Capacity management index system and method

A computer implemented method that derives an algorithm for a Capacity Management Index (CMI) that is used in an enterprise strategy process for managing capacity, comprising the steps of:

• defining Capacity Management Index (K) as a sum of all Service Indices (SS), weighted according to a predetermined significance of their individual contributions;
• defining a Service Index (SS) as a sum of all Component Indices (CC) for that Service, weighted according to a relative importance of their individual contributions;
• defining a Component Index (CC) for a given component as a ratio of a demand (DC) for that Component to a capacity (kC) of that Component;
• interpreting, by at least one computing device, the Component Index (CC) as follows:
• CC<1 Capacity exceeds Demand;
• CC=1 Capacity equals Demand;
• and
• CC>1 Demand exceeds Capacity;
• inserting, by the at least one computing device, the definition of the Component Index (CC) into the definition for the Service Index (SS) and inserting the definition of the Service Index (SS) into the definition for the CMI (K) and obtaining a CMI (K) that represents an aggregate index over all Lines of Business (L);
• incorporating, by the at least one computing device, additional Demand considerations by recognizing them as demands of a Technology Infrastructure Group (TIG);
• incorporating, by the at least one computing device, demand forecasting upon the Lines of Business;
• wherein if using measured data, then K represents an Actual CMI;
• wherein if using forecast data, then K represents any of an Historical or a Future forecast CMI, respectively depending on a predetermined time interval;
• including, by the at least one computing device, a confidence factor (F) that is based upon an observed deviance of historical forecast values from values that are actual and measured;
• adjusting, by the at least one computing device, the confidence factor (F) by a time-based factor (T);
• including, by the at least one computing device, external factors by establishing a correlation between external factor and internal business metric, by establishing a correlation between internal business metric and service metric, and by using derivations to define a relationship between external factors and service demand;
• combining, by the at least one computing device, a set of internal Future forecasts (KFuture) with a set of External Indicators (KEe), weighted such that a given forecasts contribution to a Combined forecast (Kcombined) is proportional to a relative strength of its correlation to the Actual CMI (KActual);
• and
• adding, by the at least one computing device, Overhead demand (DO) and Buffer demand (DB) for each component to form a resultant K;
• responsive to adding Overhead demand and Buffer demand, using said resultant K in an enterprise strategy process for managing capacity.