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Creating a Dynamic Framework for
Human Resource Management
Within Organisational Change

Colloquium on Organisational Change and Development
Bern, 13.09.2012

Tobias M. Scholz
Chair for Human Resource Management
and Organizational Behavior
University of Siegen
Need for Change




“As companies face an information
explosion and an unprecedented need
for flexibility in a rapidly changing
marketplace, the corporate model is in
the midst of a complete makeover.“
(Barabási, 2003:201)


But: Organisations still tend to define and solve problems
based on simplification, predictability, equilibrium and
linearity (Marion, 1999)

Furthermore: Organisations are forced to focus on the
human factor (Pfeffer, 2010)



Tobias M. Scholz                  pmg.uni-siegen.de          2
Need for Change in Human Resource Management



•    Self Positioning
     Strategic Business Partner (Lawler/Mohrman, 2003)
     Specialized Service Partner (Greer et al., 1999)

•    Shift in the Organization
     Decentralization (Moore et al., 2003)
     Outsourcing (Griffiths, 2005)
     Temporary Teams (Schreyögg/Sydow, 2010)
     Disolving Borders (Chesbrough, 2003)
     Virtual Teams (Maznevski/Chudoba, 2000)

•  Changes in Environment
   Globalization (Feiock et al., 2008)
   War for Talents (Michaels, et al. 2001)
   Information Overload (Edmungs/Morris, 2000)
   Cultural Interconnectedness (Clerkin, 2011)
 Search for Dynamic Framework
 Applicability of Complex Systems


Tobias M. Scholz                          pmg.uni-siegen.de   3
Features of Complex Systems (Cilliers, 1998)



•    Complex systems consist of a large number of elements
•    These elements interact dynamically.
•    Interactions are rich; any element in the system can
     influence or be influenced by any other
•    Interactions are nonlinear.
•    Interactions are typically short range.
•    There are positive and negative feedback loops of
     interactions.
•    Complex systems are open systems.
•    Complex systems operate under conditions far from
     equilibrium.
•    Complex systems have histories.
•    Individual elements are typically ignorant of the behavior of
     the whole system in which they are embedded.




Tobias M. Scholz                        pmg.uni-siegen.de            4
Metaphors for Organisational Change (Eoyang, 2011)



•    Fractals are fragmented geographical objects persisting of
     smaller copies of the complete structure (Mandelbrot, 1982).

•    Simple rules are also called minimum specifications and
     can result into system-wide patterns (Wolfram, 2002).

•    Self-organized criticality alludes to the general tension in
     an organization that holds it in some gravity (Bak, 1996).

•    Emergence means the process of pattern creation through
     interaction amongst members that differs to general patterns
     formed in an organization (Garnier et al., 2007).

•    Adaptation means the fit of an organisation to the
     environment and therefore has to adapt evolutionarily to
     internal and external patterns (Siggelkow, 2002).




Tobias M. Scholz                         pmg.uni-siegen.de          5
Distributions




                                       Barabási, Albert-László,
                                       The Architecture of
                                       Complexity, in: IEEE
                                       Control Systems Magazine
                                       27 (4/2007), 33-42.




Tobias M. Scholz   pmg.uni-siegen.de                    6
Human Resource Management under the assumption of
normal distribution or power-law distribution




Tobias M. Scholz                pmg.uni-siegen.de   7
(1) Fractals



•    Gaussian Fractals  Centralization
      – All different HR functions aspire toward a common
        system.



•    Paretian Fractals  Decentralization
      – Sub systems differ and fit towards the HR functions.
      – Through interaction key visions emerge through
         combination and adaptation


                                                                Centralization             Decentralization

                                                                    Order                      Disorder

                                                               Attack Tolerance             Error Tolerance

                                                                 Convergence                  Divergence

                                                           Adjustment to the Average   Adjustment to the Outliers




Tobias M. Scholz                       pmg.uni-siegen.de                                                   8
(2) Simple Rules



•    Gaussian Simple Rules  Order
      – Many rules (distinct and precise)
      – Maintain core competencies of HRM
      – Order leads to a constant adaptation

•    Paretian Simple Rules  Disorder
      – Only few rules (general and minimalistic)
      – Different parts of HR have different rules
      – General rule: All processes need to exist
      – Leads to increased interaction between different parts

