Artificial Intelligence and Machine Learning models

  • Stood up health metric reports for the newly created forecasting model

  • Developed a custom app to enable just-in-time inventory and distribution, answering the question, “Do we have enough materials and people to get the work done?”

  • Enabled an error tracker for materials demand, preventing misallocation of resources


  • Prescriptive forecasting model that improved service to customers

  • Significant cost savings through excess inventory reduction and optimized labor demand

  • Improved fulfillment of service level agreements