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…
Categories: Final report, Finance, Forecasting, Houston, Marketing, Optimization, Planning, Presentation, Scheduling, Simulation, Texas, United States, Video Tags:
Client: Lennox Industries
Team: Diana Batten, Maddie Kamp
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
Lennox Industries is a residential and commercial heating and air-conditioning company with a 13-15% market share in about 80 countries. Lennox is unique in that they operate as both the manufacturer and distributor of their products selling directly to their customers, typically contractors.
This project identified correlations between customers’ buying patterns and their attrition, or loss of their business. Based on transaction-level data of 4,500 customers over a three-year period, an early-warning model was developed to signal the potential loss of a customer and enable Lennox to act preemptively. The analytics were based on a ranking procedure based on key indicators and a Markov chain analysis with categorical transition probabilities derived from historical data. With this model encapsulated in spreadsheet form with the ability to customize the analysis geographically and seasonally, the results give Lennox management a new tool to maintain their current customers and evaluate new markets.
Client: Arlington Texas Police Department
Team: Ron Andrews, Blake Robinson
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
The Arlington Police Department is responsible for policing the city of Arlington to achieve a safer community. The policing of the city is divided roughly into four main areas (north, south, east, and west) with each respective area possessing its own police station. The Arlington Police Department requested insight into the placement of the police stations to see if they were effectively located to process the level one crimes that originate from each main area. If a main area was not adequately covered, areas could be hypothetically redrawn to accommodate effective policing.
Our method of analysis included the use of in-depth data analysis and a pure network model that had the potential to take into consideration Euclidean distances, time schedules, crime severity and political issues. Our findings indicated that the placement of police stations given current population levels were placed reasonably close to where our model suggested they should be placed. It was also discovered that complex issues such as political issues and crime severity are hard to quantify within a model given due to the ambiguous nature of the data.