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Outsourcing of Professional Services: Technical, Economic, Organizational, and Strategic Aspects

Outsourcing of Professional Services: Technical, Economic, Organizational, and Strategic Aspects. University of Arizona Fall 2008. Professor Amar Gupta Tom Brown Chair and Senior Director for Research and Bus. Development Eller College of Management Tucson, AZ 85721 USA.

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Outsourcing of Professional Services: Technical, Economic, Organizational, and Strategic Aspects

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  1. Outsourcing of Professional Services: Technical, Economic, Organizational, and Strategic Aspects University of Arizona Fall 2008 Professor Amar Gupta Tom Brown Chair and Senior Director for Research and Bus. Development Eller College of Management Tucson, AZ 85721 USA

  2. History of Evolution • The “Kodak” Effect: 1989: To IBM, DEC, Businessland

  3. History of Outsourcing • Earlier in 1963, EDS took over EDP department of Blue Cross of Pennsylvania • EDS took equity position in System One of Continental Airlines • EDS purchased by GM in early 80s and spun-off again • 10 % of outsourcing revenue must be ploughed back into South Australia’s economic growth!

  4. Other Significant Developments • Y2K and EEC • Policies of governments in emerging economies • Policies of governments in developed economies

  5. Outsourcing in Automobile Industry • Ford Motor Company in 1900s • Import of Parts from other locations/countries • Markets versus Manufacturing Locations • Transition back to the US!

  6. Outsourcing in Other Industries • Optics Industry • Steel Industry • Impact of Disruptive Technologies

  7. Economic Issues • Analysis of Individual Companies • Analysis of Industry Sectors • Analysis of Individual State/Local Governments • (Case of Indiana vs. Springfield) • “Net” Impact to Individual • Loss of Job vs. Benefits as Consumer, Taxpayer, Shareholder

  8. Indiana Example • Summer of 2003: Tata America Int. Corp, Accenture, and Deloitte Consulting make bids ranging between $ 15.2 million and $ 38.5 million. No Indiana-based company submitted bid. Up to 65 contract workers were envisaged to work alongside 18 state workers. • September 2003: Governor Frank O’Bannon accepts lowest bid. • November 2003: Governor Joe Kernan cancels contract. • Decision NOT related to shortcoming of any type. • Projected Difference: $ 8.1 million versus approximately 50 employees. • Decision of Voters in 2004!!

  9. Springfield Example • Cost of Drugs Lower Abroad: typically one-fifth to one-half; • Better Services for Residents of City and/or Lower taxes; • Model accepted at State Level; • California has adopted slightly different model: CGI etc.; • Practices Vary Widely….

  10. 1 Person 10 Persons Co-located 10 Persons Distributed 10 Persons Distributed 1 10 X F 10 X f 10 X f / R Productivity Issues

  11. Distance Tax • Communications • Travel • Maintenance of Duplicate Facilities • Cultural • ..

  12. Medical Transcription Services • Extended Learning Curve- Eight to Twelve Month Training Program • Cost: US $2500 to $3000/mo versus Indian MT < $300/mo • Education: All have at least undergraduate degrees • 221 science/medical-based degrees • 37 doctors • 17 pharmacists • Cultural: Bagels and Beagles and other cultural differences

  13. Results of Major Studies • $ 1 spent abroad leads to $ 1.45-1.47 of “value” • Of this, foreign firm receives only 33 cents; • US company receives between much more; • Aggregate benefit to US economy of $ 16.8 billion from one sector alone.

  14. Overall Numbers • Number of US companies • Number of Jobs Relative to Overall Size in India • Percentage of Global Market

  15. Outsourcing in Other Areas • Legal: P & G • Accounting • R&D • Teaching: My job can be outsourced! • British Rail • Italian Passports

  16. Question for Break • Think of other examples of outsourcing • Think of older examples of outsourcing

  17. Organizational Issues • Intra-organizational, Inter-organizational, or Partnership • Degree of Coupling • Intellectual Property Issues – possibility of taxing IP exports/imports

  18. Creation of New Terms and Models • Outsourcing • Offshoring • Globalization • Near-shoring • In-sourcing • Multi-sourcing • Co-sourcing

  19. One Consulting Company’s View

  20. Decision Variables • Magnitude of Project • Complexity of Effort • Criticality of Endeavor • Duration and Potential Repeatability • Degree of Need for Scalability • Cost Considerations • Preference for Host Environments: Social, Economic, Political, Skill-Level, Language

  21. Potential Locations

  22. Evaluating Potential for Offshoring • Temporal and Spatial Considerations • Balance between Automation and Labor • Degree of Proximity Needed with Suppliers, Co-Contractors, and Buyers • Time zone differences (Earlier a bug; now a feature) • Degree of Need for Specialized Expertise • Trans-border Data Restrictions • Immigration and other Cross-border Restrictions (H1B, L1 visas; security considerations)

  23. Value Addition Models • By understanding the offshore teams’ role in value addition, firms can plan their models accordingly. Also, as costs get higher, offshore teams can also move up the learning curve to higher value jobs. • Low-end • Mid-range • High-end • For the nation, the important issue is not where companies are based, but where value addition is based.

