The power of artificial intelligence to analyze complex community feedback at scale
At a glance
GHD Digital helped the Region of Peel’s Waste Department understand the values, sentiment and views of their community members. Using data science, artificial intelligence (AI) and machine learning we transformed their behind-the-scenes public engagement practices by focusing on a critical element of engagement – reporting. With the ability to analyze complex, qualitative community feedback at scale, the Region of Peel was able to unlock a greater understanding of how the public felt about the proposed changes to their waste system.
The challenge
The Region of Peel provides services to 1.5 million people in Ontario, Canada. Like many municipalities around the world, their Waste Department was faced with a multi-tiered challenge. How might they incentivize waste reduction, manage the rising cost of waste management and develop a financial plan that would deliver a fiscally and environmentally sustainable solution for the Region and its residents?
To address these issues, in 2020 the Region embarked on a financial planning process to explore how they might bridge the gap between their current tax revenue and the funds required to cut landfill waste by 75 percent by 2034. Before they began, the Region recognized the importance of involving community members in their financial planning process, so that together, they could create a more sustainable community for the future.
Our response
Challenge 1: Getting residents and stakeholders meaningfully involved
The Region knew that community engagement on such a complex topic that impacted residents’ finances directly, would be a big challenge. A typical community survey would not suffice.
We worked hand in hand with the Region’s waste team to develop a robust, multi-phase engagement strategy. Together through in-person and online workshops, social media, and a robust Online Open House, we supported deep community dialogue about the challenges and opportunities that different funding scenarios might present, gathering and discussing thousands of community perspectives.
During the second phase of the engagement process, the Region received over 30,000 comments from over 10,000 members of the public, making it the most successful outreach effort by their department to date. The sheer volume of community feedback received is truly rare in the engagement field. This incredible response highlights the community’s deep involvement and interest in contributing to the solution, making this initiative a standout success.
Challenge 2: Using community feedback to inform decisions
Then came the second big challenge: determining how to handle all of the community data, use it effectively and derive meaningful insights that could directly inform the Region’s decisions.
A year before large language models like ChatGPT were available to the general public, our engagement specialists together with our advanced analytics team created an AI-driven solution that, for the first time, made it possible to analyze the quantity and complexity of this type of community data.
In phase 1, our team applied topic modeling and supervised learning to develop a fully customized digital system that explored the data. This was relatively simple sentiment analysis, with user responses being examined to understand what the public liked and disliked about the possible fee structures being explored, many of which would shift to a form of pay-for-what-you-generate payment for waste services. AI supported the existing human analysis process, articulating what community members valued in their waste system.
In phase 2, residents were presented with three scenarios to discuss, and that feedback would inform the Region’s decisions moving forward:
- Keep the original tax-based program
- Implement a user-fee system where residents pay for what they generate
- A combination of a tax-based system and a user-fee system.
The impact
The use of AI in reporting derived much richer insights than manual analytics. As one example, the results showed that while most residents preferred the existing tax-based model for paying for waste, they also recognized that this funding scenario did not incentivize waste reduction, a goal that was clearly articulated as part of the overall challenge.
Being able to decipher the unique insight across 30,000 public comments could not have been done without the assistance of AI.
This digital solution enabled the Region to meaningfully understand their community’s perspectives. Using AI to support engagement reporting, we had the opportunity to raise the bar on democratic process, enabling our decision-makers to better understand the people they served, with rich insights that were backed by data-driven, defensible results.
Engaging community members in the decisions that impact them is at the heart of democracy. We know that asking quality questions and creating opportunities for meaningful dialogue would result in better quality feedback. Transparency and openness to actively listening to community values, then using that feedback to inform decision-making, is what public engagement is all about. With the ability to harness AI to understand complex community feedback, our governments can make more informed decisions, in service of the residents they serve.
Contact us today and unlock the power of AI to help understand what your community values.
Collecting and analyzing data remains key for us, because it really gives us an indication of whether our decision was effective or if it needs to be modified. Being able to collect feedback from our residents and feel confident that it’s an accurate reflection of our community is paramount to us. This has set a new bar for us. It has raised our standards in terms of engagement practices.