This Industry Capstone Program project is with the company Whitestone Associates and the corporate partner is Frank Gallucci. The faculty advisor is Professor Zachary Feinstein.

General Information:

Whitestone Associates is a boutique investment banking firm specializing in the buying and selling of industrial companies in the fluid power, motion control, and automation markets. 

The ability to analyze data is critical to Whitestone’s success. However, much of the analysis is currently done in an unsystematic way. To the best of our knowledge, there are few firms that use algorithms to determine if a company has a predisposition to sell to a qualified buyer. Whitestone has made a focused effort over the last two years to assemble a definitive database of enterprises that participate within Whitestone’s Market Sector.

Utilizing and supplementing Whitestone’s database, it is Whitestone’s strategic intent to develop predictive algorithms that will provide leading indicators of a company’s predisposition to entertain an acquisition offer. Our project will complement and supplement Whitestone’s interest in this project.

This project will focus on identifying structured and unstructured databases and scraping relevant data that will provide the M&A practitioner some insight as to whether a closely held enterprise would be predisposed to entertain an offer to acquire their company. Many other potential insights could be realized. However, we will start with identifying sellers in a narrow industrial market niche: the fluid power, motion control, and automation markets.

This project team would:

 

•Develop a database procurement strategy within Whitestone’s targeted markets.

•Help Whitestone secure that data (a make, buy decision).

•Clean the obtained data (scraped or purchased) to be useful for further analysis.

•Create an algorithm to automate the prior procedures

Time and structure:

•It is unclear at this point if this initiative will be embedded in a standalone company or will be an extension of Whitestone associates.

Preferred qualifications of student team members:

 

•Entrepreneurial mind-set

•Data procurement and analytical skills

•Project management skills

•Insight into behavioral economic and macroeconomic drivers
•Programming experience (ideally web scraping)