By Jmaine
In “The Stages Approach to the Policy Process,” P. deLeon (1999) argues that despite the few shortcomings of the stages approach, it is still a useful tool for providing quality analytic information to government. However, in “Mixed-Scanning: A 'Third' Approach to Decision Making,” A. Etzioni (1967) argues that the shortcomings of the rationalistic approach as well as the incrementalist approach warrant a new way. Etizioni proposes the mixed-scanning approach, which straddles the borderline of the rationalistic and incrementalistic traditions.
One of the key architects of the stages model is H. Lasswell. The stages model represents Laswell's vision for policy science, providing quality analytic information to government so it can solve public challenges. To solve public challenges, the stages model offers decision makers a process of seven steps: 1) intelligence, 2) promotion, 3) prescription, 4) invocation, 5) application, 6) termination, 7) appraisal. A student of Laswell later refined the framework, offering the list of a) initiation, b) estimation, c) selection, d) implementation, e) evaluation, and f) termination.
The stages model has a few strengths. One form of strength is that it brought some conceptual depth that was lacking in the conventional approaches of economics and political science. Another form of strength is that it shifted policy research from a concentration on public administration and institutions to a new foundation for solving problems. A third form of strength is that it allowed for the inclusion of 'social norms and personal values' in decision-making, which was often not made visible in economics and political science.
The stages approach also has a few weaknesses. Some of the strongest criticism comes from P. Sabbatier. Sabbatier points out that a) the model cannot offer a causal explanation for policymaking, b) it does not lend itself to hypothesis testing, c) it is an inaccurate description of how policymaking actually works, d) it overlooks the dynamic of inter-governmental relationships, e) it is a very paternalistic approach, i.e. 'top down,' f) it does not offer the prospects to include learning in the stages or address the fact that policy analysis may take on various roles.
In the end, deLeon appears to be agnostic but thinks that the stages model offers the most systematic approach. We have some idea of the parts of the whole, even though we may not have a very solid understanding of how the system works. DeLeon says we can take guidance from J.M. Keynes who wrote that “it is better to be roughly right than precisely wrong.”
A. Etzioni takes a broader approach to assessing the strengths and weaknesses of the stages model. Etzioni describes three analytic approaches that underpin decision-making. One model is the rationalistic approach, which assumes that actors “have a high degree of control over decision making situations” (Etzioni, 1967). In this approach, the actor is alerted of a public challenge, drafts a goal, develops criteria that can be used to evaluate alternatives, looks at the costs and benefits of each alternative, and makes a decision. The second model is the incrementalist approach, also known as 'muddling through' because it assumes that decision makers do not have a tight control over the policy environment. In this approach, the model runs on a couple of inputs: a) zero in on policies that offer incremental change, b) restrict the universe of policy alternatives to a few in number, c) when considering a policy, pinpoint just a few consequences, d) rely heavily on mechanisms such as analysis and evaluation, e) promote remedial policies that are geared towards meeting challenges of today, not the future. The third model is the mixed-scanning approach, which is a blend of those previously described.
To show us the difference between the three approaches, Etzioni uses one policy example. Imagine that the government was charged with setting up a global system (i.e. satellites) that would capture weather patterns. The rationalistic approach would set up an “exhaustive survey of weather conditions by using cameras capable of detailed observations and scheduling reviews as much as possible.” The problem with this approach is that it would have a high price tag and overload the possibilities for action. The incrementalist approach would use past observations as a guide to scan areas that are worth paying attention to. The problem with this approach is that the scan will miss the new developments in areas not covered by the scan. Finally, the mixed-scanning approach would “employ two cameras; one that covers all parts of the sky; another to focus on areas revealed to require more in depth examination.” The advantage of this approach is that it is well positioned to pick up on new developments should they arise. According to Etzioni, mixed-scanning is a more realistic and effective strategy to foster decision making.
Both Etzioni and deLeon promote a certain vision of the stages model. One limitation that was overlooked is that it does not fit how policy changes are happening at the local, state level. For five years, I tracked state legislation in Minnesota. There, the state legislature is a 'citizen legislature,' meaning that they meet for only four months out of a year. Between the start and end date of the legislative session, they must resolve a number of complex public challenges. In my experience, there was only three times where actual behavior was aligned with the stages framework. 1) I did notice that policy was initiated by voters, coalitions, or key stakeholders. 2) I also noticed that implementation was conducted at the state agency level, mostly after interpreting the meaning of policy guidance from lawmakers. 3) The only type of estimation (or impact analysis) that was done was fiscal notes. However, these fiscal notes hardly ever accounted for broader impacts, such as demographics (gender, race/ethnicity, age) or economic standing (low income) or inequality (disparities in opportunity or outcomes)—even though they were major dynamics of policy challenges.
