Data Analytics for IBM’s IT Service Deals’ Solutioning: Methodologies and Practical Implications( Aly Sami Megahed )

March 11, 2019 @ 12:00 pm – 1:00 pm
E-JUST, HQ Building - Room No. 207

Data Analytics for IBM’s IT Service Deals’ Solutioning: Methodologies and Practical Implications

Aly Sami Megahed
Research Staff Member
IBM Almaden Research Center, San Jose, California, USA

IBM competes in a tender-like process to win highly valued IT service contracts as part of its $20B outsourcing business. Focusing on deals that are $10M and above, the typical negotiation lifecycle is anywhere between 3 to 12 months. Each deal contains IT services like cloud computing, service desk, and databases. The average number of total components/services in such opportunities is 10k. We then develop a pricing framework and show new theoretical and empirical results. Lastly, we present machine learning based models that combine structured and unstructured data to predict whether prospective deals will result in signed contracts. We empirically show that combining structured and unstructured data significantly enhances prediction accuracy and produces a prediction superior to human predictions. Our approaches were deployed in production resulting in a verifiable $350M business impact and a significant improvement in the production/win rates and efficiencies.


Dr. Aly Megahed is a research staff member at IBM’s Almaden Research Center in San Jose, CA. In his current job, he develops and advances research in analytics, statistics, machine learning, and operations research to address different service science, cloud computing, Internet of Things (IoT), and blockchain technology problems. Dr. Megahed got his Ph.D. in Industrial Engineering from Georgia Tech. He has given both invited and submitted talks at several conferences, companies, and institutions/universities, and has his work published in several academic journals and conferences in addition to filing 30 patent disclosures. Dr. Megahed has also won several internal IBM awards and external ones, including the second place at the INFORMS Innovative Applications in Analytics Award, being a finalist (so far) for the Edelman award, and the first place at the Excellence in Service Innovation Award of ISSIP.