When it comes to policy-making, quantification is a necessary device to discipline the field in terms of providing empirical evidence in a systematic manner to overcome existing prejudices arising due to various ideologies within a related field. By defining the questions and concepts of a particular policy field, not only can a comparison be made among alternatives, but also trade-offs so that precision instead of speculation can prevail. By setting the standards for how to weight costs, benefits and values, a framework can be built for establishing clear evidence. On the other hand, expecting accountability and good governance due to the mere use of quantification would also be futile as quantification is not always perfect on its own.
Based on Stokey & Zeckhauser’s essential policy book “A Primer for Policy Analysis” (1978), the following framework of policy analysis would be familiar to many policy-developers:
- A problem that needs to be resolved is identified.
- Possible courses of action to resolve the issue are listed.
- Potential consequences of actions are analyzed via means of quantitative analysis (data analysis, program evaluation).
- A valuation by means of assigning monetary quantities to individual values (referred to as ‘willingness to pay) is undertaken so that a cost-benefit analysis can be completed.
- A final decision is made based on the existing alternatives.
According to this linear framework, quantification acts as a tool in the sense that it tries to fulfill a social objective subject to some politics based on a policy choice. This type of quantification is based on various measures and scores. Rather than shaping the solution itself, it merely selects the best choice for the aims of public policy which have been defined by others. In other words, it acts similar to a tool for doing calculus in the field of policy-development.
Rather than viewing the world of policy as being bi-polar made up of tools and aims, we should adopt a more holistic approach as policy aims and quantification are often intertwined. There is a mutual co-shaping of policy aims and tools as what and how a policy is quantified often times shapes its aims and vice versa even though policy-makers may not be aware of this mutual process.
One of the commonly held assumptions on quantification is that it should be objective and independent from policy aims which might offer the following drawbacks unintentionally:
- The incentives of policy-makers and implementers might be distorted.
- Normative standards regarding policy evaluation might be flattened.
- The range of policy issues acknowledged to be addressed or to exist might be constrained.
Quantitative policy is grounded within welfarism, according to which a policy evaluation should be made based on its implications for the common human well-being. This well-being relates to an utilitarian approach as it defines well-being from a material cost and benefit perspective given the easiness to measure the willingness to pay in such a method. This is not to say that normative standards cannot be shaped by other moral perspectives such as consequentialist ones with a focus on results or deontological ones with a focus on rights and responsibilities.
Being devoted to taking sound policy decisions means being committed to quantification. A value can be assigned to a variety of intangible elements ranging from rights to duties so that different equity considerations can also be introduced into the process of policy evaluation. To give a specific example, once the quantification process of all the effects is completed, the best policy can be specified by finding out the one which maximizes total utility given the limitation that the difference between individual utilities should not exceed a specific percentage.
While it might be difficult to measure the value of rights and responsibilities or take into account various equity aspects, tangible costs and benefits could be quantified much easier from both a practical and conceptual perspective. Such a way of thinking has also become a part of applied economic thinking regarding the quantitative policy analysis. It would be unreflective to aim at maximizing net utility without taking into account aspects of responsibilities or equity. Doing so would simply mean taking for granted that a good policy can simply be defined as the one that optimizes tangible benefits.
The linear model of doing policy analysis can be misleading. As Foucault used to say, utilitarianism is no longer a philosophy as it is seen as a “technology of government”. In a similar vein, policy developers do not use quantification because of being utilitarian. The reverse holds true; because of being utilitarian they quantify.
Although the method of quantification sheds light on various policy issues, still solutions for policy problem might be sought after in the wrong places if policy-developers insist on using quantification for those issues which remain in the dark due to expensive or tough quantification. So, rather than approaching quantification as a panacea for all policy issues, a critical mindset should be adopted.
Non-surprisingly, one of the most influential fields for policy has been the field of economics, which has quantification engrained into its existing methodologies. Being inspired by economy scientists, policy developers should not be too eager to adopt quantification methodologies without adopting a reflective mindset and weighing both its pros and cons. The process of both reform and reflection should be defended when it comes to the importance of quantification in policy discourse.