Page Last Updated: Wednesday, 27 January 2016 09:36 EDT, 2002, 2008, 2011, 2012, 2016

Complex Operational and Organizational Problems

Topic: Analysis of messy data

Dr. Dean S. Hartley III

One of the techniques of operations research is the design of experiments to collect data for analysis. Various designs are available, such as fractional factorial, Latin hypercube, and response surface methodology (RSM). The purpose of these designs is to allow the identification of the factors (including interactions) that affect the results and to permit estimation of their influences. These methods assume that the controllable factors are actually controllable. Generally, these factors are actually controllable only within certain limits. Thus, the results may not be neat, orthogonal sets of independent data, but messy data. Additionally, many situations do not permit designed experiments. The data have been collected for some other purpose and have no structure at all. This results in very messy data.

Messy data can be analyzed, sometimes yielding valuable results.

Select one of the links below.

Year Client Project
1978 Milliken & Co. Fashion Fabrics Define how to enter the dress business.
1983 Milliken & Co. Carpets Lead the Information Management Task Force.
1988 JAD Validate attrition algorithms using historical data.
1998 US Forces Japan Recommend a statement of work for US Forces Japan Construction Management procurement.
2000 Federal Bureau of Investigation (FBI) Make recommendations on FBI staffing.
2001 US Army Medical Research and Material Command (MRMC) Telemedicine and Advanced Technology Research Center (TATRC) Advise on portable computerized medical records for soldiers.

Return to Website Entrance.

Solving Complex Operational and Organizational Problems
Dr. Dean S. Hartley III, Principal