How do we define “revenue science” and how does it go beyond typical revenue management practices and revenue optimization strategies to deliver next-level profitability and productivity?

The year is 1989. IDeaS’ data-science founders are busy at work testing and proving new theories of opportunity cost and quantitative data analysis. They’re boiling algorithms and complex equations down to simplified decision outputs and pioneering what would become the founding principles of IDeaS’ Revenue Science: the discipline of infusing sophisticated mathematics with industry expertise to transform data into accurate, automated, and actionable revenue-enhancing decisions.