The evaluation of policy hardly ever happened. I saw only two during my tenure, one on minimum wage, another on welfare to work. My representative lawmaker called for more evaluations but would face resistance because they take up a lot of time and cost to prepare. Transparency and openess are important stages not mentioned in the framework, something that J. Stiglitz (1998) would like to see more of in the public sector. I saw a lot of 'Lone Ranger decision-making,' closed door meetings where policy was hashed out and passed without regard for broader input or quality analysis. Can we strengthen the stages model by integrating how decision-making on state and local policy actually works? Is there another model that can complement the stages model?
References
DeLeon, Peter. 1999. “The Stages Approach to the Policy Process: What Has It Done? Where Is It Going? In Paul Sabatier Ed. Theories of the Policy Process. Westview Press.
Etzioni, Amitai. 1967. “Mixed-Scanning: A Third Approach to Decision-Making.” Public Administration Review, 27(5).
Stiglitz, J. 1998. “The Private Uses of Public Interests: Incentives and Institutions.” Journal of Economic Perspectives, 12(2).
Comment
I'm still a bit perplexed by Etzioni's use of the camera metaphor in his mixed-scanning model. After all, the mixed scanning approach seems very similar to the way the human eye works: we take a broad scan of the situation, and then zero in on areas that require additional examination (niches that present an opportunity or a problem, show new data or development, etc). We look at the entire mango tree, and zoom in on the ripest fruit on the most accessible branch. Just like Etzioni's qualifier, Managers zero in on areas requiring "higher level" attention (should the mango tree be pruned to encourage lower-hanging growth in the long term?), while workers focus on areas presenting problems to their specialty (How can I get all six of those mangos down without snapping that branch?). Opportunities for fundamental and incremental decisions can be seen with the human eye.
I wonder if this was an attempt to avoid references to biomimicry or evolutionary theory on Etzioni's part. Or, perhaps he intended to distance his metaphor from the human brain for more strategic purposes, if he did not intend to discuss the implication of serial or parallel attention span on the application of the camera's findings.
In “The Stages Approach to the Policy Process,” P. deLeon (1999) argues that despite the few shortcomings of the stages approach, it is still a useful tool for providing quality analytic information to government. However, in “Mixed-Scanning: A 'Third' Approach to Decision Making,” A. Etzioni (1967) argues that the shortcomings of the rationalistic approach as well as the incrementalist approach warrant a new way. Etizioni proposes the mixed-scanning approach, which straddles the borderline of the rationalistic and incrementalistic traditions.
One of the key architects of the stages model is H. Lasswell. The stages model represents Laswell's vision for policy science, providing quality analytic information to government so it can solve public challenges. To solve public challenges, the stages model offers decision makers a process of seven steps: 1) intelligence, 2) promotion, 3) prescription, 4) invocation, 5) application, 6) termination, 7) appraisal. A student of Laswell later refined the framework, offering the list of a) initiation, b) estimation, c) selection, d) implementation, e) evaluation, and f) termination.
The stages model has a few strengths. One form of strength is that it brought some conceptual depth that was lacking in the conventional approaches of economics and political science. Another form of strength is that it shifted policy research from a concentration on public administration and institutions to a new foundation for solving problems. A third form of strength is that it allowed for the inclusion of 'social norms and personal values' in decision-making, which was often not made visible in economics and political science.
The stages approach also has a few weaknesses. Some of the strongest criticism comes from P. Sabbatier. Sabbatier points out that a) the model cannot offer a causal explanation for policymaking, b) it does not lend itself to hypothesis testing, c) it is an inaccurate description of how policymaking actually works, d) it overlooks the dynamic of inter-governmental relationships, e) it is a very paternalistic approach, i.e. 'top down,' f) it does not offer the prospects to include learning in the stages or address the fact that policy analysis may take on various roles.
In the end, deLeon appears to be agnostic but thinks that the stages model offers the most systematic approach. We have some idea of the parts of the whole, even though we may not have a very solid understanding of how the system works. DeLeon says we can take guidance from J.M. Keynes who wrote that “it is better to be roughly right than precisely wrong.”
