In the last post we focussed on the gathering evidence and in this post we will discuss possible alternatives. Here are links to the articles of the different parts of the book:
Step I: Define the problem
Step II: Assemble some evidence
Step Three: Construct the alternatives
The word alternative lamentably is used with varying meaning. In the exclusive sense an alternative replaces a policy and they cannot be enacted at the same time where as in the inclusive sense an alternative can be applied in conjunction with the policy and potentially enhance the results. It is recommended to clearly state what kind of alternative is talked about.
In the early stages of a policy analysis Bardach recommends to comprehensively look for alternatives and analyse as many as possible and over time narrow it down to the most promising alternatives.
Alternatives can be gathered by “window-shopping” at political, institutional or private outlets that propose their policies. Another way to obtain alternatives is by designing them, however, more often than note a creative brainstorm will not produce a new world-changing idea that has not been proposed yet.
Casual models explaining the cause of problems can be useful to determine policies and intervention points but often a direct chain of causes cannot be constructed. The number of factor playing into a model is often obscure and can only be estimated making any model predictive at best. Nonetheless they offer great initial insights and therefore several common models are listed:
- Market Models: Disaggregated suppliers exchange goods/services with disaggregated demanders and the model is thought to reach equilibrium through exchange.
- Production Models: Identify parameters that make the production system (e.g. command-and-control regulation) vulnerable to breakdown, fraud, abuse, egregious diseconomies and the distortion of intended purpose. Another set of interesting parameters are those that induce the highest performance levels.
- Evolutionary Models: Essentially they represent a genetic algorithm that represent a common process of change over time. In the policy view it consists of “variation among competitors”, “selection” and “retention”. The first consists of the kind of problems that come up, the second of how problems are assessed and the last of how problems are understood by the detector.
Conceptualize and Simplify
The list of alternatives should not be overwhelming, so only a small set of well-thought alternative should be presented. An alternative should be presentable by a simple sentence or even a phrase. However, it should not be reduced to its summary and an extensive version should be available. Variants of alternatives should be considered as one for this purpose and only be looked at once an alternative is chosen.
If the alternatives consist of a continuum, it is usually worth so segment the continuum into distinct units to all for a low number of alternatives.
Design policy alternatives
When pre-existing alternatives are insufficient – e.g. in the case of exploiting new opportunities – policies need to be designed. The process differs from merely comparing alternatives in that
- it needs to be shown that the design fulfils the demands
- it needs to be shown that the design is consistent
- it might need to be adjusted to be realistic
- it often requires trial-and-error
A good way to getting a hold of the loftiness of policy designing is to set targets (e.g. 20% increase in public transport) and budgets (e.g. improve public transport with $20 million).
Look for design pattern in previous policy designs (even in different fields) to find useful approaches to your problem. However, consider scale and environment before reusing design patterns as they may hinder applicability.
To get a stable design – especially under trial-and-error – Bardach suggests a few starting point:
- The least flexible design element (e.g. budget)
- The most powerful design element (e.g. desincentivise car use to favour public transport
- The most robust design element (e.g. a subsystem of the design that could provided benefits without the whole policy being implemented)
- The most transitory, least costly, design element (e.g. intermittent solutions to cover a switch in underlying designs)
As a result of the fluency of the policy development it is necessary to regularly check the assumptions. A helpful tool are logic models(“Logic Model Development Guide,” 2004).
Usually, the design process can be grouped into two distinct tasks. First the system needs to be designed in a steady running state and second a transition towards that state needs to be designed.
It is useful to involve stakeholders as soon as possible to get feedback and find supporters and identify potential opponents and their reasons of opposition. However, if the design on the one hand is too rough potential stakeholders may not engage fearing early-mover vulnerability or may float their own ideas complicating the process. If the design on the other hand is to polished stakeholders may oppose simply for not being consulted. Bardach calls the appropriate moment rough-but-not-to-rough.