Statistical Challenges for a Crowd-Sourcing--Based Delivery Platform of Software Development

• Activity Number: 489
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Ta-Hsin Li*
• Companies: IBM T.J. Watson Research Center
• Keywords: predictive analytics ; risk estimation ; participation ; freelancer ; crowd sourcing ; smarter workforce

Abstract

An emerging business model in application software development in large enterprises is to employ a flexible workforce, or a resource pool, which consists of vetted freelancers, to support the application development process, including software design, coding, and application testing. The success of this model depends crucially on having the right participants at the right time when their skills are needed. However, the need for each set of skills fluctuates over time, depending on the software development activities of the business; the number of participants also fluctuates because participation is entirely voluntary and performed via self-selection of work. Therefore, maintaining the appropriate capacity, or supply, of the resource pool is an important and challenging problem for the service provider who utilizes this type of delivery platform. This talk will discuss statistical challenges in supply predictive analytics for a resource pool operation in IBM's Global Business Services Division.