Production and distribution supply chain optimization software

A system comprising:

• a computer;
• input and output devices in communication with said computer;
• and
• a memory encoded with a computer program, which, when executed by said computer, causes said computer to perform the following:
• allow a user to identify activities that comprise a process, wherein the process is a series of activities, wherein an input of at least one subsequent activity is dependent on an output of at least one previous activity,
• further allow said user to identify measurable drivers associated with a at least one metric, reflecting an efficiency of said process, for each of the activities;
• identify bridge variables from said identified drivers, wherein each bridge variable is a driver that is relevant to more than one of said activities;
• establish a relationship between various drivers by representing at least one non-bridge variable driver in terms of one or more said bridge variables;
• using said relationship, represent activities at least as a function of one or more of said bridge variables, thereby reflecting interdependence between said activities to represent the entire series of activities of said process;
• generate a model of said process at least as a function of said bridge variables by combining representations of activities comprising said process;
• and output, from said model, a predictive metric reflecting an efficiency of the total process.

A computer-readable data storage medium containing program instructions, which, when executed by a processor, cause said processor to perform the following:

• allow a user to identify activities that comprise a process, wherein the process is a series of activities, wherein an input of at least one subsequent activity is dependent on an output of at least one previous activity;
• further allow said user to identify drivers associated with a metric reflecting an efficiency of said process for each of the activities;
• identify bridge variables from said identified drivers, wherein each bridge variable is a driver that is relevant to more than one of said activities;
• establish a relationship between various drivers by representing at least one non-bridge variable driver in terms of one or more of said bridge variables;
• using said relationship, represent activities at least as a function of one or more of said bridge variables, thereby reflecting interdependence between said activities to represent the entire series of activities of said process;
• generate a model of said process at least as a function of said bridge variables by combining representations of activities comprising said process;
• and
• output, from said model, a predictive metric reflecting on efficiency of the total process.

A computer-implemented method of managing a process, said computer implemented method comprising:

• identifying activities that comprise the process, wherein the process is a series of activities, wherein an input of at least one subsequent activity is dependent on an output of at least one previous activity;
• identifying drivers associated with at least one metric, reflecting an efficiency of said process, for each of the activities, wherein identifying said drivers includes identifying at least one of fixed components and variable components of each said driver;
• determining, in a computer, a metric for each said driver based on said at least one of fixed components and variable components thereof;
• generating, in a computer, a model of said process at least as a function of said drivers by combining representations of activities comprising said process;
• and
• outputting, from said model in a computer, a predictive metric reflecting an efficiency of the total process.