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Financial Product Mix for Capstone Asset Management

October 31st, 2011 No comments

Client: Capstone Asset Management Co.
Team: Mallory Harrison, Natalie Jaroski
Faculty advisor: Dr. Barr   Year: 2010
Documents: Final report (PDF), Presentation (PDF)

Capstone is a privately owned investment advisory firm in Houston, TX that offers privately managed accounts to achieve client’s financial objectives. They currently manage over $3.8 billion in assets for about 3,000 different clients. They provide products and services through three distribution channels: brokers/advisors, institutions/corporations, and high-net-worth individuals. Revenues are generated by marginal product fees associated with assets under management allocated by product.

Capstone has in place a detailed budgeting process but desires to expand the process to include financial modeling to measure profitability by product. Our goal for this project is to develop a model that would calculate existing profitability on assets under management by product. Our second goal is to develop an optimization model that takes into account the revenues and expenses associated with sales of existing products versus the revenues and expenses associated with the development of new products. The final output of the optimization model is to identify the most profitable mix for new product sales. Read more…

NASA Production Center Process Improvements

June 5th, 2009 No comments

Client: National Aeronautics and Space  Administration
Team:  Chris Genda, Loan Ngoyen, Valerie Vlahos, John Williams
Faculty advisor: Dr. Richard Barr     Year: 1997
Documents:    Final presentation

The present operations procedures used by the NASA Manufacturing Di­vision has room for improvement in the following areas: information accuracy within the INFISY system and tracking machine downtime, departmental com­munication, job scheduling at each work center, and estimating job cost and completion time. Due to the combined errors and problems mentioned within the Division, several effects are obvious.

The inaccurate use of the INFISY system has led to an incomplete historical data set, which has greatly affected the forecasting of completion times of jobs. This is apparent in the very large negative variances (actual-estimated time). The high percentages of those not logged out on INFISY have led to part mislocation. Job scheduling is diffi­cult without tracking intermediate completion dates. Not monitoring machine down time leads to possible higher repair costs than sometimes purchasing a new machine. Under the current use and application of the INFISY software, job scheduling and forecasting are not optimized as needed. Addressing these issues gradually will improve the production operation. Read more…