Problem Statement
“Where do I get the most bang for the buck?”
This is a question asked all-to-often by government and business leaders alike. For this client, the challenge laid in determining the “should-cost” value for the quantity, type, and length of military operations.
This challenge was compounded by the prevalence of data quality issues stemming from unstructured financial reporting practices.
Tool Specification
ROME utilizes a custom machine-learning algorithm rooted in linear/non-linear regression applications to forecast probable budget requirements to facilitate a specified set of military deployments. It allows users to optimize resource allocation using real-time financial, risk, and organizational priority data from any data source.
Deployment and Value Statement
ROME was deployed to provide budgeting & financial planners sufficient insight and justification for budget requests to facilitate out-year financial planning.
Further, ROME enables the end user to execute various optimization operations to determine the most valuable operational-tempo given budgetary constraints and overall organizational goals.
