By Claude Joseph
The process of decision-making is by no means a clear-cut undertaking. There is no common ground among scholars on what should constitute the right method of policy-making. Some (such as Munger, 2000) propose an approach comprised of five main steps: 1) problem formulation, 2) selection of criteria, 3) comparison of alternatives and selection of the best policy, 4) consideration of political and organization constraints, and 5) implementation and evaluation of the program. This traditional framework known as the rational-comprehensive formulation of policymaking and inspired by the neoclassical economic paradigm has been a subject of a myriad of criticisms.
In his oft-cited article The Science of “Muddling Through,” Lindblom (1959) proposes a method of successive comparisons as opposed to the rational comprehensive framework. As he argues, the reason is simple. The comprehensive rational perspective assumes unbounded intellectual capacities along with sources of information that men are far from possessing. Moreover, when time and money, two factors deemed necessary to address policy problems, are limited, the best way of doing is “adjustment at the margin.” Inspired by Simon’s bounded rationality approach, Lindblom develops a framework known as incrementalism, the essence of which is that “policy does not move in leaps and bounds, democracies change their policies almost entirely through incremental adjustment” (p. 84).
This line of reasoning, however, does not go unchallenged. Etzioni, among others, criticizes the “muddling through” approach for being too conservative. Thus, his Mixed-Scanning is, he contends, a combination of the rationalistic method and the incrementalist perspective while avoiding of being neither utopian as the former nor conservative as the latter. Whether Etzioni has achieved the goal he set forth in this article is really debatable. Forester (1984), on the other hand, in Bounded Rationality and the Politics of Muddling Through, outlines a somewhat more realistic approach. To him, context matters. In fact in decision-making, context indeed matters.
This morning, I received an email from Thomas Jacob, a fellow Ph.D student in charge of organizing academic events and the like so students can get together once a month in order to share their works, ideas and so on. In his email, he says “If it’s not too much trouble, please shoot me a quick note with your class schedule. I’m going to combine them all in one place, to search for the optimal day/time to host our colloquia.” As it happens, in this specific context, it is highly likely for Tom to reach an optimal day/time because the number of students in this program is so small that a rational-comprehensive requirement can easily be met. If everyone shoots Tom a quick note with his/her class schedule, Tom, the decision-maker, will have complete and perfect information to undertake his operation.
However, should he aim at organizing an event to gather students from the whole school, the task would turn out to be very unlikely. Constraints would range from time-incompatibility among students to costs determination to organizational constrains, to mention just a few. This example, albeit not the most perfect one, conveys however the importance of context in decision-making. Therefore, the first task in decision-making is to take into account the context within which the decision will be made. As Forester (1984) shows, the context involves elements such as the setting, the problem (whether or not it is well-defined, and whether its scope, value dimensions, and chain of consequences are clearly delineated), information (perfect or imperfect), and the availability of time. Once one has a clear grasp of the context, the determination of the appropriate method – rational, incrementalism, mixed-scanning – of decision-making is feasible.
The process of decision-making is by no means a clear-cut undertaking. There is no common ground among scholars on what should constitute the right method of policy-making. Some (such as Munger, 2000) propose an approach comprised of five main steps: 1) problem formulation, 2) selection of criteria, 3) comparison of alternatives and selection of the best policy, 4) consideration of political and organization constraints, and 5) implementation and evaluation of the program. This traditional framework known as the rational-comprehensive formulation of policymaking and inspired by the neoclassical economic paradigm has been a subject of a myriad of criticisms.
In his oft-cited article The Science of “Muddling Through,” Lindblom (1959) proposes a method of successive comparisons as opposed to the rational comprehensive framework. As he argues, the reason is simple. The comprehensive rational perspective assumes unbounded intellectual capacities along with sources of information that men are far from possessing. Moreover, when time and money, two factors deemed necessary to address policy problems, are limited, the best way of doing is “adjustment at the margin.” Inspired by Simon’s bounded rationality approach, Lindblom develops a framework known as incrementalism, the essence of which is that “policy does not move in leaps and bounds, democracies change their policies almost entirely through incremental adjustment” (p. 84).
This line of reasoning, however, does not go unchallenged. Etzioni, among others, criticizes the “muddling through” approach for being too conservative. Thus, his Mixed-Scanning is, he contends, a combination of the rationalistic method and the incrementalist perspective while avoiding of being neither utopian as the former nor conservative as the latter. Whether Etzioni has achieved the goal he set forth in this article is really debatable. Forester (1984), on the other hand, in Bounded Rationality and the Politics of Muddling Through, outlines a somewhat more realistic approach. To him, context matters. In fact in decision-making, context indeed matters.
This morning, I received an email from Thomas Jacob, a fellow Ph.D student in charge of organizing academic events and the like so students can get together once a month in order to share their works, ideas and so on. In his email, he says “If it’s not too much trouble, please shoot me a quick note with your class schedule. I’m going to combine them all in one place, to search for the optimal day/time to host our colloquia.” As it happens, in this specific context, it is highly likely for Tom to reach an optimal day/time because the number of students in this program is so small that a rational-comprehensive requirement can easily be met. If everyone shoots Tom a quick note with his/her class schedule, Tom, the decision-maker, will have complete and perfect information to undertake his operation.
However, should he aim at organizing an event to gather students from the whole school, the task would turn out to be very unlikely. Constraints would range from time-incompatibility among students to costs determination to organizational constrains, to mention just a few. This example, albeit not the most perfect one, conveys however the importance of context in decision-making. Therefore, the first task in decision-making is to take into account the context within which the decision will be made. As Forester (1984) shows, the context involves elements such as the setting, the problem (whether or not it is well-defined, and whether its scope, value dimensions, and chain of consequences are clearly delineated), information (perfect or imperfect), and the availability of time. Once one has a clear grasp of the context, the determination of the appropriate method – rational, incrementalism, mixed-scanning – of decision-making is feasible.
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