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PowerPoint Presentation - University of Arizona

VIEWS: 3 PAGES: 46

									     Outsourcing of Professional Services:
   Technical, Economic, Organizational, and
               Strategic Aspects
               University of Arizona
                    Spring 2007
              Professor Amar Gupta
Tom Brown Chair and Senior Director for Research and
                Bus. Development
          Eller College of Management
             Tucson, AZ 85721 USA
             History of Evolution
• The “Kodak” Effect: 1989: To IBM, DEC,
  Businessland
            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!
       Other Significant Developments

• Y2K and EEC
• Policies of governments in emerging economies
• Policies of governments in developed economies
    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!
       Outsourcing in Other Industries

• Optics Industry
• Steel Industry



• Impact of Disruptive Technologies
       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
                      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!!
              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….
                Productivity Issues

•   1 Person                 •   1
•   10 Persons Co-located    •   10 X F
•   10 Persons Distributed   •   10 X f
•   10 Persons Distributed   •   10 X f / R
                    Distance Tax

•   Communications
•   Travel
•   Maintenance of Duplicate Facilities
•   Cultural
•   ..
          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
            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.
              Overall Numbers

• Number of US companies
• Number of Jobs Relative to Overall Size in
  India
• Percentage of Global Market
           Outsourcing in Other Areas

•   Legal: P & G
•   Accounting
•   R&D
•   Teaching: My job can be outsourced!
•   British Rail
•   Italian Passports
             Question for Break

• Think of other examples of outsourcing
• Think of older examples of outsourcing
   Organizational Issues

•Intra-organizational, Inter-
organizational, or Partnership
•Degree of Coupling
•Intellectual Property Issues –
possibility of taxing IP
exports/imports
      Creation of New Terms and Models
•   Outsourcing
•   Offshoring
•   Globalization
•   Near-shoring
•   In-sourcing
•   Multi-sourcing
•   Co-sourcing
One Consulting Company’s View
                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
         Potential Locations

   Country           Skills & Training
Russia                     A+
India                      A
Israel                     A
China                      B
Ireland                    B
Singapore                  B
Malaysia                   C
Mexico                     C
Philippines                C
        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)
             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.
       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
                  Key Motivators

•   Cost
•   Skill Levels
•   Time to Enter Market
•   Economies of Scale
•   Local Market Needs
•   Opportunity to Concentrate on “Bigger” Issues
                             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
               Partnership Models

•   Resource Based
•   Offshore/Nearshore Development Center
•   Build, Operate, and Transfer
•   Joint Ventures
•   ..
      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
                 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.
      Example Organizations/Projects

• IBM PC
• Polaroid
• Novartis
          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
            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
24-Hour Global Knowledge Factory
                 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
    Two concurrent approaches to knowledge-based
                      design…

              SSPARCy                                                    MATE
• Examine relation between changing expense            • Fully integrate all stakeholders into design
and utility functions and design parameters            process in an efficient and user-friendly
                                                       manner
• Provide designers with more concrete
method of expressing design rationale                  • 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
      Inputs
    - range of           Bracketing
   uncertainty            Software
- attribute value         Module
  - user choice



                         Indifference      yes      Outputs
                           Point?                - indifference
                                                      point
                                no
  User input
 - user choice              Outputs
                        - new range of
                          uncertainty
                       - attribute value




             Dynamic Web-based Interface
              for Knowledge Acquisition
Decision Rationale Module              Decision Archival Module


       Attribute                               Decision
       Definition                              Rationale



        Utility                                 Decision
       Interview                               Parameters



         Utility             Utility           Attribute
        Function            Measures            Values




  Architecture Diagram for “KNOWFACT”
                    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.
        Knowledge Management

     Sources                       Bottleneck
                                                          Receivers
S1

     Pesetas       Conversion                                     R1

                                            Conversion       French
                                                             francs
S2

               Conversion                                         R2
                                             Conversion      US




Sm
               Conversion
                                                                  Rn
                                          Conversion




                            Information
                            Highway
            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
        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!!!
    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
                             Wireless
            Computing
                            Technology
            Technology

               Wireless Grid Services
        Grids for Virtual Organizations

Grid Type               Mainly Provides
Computational Grid      Computational Power


Data Grid               Data Access and Storage


Utility Grid            On-Demand Access to
                        Grid Resources
                Virtual Enterprises?
• 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
    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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