                                                                Centralization             Decentralization

                                                                    Order                      Disorder

                                                               Attack Tolerance             Error Tolerance

                                                                 Convergence                  Divergence

                                                           Adjustment to the Average   Adjustment to the Outliers




Tobias M. Scholz                       pmg.uni-siegen.de                                                   9
(3) Self-Organized Criticality



•    Gaussian Self-Organized Criticality  Attack Tolerance (Albert et al., 2000)
      – HR and sub systems are reaching for similarity
      – HR functions can be resumed by other sub-systems
      – Removal of HR functions without replacement can be done often

•    Paretian Self-Organized Criticality  Error Tolerance (Albert et al., 2000)
      – HR and sub systems are striving away from similarity
      – Errors will not spread towards over sub systems
      – Other sub system will fill in, but not adapt the error


                                                                  Centralization             Decentralization

                                                                      Order                      Disorder

                                                                 Attack Tolerance             Error Tolerance

                                                                   Convergence                  Divergence

                                                             Adjustment to the Average   Adjustment to the Outliers




Tobias M. Scholz                         pmg.uni-siegen.de                                                   10
(4) Emergence



•    Gaussian Emergence  Convergence
      – Interaction with different sub systems leads to merging
      – Alignment of functions
      – Emergent processes quickly spread through the HR

•    Paretian Emergence  Divergence
      – Divergence trigger a variety of emergent processes
      – Spreading leads to competition and slow spreading



                                                                Centralization             Decentralization

                                                                    Order                      Disorder

                                                               Attack Tolerance             Error Tolerance

                                                                 Convergence                  Divergence

                                                           Adjustment to the Average   Adjustment to the Outliers




Tobias M. Scholz                       pmg.uni-siegen.de                                                   11
(5) Adaptation



•    Gaussian Adaptation  Adjustment to the Average
      – Selection of functions that handles the majority of
        processes or tasks
      – HR functions seek similarity and majority
      – Outliers could be better

•    Paretian Adaptation  Adjustment to the Outliers
      – Adaptation towards the necessary processes
      – Improvements could only benefit one extreme, not
         majority
      – Different processes adapt constantly
      – Could lead to an arms race                              Centralization             Decentralization

                                                                    Order                      Disorder

                                                               Attack Tolerance             Error Tolerance

                                                                 Convergence                  Divergence

                                                           Adjustment to the Average   Adjustment to the Outliers




Tobias M. Scholz                       pmg.uni-siegen.de                                                   12
Dynamic Framework



•    Path needs to be chosen, based on the information within
     an organization

•    With distribution HRM can support and implement Change
     within an organisation

•    Both distributions lead to different chances and obstacles

•    Fitting distribution is essential and constant surveying

•    Average seems “more right” but reality speaks different
     (e.g. high potentials, cultural diversity)

 Fluid Human Resource Management




Tobias M. Scholz                         pmg.uni-siegen.de        13
Conclusion



•    Complex systems could be a future for organizational studies
     (Andriani, & McKelvey, 2009)


•    Controllability of complex systems is still highly theoretical
     (Liu, Slotine, & Barabási, 2011)


•    Complex system is still a “chaos of the literatures” (Eoyang,
     2011:318)


•    Change in HRM is necessary from a static world towards a
     dynamic world

•    Dynamic HRM allows to act and react on Organisational
     Change

 Distributions can help to support HRM in the
      Organisational Change


                                                                      © Julia Christophers



Tobias M. Scholz                         pmg.uni-siegen.de                                   14
References

