Patent ID: 8170894

Claim:
A method of detecting disruptive business process innovations comprising the steps of: performing an initialization phase comprising the steps of gathering a quantity of time series data, wherein said step of gathering said quantity of time series data time series data comprises the steps of: gathering a quantity of expected research and development time series data; gathering a quantity of reference research and development time series data; gathering a quantity of expected revenue time series data; gathering a quantity of reference revenue and development time series data; gathering a quantity of expected operations expense time series data; gathering a quantity of reference operations expense time series data; gathering a quantity of expected time cycle time series data; gathering a quantity of reference time cycle time series data; performing a processing phase using a computing machine comprising the steps of: creating at least one set of time series data; performing dynamic nonlinear analysis using said at least one set of time series data; applying a learning method to analyze said time series data; performing an output phase comprising the steps of: creating a disruptive innovation output analysis portfolio; and performing an option to perform said processing phase and said output phase again with different situational attributes; wherein said initialization phase further comprises the step of storing said time series data and, wherein said step of performing dynamic nonlinear analysis using said at least one set of time series data further comprises the steps of: deriving a Lyapunov exponent from said at least one set of time series data; deriving the presence of a strange attractor from said Lyapunov exponent and from said at least one set of time series data; deriving a Hurst exponent from said at least one set of time series data; deriving the correlation dimension from said Hurst exponent and from said at least one set of time series data; creating a graphic from said time series data; and wherein said step of creating sets of time series data comprises the steps of: performing data integrity checks on said at least one set of time series data, wherein said step of performing data integrity checks comprises the steps of: identifying data problems; and remedying said data problems.