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)
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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
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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.
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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).
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6. Distributions
Barabási, Albert-László,
The Architecture of
Complexity, in: IEEE
Control Systems Magazine
27 (4/2007), 33-42.
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7. Human Resource Management under the assumption of
normal distribution or power-law distribution
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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
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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
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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
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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
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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
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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
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16. References
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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
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Griffiths, J. 2005. BBC Gets Creative as HR Jobs Are Cut, People Management, 11(9), 9.
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Liu, Y./Slotine, J./Barabási, A., 2011. Controllability of Complex Networks. Nature 473, 167-173.
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Marion, R. 1999. The edge of organization: Chaos and complexity theories of formal social organizations. Thousand Oaks: SAGE
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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.
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