A key objective of the PoliRural project is to explore the use of innovative tools applied to Regional Foresight. The expectation is that the use of tools based on Text Mining should lead to productivity gains for the local teams that lead and facilitate Foresight initiatives, whereas tools based on the use of System Dynamic Modelling can help stakeholders understand and select optimal policy mixes for implementation.
This article summarizes the work done to test the Policy Options Explorer or POE and provide a foundation for the work needed to make it into a generally accessible tool for use by non-experts. It can be read in conjunction with an article published in Newsletter No. 10, which introduced the subject of System Dynamic Modelling and described “Progress so Far in the Application of SDM to Regional Foresight.” It can also be read in conjunction with an article published in Newsletter No. 12 entitled “A Second Set of Experiments for Exploring the Application of SDM to Regional Foresight” in which we developed and tested a special case of the POE, where the only indicator of performance was a composite index of rural attractiveness, with a view to exploring different visualisation techniques enabling non -expert users to more easily explore highly complex issues such as different connects of “rural attractiveness.”
The POE tool is based on a comprehensive model of rural regions, comprising 8 modules, containing almost 300 parameters. The POE tool consist of three layers. The bottom layer is based on a small set of ‘input’ parameters, whose different values represent different policy choices. The top layer is based on a limited set of ‘output’ parameters whose values represent the performance of the region. The middle -layer contains all of the other parameters of the model and is essentially treated as a black box. In this way the user is shielded from most of the complexity of the model and can focus on the specific issue it intends to explore. To explore the impact of different policy scenarios on their region, each user selects sets of input parameters which correspond to the different policy scenarios and runs the model to see how these choices are reflected in changes to the output parameters.
With assistance from 22SISTEMA, the regions taking part in the project developed their own regionally adapted POE, based on regional specific data, and reflecting the policy issues they wanted to explore. After the design phase of work, each region elaborated a ‘Statement of Expectations’ which laid out what they hoped to achieve from using the model, along with a “Design of Experiment” document in which they explained how they intended to test their POE. They were then asked to test the use of their POE, following the experimental methodology they had designed, providing detailed feedback on their efforts, and commentary on how closely the tool fulfilled the initial expectations. The feedback from all regions was analysed by CKA. This analysis includes feedback on the models themselves, the user experience and tools provide to use the models, the challenge of obtaining data with which to populate the models, the extent which they appear to represent reality, and the value they provided in the context of the local Foresight exercise, as an aid to understanding complex regional dynamics, and as a tool to support the selection of appropriate policy mixes intended to realise the future vision for each region. These results are very encouraging and our fundings are described in detail in a document entitled “Results of the POE Trials,” available here. This should be read in conjunction with D5.5, available here, for clear ideas of what now needs to be done to achieve a significant breakthrough in the large-scale application of SDM to the exploration of policy options in the context of regional Foresight.
