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My Experience at IBM

Discover my experiences working at IBM, particularly within the AXP team and the Service Delivery Center. Learn about the scale of operations, with over 2000 IT professionals across 23 countries and contracts worth over $4 billion. Delve into the intricacies of team dynamics, weekly meetings, and the challenges of flexible working environments. I’ll share insights on data mining, service process metrics, and statistical analysis applied to resource optimization. Plus, a glimpse into my living conditions and the unique aspects of my team.

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My Experience at IBM

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  1. My Experience at IBM Ken S. Li Dept. of Math

  2. IBM As We Know - History

  3. IBM As We Know – History

  4. IBM As We Know – Today

  5. IBM As We Know – Business

  6. IBM at AXP • One of IBM’s all-time biggest IT service contracts valued at more than $4 billion • More than 2000 IT professionals worked in the IBM@AXP team • Delivery Team (located in Phoenix, Albert Kuhn’s Team) is under Service Delivery Center-West (located Boulder, Colo.) • Manager Team is located in AXP’s World Financial Center (located in NYC) • IBM@AXP team is housed in 23 countries

  7. Interesting Acronyms • OID, OIM, RFS, PCC, EIS, ESIM, LOA, BAU, PCR, JAPA

  8. The Meetings • Weekly staff meetings (Albert Kuhn, Art Hoffman, Joseph Correnti) • In person, Tele Conferencing, Video Conferencing • Ping, Who is just joined?

  9. Communications • Lotus Notes system • Email is over used • Calendar events • Same time

  10. Working Environment • Small cubical, small office • Flexible working schedule • Travel to work • Home office

  11. My Work • Data Mining from Web Tools • Study of Metrics for service processes • Forecasting of incoming volume • Forecasting of outgoing volume • Calculation of Resource requirements • Using statistical analysis to redefine cycle time target for RFS process

  12. The RFS Process • The RFS process consists of Initialization, Request Confirmation, Solution, Quality Assurance, Waiting for Customer and other components • Types of RFS’s: Complex, T & M, Incremental, Small • BAU Throughput, BAU Queue Size, Backlog • Target cycle time for various RFS’s

  13. Mathematics Problems • Determine distribution for service time • Determine the parameters of the distributions • Relation between the sum distribution and the individual distributions • Capacity and availability • Optimization of resourcing

  14. The weather, the living condition • Hot • Dry • No Grasses • Forest has no trees • Not cheap, not expensive, big malls

  15. Bob – My Roommate

  16. Kyle, Sean and Matt – The Students

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