A pathway from open stakeholder engagement to fair decision-making
I look around the world right now and, with my regulatorily-minded geek-shaded superglasses on, I see a great need for new, effective and resource-efficient way to “do” stakeholder engagement on which sound decisions can be made. If we can make it more focussed, fairer and efficient then we would be able to reasonably insist on stakeholder engagement being fully incorporated into the planning process.
Communities recognise that new developments and policies will bring change, and that the change is likely to have both positive (jobs, royalties) and negative (often social and environmental) consequences. My collaborators and I believe proponents can and should work together with regulators and communities to make decisions on whether proposals should be approved, reaching consensus decisions with both legal and social licence to operate.
The advantage of what we are tentatively calling the “Social Licence Assessment Pathway” to developers is that proposals which are approved through this route will be accurately understood and likely to be much better accepted by regulators and the community. Further, the proponent will gain full clarity over stakeholder concerns, and any approvals granted will include conditions which clearly spell out the regulator’s expectations with agreed performance measures.
It is appropriate that government regulators and all other stakeholders should understand the likely outcomes of a proposed change and be able to weigh them up according to the prevailing laws and policies to which the proposal is subjected. Emerging technologies enable the planning process to achieve social as well as regulatory licence through making the process transparent and by employing the best collaborative analytical tools and methods.
Collaborative decision support tools have been used with ever-improving success in a variety of resource-planning (https://www.ncbi.nlm.nih.gov/pubmed/26429362, https://www.udall.gov/OurPrograms/Institute/Institute.aspx) situations. I believe that the time has come for us to incorporate these approaches into the planning process for large, complex and particularly for contentious, resource-sharing or environment-changing projects.
I don’t have all the answers but some remarkable colleagues and I do have a vision of a truly collaborative and holistic planning process which harnesses the power of modern analytical techniques, collaborative software and the transparency of web-hosted information platforms. The following is an outline of how our suggested new paradigm for stakeholder engagement process might work, including some exciting new innovations (ad alert, techy promotions ahead) which can help to facilitate it.
Our big idea has a number of novel elements. The first of these is an independent information platform where important proposal data is held and analysis methodologies can be examined. By providing calibrated access to open-source data and open-script analysis tools, stakeholders can quickly confirm that the conceptual understandings make sense, identify the key risks from the proposal, the range of plausible outcomes, and what might drive the possible outcomes towards best and worst-case scenarios.
The second important innovation which would facilitate the Social Licence Pathway is the introduction of collaborative decision-support tools for deep and efficient stakeholder engagement. For this purpose, we are advocating the use of “management ﬂight simulators” as developed by my colleague Juan Castilla Rho [link to Groundwater Modelling with Stakeholders: Finding the Complexity that Matters, Vol. 55, No. 5–Groundwater–September-October 2017]. These “simulators” incorporate agent-based modelling (ABM) to enable workshop attendees, even remote ones, to see what happens to modelled prediction outcomes if various parameters or model elements are varied. They have been found to be an extremely powerful means for engaging and informing stakeholders about what parameters are important to understand and measure in relation to their particular concerns [weblink to Juan’s Chilean projects].
We propose to couple these technologies with an agreed team of independent expert intermediaries to design and implement a transparent impact modelling process using the best available technologies. This is the third and probably the most radical element of the Social Licence Assessment process. We envisage that this analytical group would be engaged by the regulator following competitive tendering and agreement for funding from the proponent. This independent analysis will facilitate clear and consistent decision-making by the regulators which can be understood and accepted by the proponent and the community.
We showcase below how these exciting technologies might feed into a suitable development assessment process, but in reality the process is not known until it has been lived. It will be a learning journey and will need to be modified as each trial project assessment traverses the Social Licence Planning Pathway. We are confident that the paradigm is feasible, but we do not underestimate the many complexities and difficulties which will be met as the trial implementation commences.
The government receives a proposal and decides that it is sufficiently important, controversial and suited to assessment through the Social Licence Pathway. An initial cost estimate for the process is made and funds are sought from the proponent and/or any other suitable source.
The community, represented by interested NGOs and appropriate representatives, sit down with the proponent, regulatory and advisory agencies and the nominated modelling team to decide on:
Terms of reference, scope of analysis (e.g. are cumulative impacts, global warming, socio-economics in or out of scope?)
What baseline data are critical and what are important to be collected and provided on an agreed data platform, accessible to all participants?
What are the key concerns that need to be addressed by the analysis?
What mitigations might reasonably be expected to be effective in containing environmental and/or social consequences?
The purpose of this initial exercise is primarily to consider what parameters will be most important to the analysis and to identify quantitative thresholds of “oh-oh” and “development failure”. Quantification of thresholds is difficult but is very powerful in this context because it allows modelling objectives to be tied to statistical certainty estimations, as advocated by modelling legends John Doherty and Catherine Moore (https://www.gns.cri.nz/Home/Our-Science/Environment-and-Materials/Groundwater/Research-Programmes/Smart-Aquifer-Models-for-Aquifer-Management-SAM/SAM-discussion-paper),agreed with stakeholders.
We suggest that this could be done efficiently through “management ﬂight simulators” as advocated by Juan Castilla Rho [weblink]. This technology has the capacity to make stakeholder engagement both more effectively and more rapidly identifying what matters to stakeholders, numerically.
An initial set of baseline data is fed by the proponent into the transparent data platform developed by the modelling team. One possible prototype for this is the open-source “geonode platform”, which is apparently a thing now. Examples of similar platforms in production include those developed by my other collaborator David Kennewell at Hydrata to manage groundwater in Nicaragua and Haiti.
At the same time, the modelling team considers the various inputs from Phase 2 and develops a Further Investigation and Analysis/Modelling Plan. This Plan includes “data worth” analyses to identify critical data points that will be needed to ensure that the analysis meets agreed certainty benchmarks. The plan is published on the platform and feedback is sought from proponent and stakeholders. This feedback is considered by the agencies and modelling team and the Plan is amended as appropriate.
A single or several set of agreed additional investigations are completed by the proponent, and the new datasets are fed into the Platform.
The modellers perform the prediction analyses in accordance with the Plan, periodically reporting on progress and consulting with proponents and stakeholders in a set forum and amending or extending analyses if required by the forum.
Modelling results are published, including clear statements about the levels of certainty and assumptions made during the modelling. A final phase of consultation is undertaken to confirm stakeholders’ interpretations of the modelling results.
Responsible agencies make their decision about the proposal, explaining how their decision was arrived at in light of the transparent modelling results.
If the authorities approve the proposed development, the agreed consequence thresholds used to guide the predictive modelling will be translated into approval conditions, and measured and reported in a way that can be progressively ingested and displayed on the information platform created during the assessment.