Albert, R., Jeong, H., & Barabási, A.-L. 2000. Error and attack tolerance of complex networks, Nature, 406: 378-382.
Andriani, P., & McKelvey, B. 2009. From Gaussian to Paretian thinking: Causes and implications of power laws in organization. Organization Science, 20(6):
1053-1071.
Andriani, P., & McKelvey, B. 2011. Managing in a Pareto world calls for new thinking. M@n@gement, 14(2): 89-118.
Bak, P. 1996. How nature works: The science of self-organized criticality. New York: Copernicus.
Barabási, Albert-László, 2003. Linked: How Everything is Connected to Everything Else and What It Means for Business, Science, and Everyday Life. London:
PLUME Books.
Barabási, A.-L. 2007. The architecture of complexity. IEEE Control Systems Magazine, 27(4): 33-42.
Chesbrough, H.2003. Open innovation. Boston, MA: Harvard Business School Press.
Cilliers, P. 1998. Complexity and postmodernism: Understanding complex systems. London: Routledge.
Clerkin, T. A. 2011. Assessment issues in estimating managerial potential in a global context. International Management Review, 7(1), 5-9.
Edmunds, A. & Morris, A. 2000. The problem of information overload in business organisations: a review of the literature, International Journal of Information
Management, 20(1), 17-28.
Eoyang, G. H. 2011. Complexity and the dynamics of organizational change. In P. Allen, S. Maguire, & B. McKelvey (Eds.), The SAGE handbook of
complexity and management: 317-332. Thousand Oaks: SAGE.
Feiock, R. C./Jae Moon, M./Park, H. J., 2008. Is the World Flat or Spiky? Rethinking the Governance Implications of Globalization for Economic Development.
Public Administration Review 68(1), 24-35.
Garnier, S., Gautrais, J., & Theraulaz, G. 2007. The biological principles of swarm intelligence. Swarm Intelligence, 1(1): 3-32.
Greer, C. R./Youngblood, S. A./Gray, D. A., 1999. Human Resource Management Outsourcing: The Make or Buy Decision. Academy of Management
Executive 13(3), 85-96.
Griffiths, J. 2005. BBC Gets Creative as HR Jobs Are Cut, People Management, 11(9), 9.
Lawler, E. E./Mohrman, S. A., 2003. HR as a Strategic Partner: What Does it Take to Make it Happen. Human Resource Planning 26(3), 15-29.
Liu, Y./Slotine, J./Barabási, A., 2011. Controllability of Complex Networks. Nature 473, 167-173.
Mandelbrot, B. B. 1982. The fractal geometry of nature. New York: W. H. Freeman.
Marion, R. 1999. The edge of organization: Chaos and complexity theories of formal social organizations. Thousand Oaks: SAGE
Maznevski, M. L., & Chudoba, K. M. 2000. Bridging space over time: 90 Global virtual team dynamics and effectiveness. Organization Science, 91(11), 473–
492.
Michaels, E., Handfield-Jones, H., & Axelrod, B. 2001. The war for talent. New York: McGraw Hill.
Moore, S./Eng, E./Daniel, M., 2003. International NGOs and the Role of Network Centrality in Humanitarion Aid Operations. Disasters 2(4), 305-318.
Pfeffer, J. 2010. Building sustainable organizations. The human factor. Academy of Management Perspectives, 24(1), 34-45.
Schreyögg. G., & Sydow, J. 2010. Organizing for Fluidity? Dilemmas of New Organizational Forms. Organisation Science, 21(6), 1251-1262.
Siggelkow, N. 2002. Evolution toward fit. Administrative Science Quarterly, 47(1): 125-161.
Wolfram, S. 2002. A new kind of science. Champaign: Wolfram Media.




Tobias M. Scholz                                                    pmg.uni-siegen.de                                                                      16

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Creating a Dynamic Framework for Human Resource Management

