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Leadership Science 1 Parsing the Influential Increment in the Language of Complexity Academy of Management Annual Meeting 2007 Jim Hazy Adelphi University.

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Presentation on theme: "Leadership Science 1 Parsing the Influential Increment in the Language of Complexity Academy of Management Annual Meeting 2007 Jim Hazy Adelphi University."— Presentation transcript:

1 Leadership Science 1 Parsing the Influential Increment in the Language of Complexity Academy of Management Annual Meeting 2007 Jim Hazy Adelphi University Reference as: Hazy, J. K. (2007). Parsing the "influential increment" in the language of complexity: Uncovering the systemic mechanisms of leadership influence. Paper presented at the Academy of Management Annual Conference, Philadelphia, PA.

2 © Copyright 2007 James K. Hazy – All rights reserved 2 Katz & Kahn – Influential Increment Open Systems Definitions Incomplete design Internal change External change Boundary issues Membership challenges Complex Systems Interpretations Dynamic bottom-up self-organization Dynamical System Stabilities/Instabilities Adaptive tensions Networks, the meaning of boundaries Autonomous self-interested agents in a complex adaptive system (cas)

3 © Copyright 2007 James K. Hazy – All rights reserved 3 Organization: A Rent Producing System of Capabilities The firm processes its resources for the benefit of its stakeholders. Agents organize to benefit from these resource flows. Operating Profits & Cash Flow Resources Available for Investment Investment in Capabilities Capabilities Services, Delivery, etc Revenue From Current Operations + + Value Creation Loop Market Carrying Capacity + Competition - - +

4 © Copyright 2007 James K. Hazy – All rights reserved 4 Organizational System Exploration & New Capabilities Building Exploitation of Existing Capabilities New & Emerging Existing Generative Leadership Convergent Leadership Environment Organizational Boundary Resources Outputs Information Dynamic Configuration of Capabilities Models of System & Environment Markets Unifying Leadership Agents organize where the boundaries between their system and its environment are sufficiently far from thermodynamic equilibrium (i.e where there is adaptive tension) such that order is possible. They do this by reconfiguring themselves to address opportunities... In order to o explore and build new capacity, and... to exploit their current capabilities. This doesnt happen in the blind. Cognitive, social agents form mental models of the system and the environment and try to identify and shape the dynamical attractors in their models to predict and enact the best interactions Models are not enough. The system- level dynamic capabilities processes must also be influenced or biased. Leadership is needed. Generative leadership is needed to create new possible futures for the organization. It is closely related to leading innovation but includes exploration in the environment for new resources as well. Convergent leadership operates on agents expectations with respect to interactions to move organizing activities toward perceived dynamical attractors. Unifying leadership identifies & evolves useful boundaries (i.e., where order can evolve) and sustains a unified organizational identity. In this way, the presence of adaptive tension enables order to evolve as resource & information flows are organized into quasi-stable configurations and are thus quasi-predictable using dynamical systems models. Each of these leadership dimensions will be described in detail in the following charts.

5 © Copyright 2007 James K. Hazy – All rights reserved 5 Convergent Leadership Variables identified for certain dimensions of the organizations state. Leadership catalyzes interactions that converge systems flow toward attractors. These interactions enact an adaptive walk toward efficient performance at a local optimum. Deviations from norm (including fluctuations not along adaptive walk) are attenuated through negative feedback.

6 © Copyright 2007 James K. Hazy – All rights reserved 6 Leadership interactions converge action and decisions toward models-in-use Leadership interactions converge action and decisions toward models-in-use Models of Known Opportunities & Capabilities Market Capacity & Competition Rent Potential from Existing Markets Profits from operations Organizational Slack Investment in Exploitation Limits to Existing Capabilities Capabilities Operate to Exploit Existing Markets Complacency & Limits to Models-in-Use Boundary Value Gathering Convergent Leadership…

7 © Copyright 2007 James K. Hazy – All rights reserved 7 Generative Leadership Variables only generally understood- specifics about future state to be determined. Leadership catalyzes interactions that generate possible futures for the system. Leadership catalyzes interactions that evaluate select and partition interactions. Deviations from norm (including fluctuations not along adaptive walk) are amplified through positive feedback.

8 © Copyright 2007 James K. Hazy – All rights reserved 8 Leadership interactions search for opportunities & generate a variety of possible new models-in-use Leadership interactions search for opportunities & generate a variety of possible new models-in-use Models of Search Strategies & Possible Opportunities New & Emerging Markets & Competition Rent Potential from New Markets Profits from New activities Organizational Slack Investment in Building New Capabilities Limits to New Capabilities Dynamic Capabilities Explore & Build New Capabilities Failure to Prime the System, Fatigue from Long Time Delays & Limits to Imagination Boundary Value Identifying Generative Leadership…

9 © Copyright 2007 James K. Hazy – All rights reserved 9 Unifying Leadership Define boundaries internally, externally and ecologically including permeability Define and evolve identity Select among and disambiguate strategies Moderate and balance tensions Across boundaries Between exploitation (convergent leadership) & exploration (generative leadership) activities.

10 © Copyright 2007 James K. Hazy – All rights reserved 10 Leadership interactions adjust system parameters to establish & clarify identity, boundaries & models-in-use Leadership interactions adjust system parameters to establish & clarify identity, boundaries & models-in-use Models of the System, Its Boundaries & Models-in-Use Markets & Competition Rent Potential from Markets Organizational Slack Capabilities Built, Configured & Eliminated Failure to Select & Apply Execution Pressure to Appropriate Models-in-Use Boundary Value Identifying Value Gathering Failure to Sustain Innovation Unifying Leadership…

11 © Copyright 2007 James K. Hazy – All rights reserved 11 Influential Increment & Complexity Complex Systems Interpretations Dynamic bottom-up self-organization Dynamical System Stabilities/Instabilities Adaptive tensions Networks, the meaning of boundaries Autonomous self-interested agents in a complex adaptive system (cas) Leadership Mechanisms Generative Leadership Convergent Leadership Unifying leadership

12 © Copyright 2007 James K. Hazy – All rights reserved 12 Additional references on topic Hazy, J. K. (2006). Measuring leadership effectiveness in complex socio-technical systems. Emergence: Complexity and Organization (E:CO), 8((3)), Hazy, J. K. (2007). Computer models of leadership: Foundation for a new discipline or meaningless diversion? The Leadership Quarterly, 18(4), Hazy, J. K. (in press-a). Leadership or luck? The system dynamics of Intel's shift to microprocessors in the 1970s and 1980s. In M. Uhl-Bien & R. Marion (Eds.), Complexity and leadership, Volume 1: Conceptual foundations. Charlotte, NC: Information Publishing Associates. Hazy, J. K. (in press-b). Patterns of leadership: A case study of influence signaling in an entrepreneurial firm. In M. Uhl-Bien & R. Marion (Eds.), Complexity and leadership, Volume 1: Conceptual foundations. Charlotte, NC: Information Publishing Associates. Hazy, J. K., Goldstein, J. A., & Lichtenstein, B. B. (Eds.). (2007). Complex Systems Leadership Theory. Mansfield, MA: ISCE Publishing Company. Surie, G., & Hazy, J. K. (2006). Generative leadership: Nurturing innovation in complex systems. Emergence: Complexity and Organization (E:CO), 8(4),


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