Cybernetic Perspective: Difference between revisions
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The origin of the cybernetic models goes back to the end of the 1970s with the work of Stanford Beer and his Viable System Model (VSM). With both traditional management systems and cybernetic models, data plays an important role, but with cybernetic models, data is used to drive continuous, adaptive change, whereas in traditional systems, it is used to enforce standards. The cybernetic model includes the following four considerations: | The origin of the cybernetic models goes back to the end of the 1970s with the work of Stanford Beer and his Viable System Model (VSM). With both traditional management systems and cybernetic models, data plays an important role, but with cybernetic models, data is used to drive continuous, adaptive change, whereas in traditional systems, it is used to enforce standards. | ||
The cybernetic model includes the following four considerations: | |||
* Feedback loops: Output information from the system is continuously fed back as input, allowing the organization to self-regulate and adjust course. | * Feedback loops: Output information from the system is continuously fed back as input, allowing the organization to self-regulate and adjust course. | ||
* Adaptation: The organization's ability to adapt internally and externally to its environment is critical. | * Adaptation: The organization's ability to adapt internally and externally to its environment is critical. |
Revision as of 02:53, 9 September 2025
Introduction
While traditional management systems rely on a top-down, command-and-control hierarchy, cybernetic models view an organization as a self-regulating system that uses feedback to maintain its goals. Performance measurement is seen as an important component of cybernetic models that include goal setting and predictive models to facilitate decisions of alternative actions.
Generalities
The origin of the cybernetic models goes back to the end of the 1970s with the work of Stanford Beer and his Viable System Model (VSM). With both traditional management systems and cybernetic models, data plays an important role, but with cybernetic models, data is used to drive continuous, adaptive change, whereas in traditional systems, it is used to enforce standards.
The cybernetic model includes the following four considerations:
- Feedback loops: Output information from the system is continuously fed back as input, allowing the organization to self-regulate and adjust course.
- Adaptation: The organization's ability to adapt internally and externally to its environment is critical.
- Complex systems: an organization is a complex, interconnected whole, as opposed to being a collection of isolated, independent parts.
- Decentralized control: Although a central command exists with a cybernetic model, the organization’s units have the autonomy to respond quickly to local changes, as they are capable of making the best-informed decisions based on the most current information.
Cybernetic models attempt to rigorously establish processes for planning, comparing, and evaluating by considering two distinct sets of measures: those defined by the objectives and those required by the predictive models. Traditionally, control systems have emphasized goal-oriented measures. Performance measurement became associated with negative feedback based on the detection of the gaps between the planned objectives and the actual measures of the outcome. In the cybernetic model, measures involve both some aspects of control and others of communication and behaviors.
Limits of the Cybernetic Model
A cybernetic model is difficult to apply because of the difficulty of getting performance data and being able to compare it to quantifiable and unambiguous standards. From the cybernetic perspective, performance measurement is essentially associated with the control of the achievement of organizational objectives and the implementation of the strategy. Performance measures are implicitly linked to the notion of diagnostic and control systems, or formal feedback systems used to control what the organization produces and to correct deviations from a predefined performance standard.
Financial information is associated with traditional planning and control cycles. In traditional management control systems, resources are totally focused on the management of accounting information. Financial measures express the results of decisions in a comparable unit of measurement. They summarize the arbitration cost between resources as well as the cost of unused capacities. Additionally, they are the measure for contractual relations and financial markets.
Traditional measurement systems encourage conservatism and a do-it-yourself attitude. Measures such as ROI (Return On Investment) discourage managers from innovating, investing in market share, or developing sources of competitive advantage. They encourage compliance. Moreover, the flexibility and creativity of strategic planning can be ruined by formal control systems.
Control systems create a climate that can act against the success of a strategic implementation and its formulation processes. Management control systems can promote or inhibit innovation depending on how they are defined. The construction of a management information and control system requires several decisions concerning the choice of information measured, omitted, and reported. A system that filters inconsistently promotes a fictional satisfaction and clarity that will confirm conventional reasoning. The perception of a manager is limited to the information available. The cybernetic vision's emphasis on financial information has led to errors in calculating production costs, to inadequate control of information, and to the absence of long-term performance measures. Information prepared for external use is inadequate and insufficient for internal use.
These models work well for the industrial age, but they are out of step with the talents and skills that companies are trying to develop. Several factors have been summarized that show the limit of the cybernetic process to respond to change:
- Lack of resources to obtain information in quantity and quality
- Institutionalization of past successes, which inhibits the perception of necessary transformations
- Degree of centralization and concentration of specialists
- Elite values
- Time taken by the hierarchy to find the correct answers and respond.
The limitations of the traditional cybernetic approach have been comparably studied with the following list:
- Too historical and "looking back"
- Lacks predictive ability to explain future performance
- The reward of behaviors is short-term or on incorrect terms
- Lack of operationality
- Incapable of sending signals for change early enough
- Too aggregated and summarized to be able to guide managerial action
- Reflects functional processes instead of cross-functional processes
- Gives inappropriate guidance for assessing intangible values
The Human Factor
Although the cybernetic model can be seen as a better version of the command and control model, with more space given to individual communication, adaptation, feedback, and autonomy, it doesn’t recognize how people cope differently with norms, stress, autonomy, authority, reporting, decision making, communication, and more. All those aspects relate to people’s style, preferences, values, motivation, behavior, emotions, or personality as we measure them with GRI’s adaptive profile. As we can evidence with the profiles, enforcing a system that’s fundamentally Low 2, High 4, on people who are not and exhibit opposite profiles, will create frustration and result in disengagement over time. The same limits came with the competency models that emerged at about the same period as cybernetics. Additionally, roles, including leadership and management roles, may considerably vary depending on situations (think about sales or client service versus accounting) and call for adaptations over time that may be beyond someone’s comfort zone and own unique capabilities to perform.