Analytics and Optimization

The Analytics and Optimization group conducts active research in areas of mathematical sciences such as data mining, predictive modeling, mathematical optimization, algorithms and theory, stochastic analysis, simulation, pattern recognition, and statistics. Much our research in these areas appears in prestigious peer-reviewed conferences and journals. As a group, we have been actively collaborating with academia on various research topics related to our project themes.

Our key objectives is to develop innovative research tools and technologies in the analytics and optimization area (aimed at improving the quality, efficiency, and effectiveness of globally integrated service delivery organizations) as well as in the business analytics area (aimed at building differentiated solutions for industry-specific problems). Most of the problems in the analytics and optimization area are motivated by the business problems encountered by IBM’s service delivery organizations. These problems typically involve new approaches and require that we apply our research expertise in novel ways. In the business analytics space, we work closely with the Analytics and Optimization (AO) service line of IBM’s Global Business Services organization to create innovative solutions for clients and the market.

The projects in the analytics and optimization area require solid mathematical modeling and identification of right algorithmic approach based on business insights. While these projects give a competitive edge to our partners from other IBM business units, they also give rise to interesting research questions for us to work on. Examples of such projects that we have executed are capacity utilization, hiring & training, strategic planning & budgeting, workforce scheduling, contingency planning, supply chain optimization, etc.

In the business analytics area, we focus on developing industry-specific solutions particularly for the Indian and other growth markets. In addition to developing novel techniques, we use standard industrial tools such as ILOG (for modeling, linear programming, constraint programming etc.) and SPSS (for statistical purposes). We work closely with client facing IBM practitioners and consultants who bring in the domain expertise from various industry sectors such as Finance, Retail and Travel and Transportation (T&T) and service lines such as Supply Chain Management (SCM) and Human Capital Management (HCM). Our current focus areas include Risk Models for the Financial Sector, Customer Analytics for Retail and T&T Sectors.