Improved forecasting and predictive modeling saves 1,500 labor hours per year at $31B Aerospace and Defense company

Business Challenges

  • Time Consuming Process – The organization’s cash management process required data sourcing from various offline source systems
  • Manually Intensive – Complex web of disconnected offline spreadsheets and calculations that required manual processes to check for forecasting accuracy
  • No Insight into Key Drivers – Despite spending a great deal of time in data gathering and analysis, the forecasting process lacked key information from unstructured data sources such as contracts, making it difficult to track key drivers of performance


  • Established Streamlined Processes – Created mechanisms to extract data from unstructured data sources and remove the need for time consuming data entry
  • Centralized Data Repository and Forecasting Model – Replaced various spreadsheet models with a centralized data system, increasing information visibility and allowing more time to conduct value-added activities
  • Predictive Modeling – Built predictive models leveraging unstructured data to improve the ability to derive impactful insights


  • Estimated Time Savings of 1,500 Labor Hours Per Year – Streamlined and created processes that greatly reduced the need to manually input data
  • Greater Visibility into Forecasts – Newfound ability to plan and forecast cash at varying time horizons as well as the capacity to incorporate more granular level data to improve visibility across functions
  • Improved Scenario Planning – Enhanced scenario planning capabilities through a new driver-based model

Complimentary Discovery Briefing

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