  24. Delivery Models • Captive center • Joint venture • Third party • Many interrelated issues make different models right for different firms. For example, third-party ventures may allow firms to avoid PR issues of using child labor, or local corruption practices

  25. Key Motivators • Cost • Skill Levels • Time to Enter Market • Economies of Scale • Local Market Needs • Opportunity to Concentrate on “Bigger” Issues

  26. Key Hurdles • Lack of Management Support • Resistance from Employees • Difficulty in Negotiating Contracts • Difficulty in Finding Reliable Partners • Potential Risk to Intellectual Property • Political or Governmental Interference

  27. Partnership Models • Resource Based • Offshore/Nearshore Development Center • Build, Operate, and Transfer • Joint Ventures • ..

  28. Decision-making dependencies for individual work: 3 scenarios (a) Autonomous (b) Semi-Autonomous (c) Heavily-interdependent • - Three scenarios for decision making • - This really is a continuous scale, based on how interdependent the tasks are • Examples: - Autonomous – call center • - Semi-autonomous – hierarchy of experts (tv repair, etc) • - Heavily-interdependent – software development • - Important thing is to assess the knowledge interdependencies first, for two reasons: • 1) know how to setup outsourcing structure for existing operations • 2) determine if new knowledge dependencies can be made, leading to new organizations

  29. Organizational models for heavily-interdependent teams (a) Flat Organization (b) Geography-specific (c) Task-specific Organizational models for heavily-interdependent decision making teams. By addressing the “heavily-interdependent” scenario, one can deal with the complexities of relatively simpler scenarios. Another axis to consider while considering appropriate decision support systems is the nature of the organization. In a flat organization, all decision-makers, regardless of task or geography, can be deemed to belong to a single organization. In other cases, additional layers of hierarchy exist within the overall organization. Based on the degree of importance played by the geography or the task, one can visualize the three cases depicted in figure 3, to filter decision making input and output through either the geography or task group.

  30. Example Organizations/Projects • IBM PC • Polaroid • Novartis

  31. Strategic Issues • Roles of Government Agencies – when to encourage/discourage? • Evolution of “Enclaves” – infrastructure, training, security • Growing Digital Divide – political risk of have-nots in unstable countries

  32. Technical Issues • 24-Hour Knowledge Factory • Automated Translations on a real-time basis to open outsourcing to non-English markets • Surmounting Differences in Accents and Tones of Voice • Transformations and Mediations – meaning of “rear-ended” • Wireless Grids (Wirelessgrids.net) - open rural areas to outsourcing

  33. 24-Hour Global Knowledge Factory

  34. Knowledge Acquisition • Involves acquiring information from human beings, paper based documents, sensors, and other traditional media • May need to be done on a one time basis, periodic basis, or continuous basis • Driven by society, organization, or application

  35. Two concurrent approaches to knowledge-based design… • SSPARCy • Examine relation between changing expense and utility functions and design parameters • Provide designers with more concrete method of expressing design rationale • MATE • Fully integrate all stakeholders into design process in an efficient and user-friendly manner • Collect and process expense and utility data using virtual methods • Result • Efficient communication across multiple locations • Innovative ways of collecting, processing,presenting and interpreting design information

  36. Dynamic Web-based Interface for Knowledge Acquisition

  37. Decision Rationale Module Decision Archival Module Decision Rationale Attribute Definition Decision Parameters Utility Interview Utility Function Utility Measures Attribute Values Architecture Diagram for “KNOWFACT”

  38. Trusted Agents • Can access all the information from multiple databases held by participating organizations. • Will provide only subsets of information to other organizations on a need-to-know basis. • Can be used to access data that one finds hard to reach, such as the “Medicorp” data that the research group utilized. • Will play increasingly valuable role in interorganizational data flows.

  39. Knowledge Management Information Highway Conversion Conversion Conversion Conversion Conversion Conversion Bottleneck Sources Receivers S1 R1 Pesetas French francs S2 R2 US Sm Rn

  40. Knowledge Discovery • Human beings are good at visualizing in 2 or 3 dimensions • Neural networks can perform good visualization in more dimensions • Peaks and valleys predicted with good learning ability, when signal to noise ratio is above a particular threshold

  41. Neural Network Based Approaches • Neural Networks mimic the broad parallelism that characterizes the human brain • Ideal for detecting trends that even human experts may find very difficult to identify • In the case of “Medicorp” data, neural network data mining techniques could reduce inventory levels from 1 billion dollars to 500 million dollars. • Neural Network based data mining techniques appear ideally suited for large data-analysis oriented applications • 50% reduction in carrying costs while leaving operational readiness level unchanged!!!

  42. Wireless Grids: Virtual Organizations • Three aspects to consider when defining possible virtual organizations… • Grid Computing Services versus Wireless Grid Services • Wireless phones versus Wireless Grids • What isn’t being done right now. Grid Computing Technology Wireless Technology Wireless Grid Services

  43. Grids for Virtual Organizations

  44. The Virtual Enterprise is a network of several companies, which contribute their core competences and share resources such as information, knowledge, and even market access in order to exploit fast-changing market opportunities. The relationship can be long or short term. Virtual Enterprise Computing = Grid Computing Virtual Enterprises?

  45. Design Challenges for Virtual Enterprises • Decentralized Control • Accounting • Preference Specification (Service Discrimination) • Ease of Use • Security • Heterogeneity • Cost vs. Performance • Low Overhead • Complementary Resource

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