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Creating a Dynamic Framework for Human Resource Management


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Creating a Dynamic Framework for Human Resource Management

  1. 1. Creating a Dynamic Framework forHuman Resource ManagementWithin Organisational ChangeColloquium on Organisational Change and DevelopmentBern, 13.09.2012Tobias M. ScholzChair for Human Resource Managementand Organizational BehaviorUniversity of Siegen
  2. 2. Need for Change“As companies face an informationexplosion and an unprecedented needfor flexibility in a rapidly changingmarketplace, the corporate model is inthe midst of a complete makeover.“(Barabási, 2003:201)But: Organisations still tend to define and solve problemsbased on simplification, predictability, equilibrium andlinearity (Marion, 1999)Furthermore: Organisations are forced to focus on thehuman factor (Pfeffer, 2010)Tobias M. Scholz 2
  3. 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 SystemsTobias M. Scholz 3
  4. 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 4
  5. 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 5
  6. 6. Distributions Barabási, Albert-László, The Architecture of Complexity, in: IEEE Control Systems Magazine 27 (4/2007), 33-42.Tobias M. Scholz 6
  7. 7. Human Resource Management under the assumption ofnormal distribution or power-law distributionTobias M. Scholz 7
  8. 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 OutliersTobias M. Scholz 8
  9. 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 OutliersTobias M. Scholz 9
  10. 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 OutliersTobias M. Scholz 10
  11. 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 OutliersTobias M. Scholz 11
  12. 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 OutliersTobias M. Scholz 12
  13. 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 ManagementTobias M. Scholz 13
  14. 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 ChristophersTobias M. Scholz 14
  15. 15. ReferencesAlbert, 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 InformationManagement, 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 ofcomplexity 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 ManagementExecutive 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: SAGEMaznevski, 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 16