From Vision to Practice

When it comes to sustainability, social responsibility, and impact investing, they sometimes feel like ambitious ideas to me. Can these visions really be put into practice? What challenges might arise along the way? Is the project financially feasible, and what would be the optimal capital structure?

This semester, I get the opportunity to step into a real-world sustainable project and to explore from the inside how these questions can be answered.

Our client is an organization based in Brazil, focusing on sustainable development of the Brazilian Amazon Forest and aiming to improve local community life while sheltering biodiversity in Amazon. Currently, the client company is working on a project on local timber supply chain, which has been blocked into 3 main parts, lumber production and management, timer production and social housing. The residuals appear more dispersed at lower fitted values and more concentrated at higher fitted values. This suggests that the variance of the residuals is not constant across levels of the predicted values, indicating possible heteroskedasticity. All of which can empower local community, for example, job creation and housing improvement. However, to better carry out this project, the client needs to know the feasibility of the project, how much funding it exactly requires, what will be the best capital structure of it and to what extent can it bring social impact.  

Given this context, my team and I are going to use available real-world data and well-documented estimates to analyze the feasibility and potential upside for this timber supply chain project, finding all the answers to the questions above. 

Different from other projects, the team worked on the same project in the prior semester, but from a different angle. They focused on the social, environmental and financial KPIs and supply chain analysis part. Though relatively qualitative, their outcome provided us valuable background and guidance.

I have been on the traditional finance side before entering SIPA, which I once thought would be my future career pathway. But SIPA, especially SIRI, provides me the platform to learn about sustainability and understand how investment can generate social impact.

So, I was attracted to this project the moment I saw it. I viewed it as a perfect combination of my equipped skillsets (financial analysis and modeling) and my growing interest in impact investing. On top of that, nothing could be better than a real-world case.

Our team comes from diverse backgrounds. Some may feel more confident about finance and data analytics; some have more expertise in forestry and ecosystems. But together, we are all passionate about sustainability and social impact and hope to contribute not only to the project but also to the real Amazon Forest.

To get a more detailed and comprehensive understanding about the project, we have met with the client 2 times so far, discussing the changes since last semester and aligning our goals. The client also spent time on illustrating the overall condition and complexities of the Brazilian Amazon Forest to ensure our team understand the goal of this project. Meanwhile, the client also mentioned some potential challenges, including data access and finding benchmarks.

As mentioned before, our team has to base on the previous team’s outcome, so we reached out to them to learn how they selected the KPIs, how they made the assumptions and what resources they found are of great help. Their insights helped us avoid starting from scratch and allowed us to refine our approach more efficiently.

Neither carrying out a project nor building a financial model is easy, let alone for a sustainable one located in Amazon Forest.

On the modeling side, our team and the client spent hours reviewing the model’s core inputs. As some data can be hard to get, for example the erosion of wood and the price for green lumber, we agreed on which assumptions could be simplified at this stage.  Additionally, as a sustainable project, we discussed how to translate the qualitative social impacts into quantitative ones and incorporate them into our model. Balancing financial returns with social outcomes is one of the most challenging but also most meaningful aspects of this work.

There are also foreseeable difficulties on the application side, including the transportation of lumber, the potential concerns from indigenous communities, and the affordability and preference of targeted residents. The client mentioned since reliable benchmarks are limited, we may need to wait for field survey reports from other stakeholders before refining certain assumptions.

However, identifying these challenges has helped clarify our thinking. Once we outlined the uncertainties and risks, our next steps became much clearer. We assigned first-stage tasks to each team member, focusing on collecting data for the base model, while preparing to update our assumptions once third-party reports become available.

The client has shared a visual blueprint of the project: stilted houses by the riverbank with basic utilities. The design preserves residents’ traditional living patterns while improving safety, stability, and overall living conditions. Seeing this vision made the project feel tangible. The idea of improving daily life for local residents while protecting the forest continues to motivate me. I hope that not only will our analysis be successful, but that the project itself can eventually be implemented and bring meaningful social impact to communities in the Amazon.