Data Analytics And IIoT Solutions

Technical Capacity and Efficiency


Tracking multiple engineering programs and deliverables across R&D extremely difficult and time-consuming

Resource utilization and cost control difficult to achieve due to multiple influences and competing priorities

Limited ability to provide reliable forecasts for delivery of technical scope


Combined multiple, disparate data sources into a clear, cohesive dashboard used by multiple parties across programs, Lines of Business

Developed predictive analytics to forecast program completion based on real-time technical performance


  • Achieved 30% R&D organizational efficiency as defined by spend by end of year
  • Projected target of $5M+ in savings and improvement realized even before full production rollout
  • Expanded deployment across enterprise

Operational Efficiency


Customer did not have process to understand team dynamics in the assembly line

Limited analysis of data to drive corrective action

Wait/waste time not captured

Inability to understand optionality and product mix impact on performance or line design


Implemented Operational & Effectiveness (OEE) system

Tie directly into existing shop floor control systems and equipment controls to provide real-time status of production across company

Leverage data collection and visibility to show how line is performing


  • Increased analyst efficiency from 60% to 80% by removing bottlenecks
  • Reduced throughput from days to one hour in wing machining cell
  • 3% reduction in facilities and equipment support labor costs
  • 5% reduction in overtime costs

Business Analytics


Time consuming data investigation
Manual forecasting process
Inability to direction compare expected vs. current performance
Data stored in numerous separate company systems - accounting and production information not directly connected



Reorganizing Data Models
Development of analytics to compare expected and current performance
Merging data from spreadsheets and management software
Automated updating of models to minimize staff intervention 


  • Automated data capture and integration of disparate data reduced time and resources to manage business performance
  • Analytics enabled Customer to gain insights quickly and define actions where needed