Smarter service delivery and business analytics      


Smarter service delivery and business analytics - overview

Our research focus is to improve the operational efficiency of services delivery and to develop advanced business analytics tools and techniques. We develop analytical tools to predict and manage delivery risk as well as improve the adoption and delivery of our services to clients. Going forward we see a greater emphasis on social business analytics as a driver of margin expansion. Our research has resulted in significant benefits to the IBM services business and clients. In particular our research is central to several of these initiatives:

  • Predictive analytics from IBM Research was applied to 30,000 projects in 2011; this combined with disciplined delivery drove average quality benefit of $50 million over last 3 years.
  • Workforce analytics from IBM Research reduced attrition in targeted growth markets by 30%.
  • Research-developed Application Assembly Optimization model and tooling which applies "factory floor" assembly and automation principles to the application development process. This enabled double-digit productivity and $50million of savings across 750 projects.

Additionally, we have developed deep analytics techniques for analysis of over 30 million patents and scientific articles from around the world to provide valuable insights into competitive landscape, white space, and intellectual property portfolios. We also work on analyzing corporate brand and reputation, by using advanced text and data analytics to mine a wide range of social media content, such as blogs, news, forums, and corporate internal information to derive customer and enterprise insights, such as brand and reputation insights, risk and compliance monitoring, market and competitive insights.

Finally, we work on advanced modeling and analytics solutions to improve the performance and business impact by helping it drive lower equipment operational costs, improved equipment availability, longer component lifetimes, and optimized production levels.


Krishna Ratakonda:
Jeff Kreulen:
Rama Akkiraju: