Engaged Constituencies and 2 more...less...

Robust & Accessible Information

Nested Watershed Governance

Average level of agreement (1 to 10) among selected water decision makers with the statement “In general, when faced with a decision related to water-resource management, I am able to obtain information of sufficient quality to make a sound decision"

6.12019

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Story Behind the Curve

What are the stories that help us understand why there is not more access to the water data needed for decision makers to make informed decisions? OLW Network members who work on this impact measure shared the causes they believe are at work, both negatively and positively, with respect to this question. To note, OLW Network members also believed that in some cases decision makers did have access to data, but that doesn't mean that they would always use it. These are the themes that emerged from their stories:

 

  • The need for a ‘smoking gun’: When data obviously points to a major problem - a critical risk - then it tends to be used, but this is rarely the case. When data doesn’t point to an obvious problem, it is often ignored.
    • Although… Sometimes available data doesn’t motivate change: Some data that shows a critical risk - if there is no public response - just isn’t motivating enough to be used to inform decisions. Wait, nobody is saying anything? Let’s not worry then.
    • The difficulty of cumulative impact assessment: data needs to be used in a way that the cumulative impacts of decisions are considered. But, this science is catching up to our needs. The cumulative impacts may indeed show a ‘smoking gun’, but it isn't always being used that way.
  • Government commitment to use data can be lacking: Many provincial & territorial governments aren’t committed to open data and using data. BUT - the more data use becomes popularized and becomes the norm, the more it will spread.
  • Inaccessible data: For data that does exist, it is often hard to access (or in a format that can’t be accessed). There is a lack of open access data hubs to gather the data so it can be easily found.
  • Data gaps: There are many data gaps regarding water data.
  • Public trust in data and science: decision makers can follow public perception, and there seems to be an erosion in the trust of science and maybe even scientists from the public (compared to the past), which may disincentivize decision makers to use it.
    • This may also be due to complex data or science being communicated in a way people don’t understand
  • Decision makers not seeing citizen demand for data use: the public doesn’t demand bureaucrats use data all the time. When they demand it, the response can often come.
  • Use of traditional knowledge: Indigenous communities want to see the available traditional knowledge being used and considered as a baseline, but most often it is not used or considered beside 'western science'.
  • Decision makers need ‘permission’ or need to be mandated to use data: Many decision makers have access to date, but just don’t use it. This is especially true of community based monitoring data. It seems they need explicit permission or even a ‘mandate from above’ to use it.
  • Water objectives just don’t drive decisions: Canada has a perception of being water wealthy, so making decisions based on how they will impact water objectives isn’t something decision makers are used to.
  • Political decisions can incentivize governments to ignore data: When monitoring programs are not designed to answer they policy question at hand, staff can say, well ‘that’s not applicable’ and ignore data even if it is relevant.
    • Data is used when it’s needed to politically motivate change: On the other hand, when convenient, data can be used to get the public behind a change.
  • Accessible data can be a liability for governments: A concern governments have is what if people see there’s a problem… Perhaps this is because there is a lack of resources or will to make change if a problem is seen? There seems to be an instinct to reduce the ways that data can be used to hold government staff accountable.
Partners

Who are the partners that can support us in doing better against this impact measure? The following are many of the partners who have a role to play (although the list is not exhaustive):

Academia; Government decision-makers at all levels; the public; Transboundary bodies; Outdoor educators; Stewardship groups; Government Scientists; Industries (can industry “lead” government in using data to do things better?); Agricultural associations; Schools & 4-H & Guides, Brownies, etc (children can be very influential); First Nations and Metis leaders; Watershed Councils; Granting Networks and Grantors; Consulting companies that work for government and other clients who are making decisions at various levels that affect water; The media (independent & mainstream); Artists.

Ranking the Actions

Based on the stories behind the curve and the partners who have a role in supporting us doing better, a number of potential actions were brainstormed that could turn the curve on this impact measure. Threse actions were ranked based on two criteria:

  1. Leverage (L): This is the most important criterion. How much difference will the action make on our impact measure? Will this actually help turn the curve? E.g. handing out pamphlets at a community event isn’t necessarily a bad idea, but it's probably low leverage.
  2. Reach (R): That is, “is it within our reach”? Is it feasible and affordable? Can it actually be done and when? No-cost / low-cost actions rank highly here. Action that require new significant resources rank lower. Is there a clear lead person (higher), or does nobody want to take it on (lower)?

The top two actions brainstormed are as follows:

1) Developing auto-responses to trigger thresholds

  • Developing monitoring frameworks - before the 'crisis' hits - that establish thresholds in the data that, once passed, trigger pre-determined management responses.
    • Easier to talk about what you will do before the crisis hits- e.g. if pH drops to X will will do Y action. 
    • These triggers should be set in a co-developed manner
  • Work with scientists to validate the use of specific parameters as ‘triggers’, and translate into plain language for citizens to understand why it’s a trigger.
  • Considerations: How do we share or validate a ‘trigger’ being hit? For example, faulty equipment, etc. If it’s in real time (which is ideal) how do we ensure no one panics, over-reacts or just don’t care at all (ensuring appropriate responses)
  • Promote an adaptive management approach to freshwater stewardship - an iterative cycle of decision-making, monitoring and adjustment/improvement

2) Telling data’s story

  • Animate the data for the public so they can hold decision-makers accountable while animating the data for decision-makers.  
  • Develop social media narrative campaigns to tell data stories and tag decision-makers in posts.
  • Choose a number of regions that have good data and can tell a good story. 
  • Considerations:
    • The Elephant and the Rider” (target the emotional aspects of the data story vs the intellectual aspects for greater effect). 
    • Keep it simple.
    • Explaining concepts in ‘plain-language’ and finding connections to their personal lives
    • We tell people about this, but what do we ask people to do?
Strategy

While the group brainstormed the top two actions, there still needs to be commitment to implementing one of these projects. To that end, potential steps were determined for each of the two actions, as outlined here:

1) Developing auto-responses to trigger thresholds

  •  Find and develop case studies to draw upon as examples
  • This is a smaller step we can take to kick-start the process, noting that it cannot end here- we must get to the next step
  • Consideration: ideally, the case study highlights a scenario where many people can see themselves in rather than a really regionalized issue.
  • Determine the location and issue where we can advocate for this successfully.
  • Some factors that would contribute to a more ideal location and issue:
  • A location where there is data, a clear issue, and a receptive government partner
  • An issue where there is some academic literature, or other legitimizing source, that supports specific triggers 

2) Telling data’s story

  • The story needs to be told with two audiences in mind: 1) decision makers and government, and 2) the public
  • For decision makers and government
    • Supporting decision makers, and elected leaders to understand the data and where it can be obtained.
  • Public outreach
    • Outreach in a way so that as much as possible, the public who are interested can be involved in the decions being made, and understand the data behind the decisons
    • Where possible, tell the positive stories as well; where gov’t has used data to inform decisions and it was good and highlight the success.
  • For each story (for both audiences), promote the call(s) to action to increase people's participation and experiences supporting decision making that impacts them.
Scorecard Result Container Indicator Measure Action Actual Value Target Value Tag S R I P PM A m/d/yy m/d/yyyy