Case Study: Human Capital and Manpower

Government Agency (Name Withheld)

Background


 Changes in the Agency’s budget during the last ten years have shifted priority to strengthening the acquisition workforce. In order to better manage contracts, the government Agency increased funding for personnel. In order to assure that resources are optimally allocated throughout the agency, the Agency required support to build a manpower model to determine Human Capital requirements. This model would need to be driven by predictable workload factors and support universal application across multiple Contract Management Offices (CMOs). Model results would need to be grounded in proven statistical analysis and based on sound algorithms. The objective of the Agency was to produce a model that would inform approximately 70-80% of requirements determination elements with the remaining elements driven by Agency priorities, policies, and other tools. 


Approach


Because many CMOs administrate contracts that are unique, ITG recommended a multi-phased approach to developing the enterprise-wide CMO model. The recommended approach would incrementally develop and refine work breakdown structures differentiating between core processes common to all CMOs and those driven by actions performed in support of specific contract, contractors, customer, or product types. During Phase 1, ITG completed a proof of concept, developing a baseline measurement of one Contract Management Office (CMO). During Phase 2, we completed baseline measurement of ten CMOs from each of the four CMO types. We developed a comprehensive measurement document and input-output analysis, conducted measurement workshops, and used J-Accomplish™ to conduct correlation and regression analysis and build predictive manpower models. All measurement was conducted in a virtual environment to eliminate travel expenditures and minimize the impact on the organization under study. 



Results

The models were built using aggregated processes representing functions with the highest levels of resource consumption and are currently being used as a tool to determine resourcing requirements. The model has been selected to replace the Agency’s previous methodology which used a team of personnel traveling to each location to conduct data collection using interview techniques. The cost to maintain the old process, in both man-hours and travel, was high, not very timely, and not scientifically rigorous enough to withstand resourcing challenges from the Agency.  

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