SMC-IT cost risk tutorial part 1 : incorporating risk
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Engineering topics
Publications and source records attributed to Hihn, Jairus.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
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A new approach to change management has been developed and applied at the Jet Propulsion Laboratory (JPL). It's main focus is on aligning the organization with the strategic plan; and understanding the internal organizational relationships that impact change, which ultimately determine an organizations ability to be transformed and renewed The new approach regards the strategic plan of a company as the standard by which progress and achievement are measured. Purposeful interventions should generate a company movement along a strategic course, and tracking that movement is essential for managing change. This paper presents an overview of DYNOMO, or the DYNamic Organizational MOdel which was developed to assist in the measurement and analysis of organizational state. The paper concludes with summaries of two applications.
This paper presents an overview of a parametric cost model that has been built at JPL to estimate costs of future, deep space, robotic science missions. Due to the recent dramatic changes in JPL business practices brought about by an internal reengineering effort known as develop new products (DNP), high-level historic cost data is no longer considered analogous to future missions. Therefore, the historic data is of little value in forecasting costs for projects developed using the DNP process. This has lead to the development of an approach for obtaining expert opinion and also for combining actual data with expert opinion to provide a cost database for future missions. In addition, the DNP cost model has a maximum of objective cost drivers which reduces the likelihood of model input error. Version 2 is now under development which expands the model capabilities, links it more tightly with key design technical parameters, and is grounded in more rigorous statistical techniques. The challenges faced in building this model will be discussed, as well as it's background, development approach, status, validation, and future plans.