  • 1. Creating a Dynamic Framework for Human Resource Management Within Organisational Change Colloquium on Organisational Change and Development Bern, 13.09.2012 Tobias M. Scholz Chair for Human Resource Management and Organizational Behavior University of Siegen
  • 2. Need for Change “As companies face an information explosion and an unprecedented need for flexibility in a rapidly changing marketplace, the corporate model is in the midst of a complete makeover.“ (Barabási, 2003:201) But: Organisations still tend to define and solve problems based on simplification, predictability, equilibrium and linearity (Marion, 1999) Furthermore: Organisations are forced to focus on the human factor (Pfeffer, 2010) Tobias M. Scholz pmg.uni-siegen.de 2
  • 3. Need for Change in Human Resource Management • Self Positioning Strategic Business Partner (Lawler/Mohrman, 2003) Specialized Service Partner (Greer et al., 1999) • Shift in the Organization Decentralization (Moore et al., 2003) Outsourcing (Griffiths, 2005) Temporary Teams (Schreyögg/Sydow, 2010) Disolving Borders (Chesbrough, 2003) Virtual Teams (Maznevski/Chudoba, 2000) • Changes in Environment Globalization (Feiock et al., 2008) War for Talents (Michaels, et al. 2001) Information Overload (Edmungs/Morris, 2000) Cultural Interconnectedness (Clerkin, 2011)  Search for Dynamic Framework  Applicability of Complex Systems Tobias M. Scholz pmg.uni-siegen.de 3
  • 4. Features of Complex Systems (Cilliers, 1998) • Complex systems consist of a large number of elements • These elements interact dynamically. • Interactions are rich; any element in the system can influence or be influenced by any other • Interactions are nonlinear. • Interactions are typically short range. • There are positive and negative feedback loops of interactions. • Complex systems are open systems. • Complex systems operate under conditions far from equilibrium. • Complex systems have histories. • Individual elements are typically ignorant of the behavior of the whole system in which they are embedded. Tobias M. Scholz pmg.uni-siegen.de 4
  • 5. Metaphors for Organisational Change (Eoyang, 2011) • Fractals are fragmented geographical objects persisting of smaller copies of the complete structure (Mandelbrot, 1982). • Simple rules are also called minimum specifications and can result into system-wide patterns (Wolfram, 2002). • Self-organized criticality alludes to the general tension in an organization that holds it in some gravity (Bak, 1996). • Emergence means the process of pattern creation through interaction amongst members that differs to general patterns formed in an organization (Garnier et al., 2007). • Adaptation means the fit of an organisation to the environment and therefore has to adapt evolutionarily to internal and external patterns (Siggelkow, 2002). Tobias M. Scholz pmg.uni-siegen.de 5
  • 6. Distributions Barabási, Albert-László, The Architecture of Complexity, in: IEEE Control Systems Magazine 27 (4/2007), 33-42. Tobias M. Scholz pmg.uni-siegen.de 6
  • 7. Human Resource Management under the assumption of normal distribution or power-law distribution Tobias M. Scholz pmg.uni-siegen.de 7
  • 8. (1) Fractals • Gaussian Fractals  Centralization – All different HR functions aspire toward a common system. • Paretian Fractals  Decentralization – Sub systems differ and fit towards the HR functions. – Through interaction key visions emerge through combination and adaptation Centralization Decentralization Order Disorder Attack Tolerance Error Tolerance Convergence Divergence Adjustment to the Average Adjustment to the Outliers Tobias M. Scholz pmg.uni-siegen.de 8
  • 9. (2) Simple Rules • Gaussian Simple Rules  Order – Many rules (distinct and precise) – Maintain core competencies of HRM – Order leads to a constant adaptation • Paretian Simple Rules  Disorder – Only few rules (general and minimalistic) – Different parts of HR have different rules – General rule: All processes need to exist – Leads to increased interaction between different parts Centralization Decentralization Order Disorder Attack Tolerance Error Tolerance Convergence Divergence Adjustment to the Average Adjustment to the Outliers Tobias M. Scholz pmg.uni-siegen.de 9
  • 10. (3) Self-Organized Criticality • Gaussian Self-Organized Criticality  Attack Tolerance (Albert et al., 2000) – HR and sub systems are reaching for similarity – HR functions can be resumed by other sub-systems – Removal of HR functions without replacement can be done often • Paretian Self-Organized Criticality  Error Tolerance (Albert et al., 2000) – HR and sub systems are striving away from similarity – Errors will not spread towards over sub systems – Other sub system will fill in, but not adapt the error Centralization Decentralization Order Disorder Attack Tolerance Error Tolerance Convergence Divergence Adjustment to the Average Adjustment to the Outliers Tobias M. Scholz pmg.uni-siegen.de 10
  • 11. (4) Emergence • Gaussian Emergence  Convergence – Interaction with different sub systems leads to merging – Alignment of functions – Emergent processes quickly spread through the HR • Paretian Emergence  Divergence – Divergence trigger a variety of emergent processes – Spreading leads to competition and slow spreading Centralization Decentralization Order Disorder Attack Tolerance Error Tolerance Convergence Divergence Adjustment to the Average Adjustment to the Outliers Tobias M. Scholz pmg.uni-siegen.de 11
