Leadership Competencies: Garbage Can Model

University / Undergraduate
Modified: 11th Feb 2020
Wordcount: 804 words

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There are two major decision making models. The garbage can decision making model is reality based, and intended to extend the understanding of organizational decision making by accentuating a time-based context (the situation at one point in time) and accepting chaos as reality. This is typical decision making in the emergency room of a hospital; the expertise of the medical team is vital. Rational (willful choice) decision-making models are a subset of reality-based models (Ledlow & Coppola, 2011). In an emergency room situation, willful choice principles are mentally checked off by physicians at roughly the speed of light.

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Choice is guided by four basic principles: (1) unambiguous (knowing which questions are relevant) awareness of another possibility; (2) likelihood and knowledge of significances; (3) a rational and reliable priority system for alternate ordering; and (4) heuristics or decision rules to choose an alternative (Ledlow & Coppola, 2011). After a decision is made using the garbage can decision method, rational choices are made regarding implementation.

The garbage can model is quite different from traditional decision-making models. It assumes that organizations are a long way from flawless and work in a condition of insurgency (without guidelines), where hierarchical inclinations and procedures are indistinct to the individuals from the association and policy makers in the association change frequently. The garbage can model assumes that no authoritative procedure for finding an answer for an issue exists and that decision makers are separated from issues and arrangements (Bugajenko, 2003).

Both willful choice and garbage can decision models are utilized in health organizations. The willful choice, or rational, model accepts that individuals in associations settle on choices considering reason, in a purposeful way, through an insightful and deliberate procedure that results in an ideal choice. It involves six sequential steps: 1. Identify the problem. 2. Collect data. 3. List all possible solutions. 4. Test possible solutions. 5. Select the best course of action. 6. Implement the solution based on the decision made (Ledlow & Coppola, 2011).

The garbage can, or reality-based, hypothesis accept that decisions are made on a messy and indiscriminate premise, like satisficing or “wading through”. In health care associations members in the decision-making process regularly have clashing viewpoints of the issue, have restricted time and assets to gather information, and are obliged to consider every conceivable solution by regulatory compliance requirements. In addition, time and money limits make it irrational to test all conceivable arrangements (“Problem Solving and Decision Making in Health Organizations,” n.d.) Use of both decision-making tools is vital in such instances as mental health, providing a greater range of important input in treatment decision making (Strauss, Lawless, & Sells, 2009). Overall, it is shown that in the medical industry, both willful choice and garbage can decision making models are instrumental in the successful delivery of healthcare.

References:

Bugajenko, O. (2003). The garbage can model of decision making. Retrieved January 31, 2017, from http://study.com/academy/lesson/the-garbage-can-model-of-decision-making.html

Ledlow, G. R., & Coppola, M. N. (2011). Leadership for Health Professionals: Theory, Skills and Applications (14th ed.). Retrieved from https://bookshelf.vitalsource.com/#/books/9781449626440/cfi/6/4!/4/2/14/8/26/2@0:0

Maister, D. (2001). Davidmaister.Com > garbage can decision making. Retrieved February 3, 2017, from David Maister Professional Business Professional Life, http://davidmaister.com/articles/garbage-can-decision-making/

Problem Solving and Decision Making in Health Organizations. Retrieved February 3, 2017, from Frates Health Care, file:///G:/HSM410/07ch_frates_health_care_1.pdf

Strauss, J., Lawless, M. S., & Sells, D. (2009). Becoming expert and understanding mental illness. Psychiatry, 72(3), 211-21. doi:https://search.proquest.com/docview/220676554?accountid=41759

 

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