A. Etzioni takes a broader approach to assessing the strengths and weaknesses of the stages model. Etzioni describes three analytic approaches that underpin decision-making. One model is the rationalistic approach, which assumes that actors “have a high degree of control over decision making situations” (Etzioni, 1967). In this approach, the actor is alerted of a public challenge, drafts a goal, develops criteria that can be used to evaluate alternatives, looks at the costs and benefits of each alternative, and makes a decision. The second model is the incrementalist approach, also known as 'muddling through' because it assumes that decision makers do not have a tight control over the policy environment. In this approach, the model runs on a couple of inputs: a) zero in on policies that offer incremental change, b) restrict the universe of policy alternatives to a few in number, c) when considering a policy, pinpoint just a few consequences, d) rely heavily on mechanisms such as analysis and evaluation, e) promote remedial policies that are geared towards meeting challenges of today, not the future. The third model is the mixed-scanning approach, which is a blend of those previously described.
To show us the difference between the three approaches, Etzioni uses one policy example. Imagine that the government was charged with setting up a global system (i.e. satellites) that would capture weather patterns. The rationalistic approach would set up an “exhaustive survey of weather conditions by using cameras capable of detailed observations and scheduling reviews as much as possible.” The problem with this approach is that it would have a high price tag and overload the possibilities for action. The incrementalist approach would use past observations as a guide to scan areas that are worth paying attention to. The problem with this approach is that the scan will miss the new developments in areas not covered by the scan. Finally, the mixed-scanning approach would “employ two cameras; one that covers all parts of the sky; another to focus on areas revealed to require more in depth examination.” The advantage of this approach is that it is well positioned to pick up on new developments should they arise. According to Etzioni, mixed-scanning is a more realistic and effective strategy to foster decision making.
Both Etzioni and deLeon promote a certain vision of the stages model. One limitation that was overlooked is that it does not fit how policy changes are happening at the local, state level. For five years, I tracked state legislation in Minnesota. There, the state legislature is a 'citizen legislature,' meaning that they meet for only four months out of a year. Between the start and end date of the legislative session, they must resolve a number of complex public challenges. In my experience, there was only three times where actual behavior was aligned with the stages framework. 1) I did notice that policy was initiated by voters, coalitions, or key stakeholders. 2) I also noticed that implementation was conducted at the state agency level, mostly after interpreting the meaning of policy guidance from lawmakers. 3) The only type of estimation (or impact analysis) that was done was fiscal notes. However, these fiscal notes hardly ever accounted for broader impacts, such as demographics (gender, race/ethnicity, age) or economic standing (low income) or inequality (disparities in opportunity or outcomes)—even though they were major dynamics of policy challenges.
The evaluation of policy hardly ever happened. I saw only two during my tenure, one on minimum wage, another on welfare to work. My representative lawmaker called for more evaluations but would face resistance because they take up a lot of time and cost to prepare. Transparency and openess are important stages not mentioned in the framework, something that J. Stiglitz (1998) would like to see more of in the public sector. I saw a lot of 'Lone Ranger decision-making,' closed door meetings where policy was hashed out and passed without regard for broader input or quality analysis. Can we strengthen the stages model by integrating how decision-making on state and local policy actually works? Is there another model that can complement the stages model?
References
DeLeon, Peter. 1999. “The Stages Approach to the Policy Process: What Has It Done? Where Is It Going? In Paul Sabatier Ed. Theories of the Policy Process. Westview Press.
Etzioni, Amitai. 1967. “Mixed-Scanning: A Third Approach to Decision-Making.” Public Administration Review, 27(5).
Stiglitz, J. 1998. “The Private Uses of Public Interests: Incentives and Institutions.” Journal of Economic Perspectives, 12(2).
Comment
I'm still a bit perplexed by Etzioni's use of the camera metaphor in his mixed-scanning model. After all, the mixed scanning approach seems very similar to the way the human eye works: we take a broad scan of the situation, and then zero in on areas that require additional examination (niches that present an opportunity or a problem, show new data or development, etc). We look at the entire mango tree, and zoom in on the ripest fruit on the most accessible branch. Just like Etzioni's qualifier, Managers zero in on areas requiring "higher level" attention (should the mango tree be pruned to encourage lower-hanging growth in the long term?), while workers focus on areas presenting problems to their specialty (How can I get all six of those mangos down without snapping that branch?). Opportunities for fundamental and incremental decisions can be seen with the human eye.
I wonder if this was an attempt to avoid references to biomimicry or evolutionary theory on Etzioni's part. Or, perhaps he intended to distance his metaphor from the human brain for more strategic purposes, if he did not intend to discuss the implication of serial or parallel attention span on the application of the camera's findings.
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