  • 12. (5) Adaptation • Gaussian Adaptation  Adjustment to the Average – Selection of functions that handles the majority of processes or tasks – HR functions seek similarity and majority – Outliers could be better • Paretian Adaptation  Adjustment to the Outliers – Adaptation towards the necessary processes – Improvements could only benefit one extreme, not majority – Different processes adapt constantly – Could lead to an arms race Centralization Decentralization Order Disorder Attack Tolerance Error Tolerance Convergence Divergence Adjustment to the Average Adjustment to the Outliers Tobias M. Scholz pmg.uni-siegen.de 12
  • 13. Dynamic Framework • Path needs to be chosen, based on the information within an organization • With distribution HRM can support and implement Change within an organisation • Both distributions lead to different chances and obstacles • Fitting distribution is essential and constant surveying • Average seems “more right” but reality speaks different (e.g. high potentials, cultural diversity)  Fluid Human Resource Management Tobias M. Scholz pmg.uni-siegen.de 13
  • 14. Conclusion • Complex systems could be a future for organizational studies (Andriani, & McKelvey, 2009) • Controllability of complex systems is still highly theoretical (Liu, Slotine, & Barabási, 2011) • Complex system is still a “chaos of the literatures” (Eoyang, 2011:318) • Change in HRM is necessary from a static world towards a dynamic world • Dynamic HRM allows to act and react on Organisational Change  Distributions can help to support HRM in the Organisational Change © Julia Christophers Tobias M. Scholz pmg.uni-siegen.de 14
  • 15.
  • 16. References Albert, R., Jeong, H., & Barabási, A.-L. 2000. Error and attack tolerance of complex networks, Nature, 406: 378-382. Andriani, P., & McKelvey, B. 2009. From Gaussian to Paretian thinking: Causes and implications of power laws in organization. Organization Science, 20(6): 1053-1071. Andriani, P., & McKelvey, B. 2011. Managing in a Pareto world calls for new thinking. M@n@gement, 14(2): 89-118. Bak, P. 1996. How nature works: The science of self-organized criticality. New York: Copernicus. Barabási, Albert-László, 2003. Linked: How Everything is Connected to Everything Else and What It Means for Business, Science, and Everyday Life. London: PLUME Books. Barabási, A.-L. 2007. The architecture of complexity. IEEE Control Systems Magazine, 27(4): 33-42. Chesbrough, H.2003. Open innovation. Boston, MA: Harvard Business School Press. Cilliers, P. 1998. Complexity and postmodernism: Understanding complex systems. London: Routledge. Clerkin, T. A. 2011. Assessment issues in estimating managerial potential in a global context. International Management Review, 7(1), 5-9. Edmunds, A. & Morris, A. 2000. The problem of information overload in business organisations: a review of the literature, International Journal of Information Management, 20(1), 17-28. Eoyang, G. H. 2011. Complexity and the dynamics of organizational change. In P. Allen, S. Maguire, & B. McKelvey (Eds.), The SAGE handbook of complexity and management: 317-332. Thousand Oaks: SAGE. Feiock, R. C./Jae Moon, M./Park, H. J., 2008. Is the World Flat or Spiky? Rethinking the Governance Implications of Globalization for Economic Development. Public Administration Review 68(1), 24-35. Garnier, S., Gautrais, J., & Theraulaz, G. 2007. The biological principles of swarm intelligence. Swarm Intelligence, 1(1): 3-32. Greer, C. R./Youngblood, S. A./Gray, D. A., 1999. Human Resource Management Outsourcing: The Make or Buy Decision. Academy of Management Executive 13(3), 85-96. Griffiths, J. 2005. BBC Gets Creative as HR Jobs Are Cut, People Management, 11(9), 9. Lawler, E. E./Mohrman, S. A., 2003. HR as a Strategic Partner: What Does it Take to Make it Happen. Human Resource Planning 26(3), 15-29. Liu, Y./Slotine, J./Barabási, A., 2011. Controllability of Complex Networks. Nature 473, 167-173. Mandelbrot, B. B. 1982. The fractal geometry of nature. New York: W. H. Freeman. Marion, R. 1999. The edge of organization: Chaos and complexity theories of formal social organizations. Thousand Oaks: SAGE Maznevski, M. L., & Chudoba, K. M. 2000. Bridging space over time: 90 Global virtual team dynamics and effectiveness. Organization Science, 91(11), 473– 492. Michaels, E., Handfield-Jones, H., & Axelrod, B. 2001. The war for talent. New York: McGraw Hill. Moore, S./Eng, E./Daniel, M., 2003. International NGOs and the Role of Network Centrality in Humanitarion Aid Operations. Disasters 2(4), 305-318. Pfeffer, J. 2010. Building sustainable organizations. The human factor. Academy of Management Perspectives, 24(1), 34-45. Schreyögg. G., & Sydow, J. 2010. Organizing for Fluidity? Dilemmas of New Organizational Forms. Organisation Science, 21(6), 1251-1262. Siggelkow, N. 2002. Evolution toward fit. Administrative Science Quarterly, 47(1): 125-161. Wolfram, S. 2002. A new kind of science. Champaign: Wolfram Media. Tobias M. Scholz pmg.uni-siegen.de 16