The Policy Compass methodology (reflected in detail in the submitted in April Policy Compass deliverable “D1.2: Policy Compass Methodology and High level user Requirements” – available in the “Deliverables” section of the project’s website) constitutes the first of the core parts of the whole Policy Compass idea and approach.
Policy Compass aims to follow a specific approach in order to cover the maximum set of end users’ needs and possible requests, in a user friendly and comprehensible way. In the following lines the complete process behind the use of Policy Compass is described summarily, without though excluding any of the important parts.
The overall Policy Compass methodology is built around 3 interrelated pillars depicted in the following figure and described below:
Figure 1: Policy Compass Methodology Pillars
- Evaluating Performance of Policies (EPP): Motivated by their desire to actually check/verify that a specific policy action, policy directive law etc. has either actually achieved, or failed to achieve the initially met targets and KPIs (or simply aiming to verify that what politicians and public servants claim as actual results), citizens seek for data confirming the understanding they have. Seeking for relevant data and metrics is the first logical step, while casual models that would verify their assumptions in a more scientific way is an even better scenario. In the same time, making connections between facts and specific actions in a visualised manner is more vivid and user friendly than simple text and mathematics. Thus, besides giving the user the ability to engage himself/herself in a formal and scientific procedure, Policy Compass will also offer visualisation capabilities. And, having achieved the initial idea, sharing the findings with the community is the final step of the process; Policy Compass will also support disseminating the results of the procedure through popular social channels.
- Building Causal Policy Models (BCPM): Relevant to the previous step, a more advanced user might not be satisfied with simply utilising existing casual and simulation models to verify and/or explain his/her findings. Having collected the necessary data, a user with the relevant background can build a new (or ameliorate an existing) casual model. Turning this model in a more user friendly and easily comprehensible form, i.e. a Fuzzy Cognitive Map, can act as a catalyst for better verification and understanding of the newly developed model. Running simulation through the aforementioned model, in order for example to predict future impacts, is the next logical step, also supported by Policy Compass. And, similar to the previous step, disseminating the findings is also wished for and supported.
- Online Deliberation And Argument Mapping (ODAM): Online deliberation can act as a catalyst both a priori and a posteriori of the two previous steps; online discussions can offer valuable input to anyone looking for data relevant to his/her interests (a priori offering) while, in the same time, interlocutors can be engaged for discussing, criticising and verifying the resulting findings. However, non-structured deliberation is not always of actual value. A way to structure new or even existing deliberations should be offered, in order to facilitate easy and effective navigation through the discussions and conclusions’ extraction. This is what Policy Compass will offer through online argument mapping.
The Policy Compass methodology is not strictly structured and static; on the contrary, it constitutes a highly dynamic approach, letting the user follow parts of the integrated workflow in the order he/she wishes. The integrated approach can be found in the following figure:
Figure 2: Interrelations between Policy Compass Main Components