1. A data processing system comprising: one or more system resources that are accessible to processes executing within multiple logical partitions, wherein the one or more system resources comprise at least one processor; a partitioning firmware that enables sharing of the one or more system resources across multiple logical partitions, each logical partition having a separate instance of an operating system, wherein said partitioning firmware further allocates specific entitlements of system resources to processes executing within each of the multiple logical partitions; and a processor executable utility that executes on a processor of the data processing system to cause the processor to perform the functions of: sampling one or more statistical data associated with performance characteristics of the logical partitions; analyzing said statistical data against pre-established scheduling criteria by: evaluating a measured change in cycles per instruction (CPI) over time; comparing said measured change to a pre-set threshold value of change; and calculating start up costs for the partition based on a time required for the measured change of the CPI to transition to a value equal to or below the pre-set threshold value; wherein a first measured change indicates the partition is still establishing a footprint and a second measure change indicates the partition is operating at steady state and completing actual work; and periodically sampling the CPI of the partition to determine whether a next measured change in the CPI indicates a re-establishing of the footprint of the partition; dynamically determining a most efficient scheduling of the multiple logical partitions and an allocation of the system resources to the multiple logical partitions based on a result of said analyzing of the statistical data; and making dispatch decisions and tuning (a) the scheduling of the multiple logical partitions and (b) the allocation of the system resources to the multiple logical partitions utilizing a result of the determining of a most efficient scheduling based on analyzing the statistical data.