Does One-Size-Fit-All Suffice for Service Delivery Clients?

  • Shivali Agarwal
  • Renuka Sindhgatta
  • Gargi B. Dasgupta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8274)


The traditional mode of delivering IT services has been through customer-specific teams. A dedicated team is assigned to address all (and only those) requirements that are specific to the customer. However, this way of organizing service delivery leads to inefficiencies due to inability to use expertise and available resources across teams in a flexible manner. To address some of these challenges, in recent times, there has been interest in shared delivery of services, where instead of having customer specific teams working in silos, there are cross-customer teams (shared resource pools) that can potentially service more than one customer. However, this gives rise to the question of what is the best way of grouping the shared resources across customer? Especially, with the large variations in the technical and domain skills required to address customer requirements, what should be the service delivery model for diverse customer workloads? Should it be customer-focused? Business domain focused? Or Technology focused? This paper simulates different delivery models in face of complex customer workload, diverse customer profiles, stringent service contracts, and evolving skills, with the goal of scientifically deriving principles of decision making for a suitable delivery model. Results show that workload arrival pattern, customer work profile combinations and domain skills, all play a significant role in the choice of delivery model. Specifically, the complementary nature of work arrivals and degree of overlapping skill requirements among customers play a crucial role in the choice of models. Interestingly, the impact of skill expertise level of resources is overshadowed by these two factors.


Completion Time Service Time Transfer Time Service Request Delivery Model 
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  1. 1.
    Agarwal, S., Reddy, V.K., Sengupta, B., Bagheri, S., Ratakonda, K.: Organizing Shared Delivery Systems. In: Proc. of 2nd International Conference on Services in Emerging Markets, India (2011)Google Scholar
  2. 2.
    Agarwal, S., Sindhgatta, R., Sengupta, B.: SmartDispatch: enabling efficient ticket dispatch in an IT service environment. In: Proc. of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012 (2012)Google Scholar
  3. 3.
    Alter, S.: Service System Fundamentals: Work System, Value Chain, and Life Cycle. IBM Systems Journal 47(1), 71–85 (2008)CrossRefGoogle Scholar
  4. 4.
    Anylogic Tutorial, How to build a combined agent based/system dynamics model in Anylogic. In: System Dynamics Conference (2008),
  5. 5.
    Assembly Optimization: A Distinct Approach to Global Delivery, IBM GBS White Paper (2010)Google Scholar
  6. 6.
    Banerjee, D., Dasgupta, G.B., Desai, N.: Simulation-based evaluation of dispatching policies in service systems. In: Winter Simulation Conference (2011)Google Scholar
  7. 7.
    Cezik, M.T., L’Ecuyer, P.: Staffing multi-skill call centers via linear programming and simulation. Management Science Journal (2006)Google Scholar
  8. 8.
    Diao, Y., Heching, A., Northcutt, D., Stark, G.: Modeling a complex global service delivery system. In: Winter Simulation Conference 2011 (2011)Google Scholar
  9. 9.
    Easton, F.F.: Staffing, Cross-training, and Scheduling with Cross-trained Workers in Extended-hour Service Operations. Robert H. Brethen Operations Management Institute (2011) (manuscript)Google Scholar
  10. 10.
    Espinosa, J.A., Slaughter, S.A., Kraut, R.E., Herbsleb, J.D.: Familiarity, Complexity, and Team Performance in Geographically Distributed Software Development. Organization Science 18(4), 613–630 (2007)CrossRefGoogle Scholar
  11. 11.
    Franzese, L.A., Fioroni, M.M., de Freitas Filho, P.J., Botter, R.C.: Comparison of Call Center Models. In: Proc. of the Conference on Winter Simulation (2009)Google Scholar
  12. 12.
    Gel, E.S., Hopp Wallace, J., Van Oyen, M.P.: Hierarchical cross-training in work-in-process-constrained systems. IIE Transactions, 39 (2007)Google Scholar
  13. 13.
    Jaber, M.Y., Bonney, M.: A comparative study of learning curves with forgetting. Applied Mathematical Modelling 21, 523–531 (1997)CrossRefzbMATHGoogle Scholar
  14. 14.
    Kleiner, M.M., Nickelsburg, J., Pilarski, A.: Organizational and Individual Learning and Forgetting. Industrial and Labour Relations Review 65(1) (2011)Google Scholar
  15. 15.
    Laguna, M.: Optimization of complex systems with optquest. OptQuest for Crystal Ball User Manual Decisioneering (1998)Google Scholar
  16. 16.
    Lo, C.F.: The Sum and Difference of Two Lognormal Random Variables. Journal of Applied Mathematics 2012, Article ID 838397, 13 pages (2012)Google Scholar
  17. 17.
    Narayanan, C.L., Dasgupta, G., Desai, N.: Learning to impart skills to service workers via challenging task assignments. IBM Technical Report (2012)Google Scholar
  18. 18.
    Nembhard, D.A.: Heuristic approach for assigning workers to tasks based on individual learning rates. Int. Journal Prod. Res. 39(9) (2001)Google Scholar
  19. 19.
    Ramaswamy, L., Banavar, G.: A Formal Model of Service Delivery. In: Proc. of the IEEE International Conference on Service Computing (2008)Google Scholar
  20. 20.
    Subramanian, D., An, L.: Optimal Resource Action Planning Analytics for Services Delivery Using Hiring, Contracting & Cross-Training of Various Skills. In: Proc. of IEEE SCC (2008)Google Scholar
  21. 21.
    Sengupta, B., Jain, A., Bhattacharya, K., Truong, H.-L., Dustdar, S.: Who do you call? Problem resolution through social compute units. In: Liu, C., Ludwig, H., Toumani, F., Yu, Q. (eds.) ICSOC 2012. LNCS, vol. 7636, pp. 48–62. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  22. 22.
    Spohrer, J., Maglio, P.P., Bailey, J., Gruhl, D.: Steps Toward a Science of Service Systems. IEEE Computer 40(1), 71–77 (2007)CrossRefGoogle Scholar
  23. 23.
    Shared Services & Outsourcing Network (SSON) and The Hackett Group, Global service center benchmark study (2009)Google Scholar
  24. 24.
    Verma, A., Desai, N., Bhamidipaty, A., Jain, A.N., Barnes, S., Nallacherry, J., Roy, S.: Automated Optimal Dispatching of Service Requests. In: Proc. of the SRII Global Conference (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Shivali Agarwal
    • 1
  • Renuka Sindhgatta
    • 1
  • Gargi B. Dasgupta
    • 1
  1. 1.IBM ResearchIndia

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