Projects

Problem: Engineering teams averaged over 170 hours per week on identifying, tracking and resolving ("troubleshooting") application errors. Created a diagnostic tool to identify and track diagnosis with "solutioning" in mind.
Results: In the first month of use, engineering teams saw a reduction of 49 hours of troubleshooting per week. In measuring engineering use, I improved the diagnostic application. The second and third months saw a decrease of 116 hours of troubleshooting per week. The final update resulted in 18 hours of troubleshooting per week by engineering teams.
Vision: Using this original model of a solution, I have integrated this machine learning tools that solve and communicate solutions.

Problem: In 2004, I uncovered inflation for business inventory was being significantly underreported. For my business, I began investigating a business treasury instrument to protect production costs.
Result: In the period of time measured from available data, the CAGR of the business treasury instrument exceeded 28% over its history including a cost adjustment associated with maintaining the instrument.
Comparison* (over a similar period of time):
- Gold CAGR: 9% (rounded)
- S&P 500 CAGR: 8% (rounded)
- Nasdaq CAGR: 10% (rounded)
- US 10 Year Treasury CAGR: 4% (rounded)

* These values only reflect the result at the time I compared from the beginning to the end. I do not update this page.

Problem 1: Vague terminology of healthcare costs.
Problem 2: Specific disease incurred a significant comprehensive healthcare cost for both patients and medical practitioners.
Results: Defined healthcare costs with a holistic measure - hereafter referred to as units. Uncovered that both patients and medical practitioners paid 7,896 units cost per diagnosis of disease. Reduced the cure cost to 3,079 units. Researched preventative measures to reduce costs to 780 units.
Vision: I've used this template to expand healthcare solutions to a few countries in Asia needing help with high healthcare costs or a shortage of medical care labor.

Note: Due to overwhelming bureaucracy, no healthcare data services are available for countries in the European Union or United States of America.

Problem: 17TB of data creating costs for storage and disaster recovery. Further costs with complex development to handle the scale of the data size along with administering the data environment.
Results: Reduced data environment size 97% along with reducing storage and performance costs by over 80%. Updated tools that would minimize (or eliminate) software licensing fees while providing deeper insights into costs for leadership.