Harnessing Eigenvector Centrality for Climate Impact

At Cool Climate Collective, I always say we are more than just Collective Capital, but our true strength to portfolio companies and the overall climate ecosystem is the combination of Collective Capital, Knowledge and Network.

So I get questions on what the network means (since it sounds fluffy, and everyone claims to be value-add in the VC space). So to better quantify the approach I’ve been applying since our initial start, I’ve been working on an approach to catalyze climate tech advancements by applying the principles of eigenvector centrality—a network theory concept commonly used in social network analysis.

By recognizing the power of indirect connections, we tap into the inherent strength of our network to identify and amplify influential nodes within the climate tech ecosystem.

Understanding Eigenvector Centrality in Context

Eigenvector centrality is predicated on the notion that a node’s importance is increased not only by the number of its direct connections but significantly by the prominence of those connected nodes. In a sense, it’s not just who you know; it’s who they know.

In Cool Climate’s network, these nodes represent our diverse co-investors and subject matter experts. Their value isn’t solely in their direct interactions with us or their immediate contributions. Instead, it’s their position within a broader, interconnected web of influential figures, organizations, and entities in the climate tech domain.

Tapping into Network Strength

When we consider adding a new startup to our portfolio, we look beyond the surface. We delve into the eigenvector centrality of our collective network—identifying key players who, by virtue of their connections, can unlock disproportionate value and facilitate the adoption and scaling of climate tech solutions.

This approach enables us to:

1. Identify Influencers: By analyzing our network, we pinpoint those individuals and organizations with high eigenvector scores—those with robust connections to other influential entities.

2. Strategic Introductions: We don’t just introduce our portfolio companies to anyone. We strategically connect them to these high-eigenvector-centrality nodes to expedite market penetration and scaling.

3. Leverage Indirect Influence: Often, it’s the second or third-degree connections that yield the most opportunity. We leverage the strength of our network’s fabric to gain access to resources, insights, and opportunities that might otherwise remain inaccessible.

Mobilizing Co-Investors and Domain Experts

Our co-investors are not passive players; they are active nodes within our network whose connections are as vital as their capital. We encourage a network-centric view of investment, where each co-investor’s network can be mobilized to support portfolio companies.

Similarly, our domain experts are more than advisors. They’re central nodes that bring with them webs of technical knowledge, industry insights, and influential connections. Their participation in Cool Climate acts as a force multiplier for our mission.

The Collective’s Strength

In leveraging eigenvector centrality, we turn our network into a dynamic, self-reinforcing entity where the success of each node contributes to the collective’s might. The power lies not in the size of the network but in the strength of its connections. In a world facing pressing climate challenges, our eigenvector-focused strategy doesn’t just add value to our portfolio companies; it amplifies the impact they have on the world.

By harnessing the power of eigenvector centrality, Cool Climate Collective operates at the nexus of innovation and influence, accelerating the deployment of climate tech solutions that are essential for a sustainable future. This is network theory in action, not just for academic interest but for tangible, planetary benefit.

When I get around to it, I’ll share more on the inner workings of how we run our Investment Committees in a hybrid sync/async manner and utilizing our internal CRM for matching ‘best fit’ to business model & investor-founder.

How does it work? (The Formula)

Where:

  • CCCImpact​ is the overall impact of the Cool Climate Collective’s network.
  • D stands for Dunbar’s number, which normalizes the network’s scale to the cognitive limit of meaningful relationships.
  • represents the sum across all nodes (i.e., individuals, startups, investors) in the network.
  • EVi​ is the eigenvector centrality of node i, indicating the influence of a node within the network. EVi​ helps identify influential nodes that can act as hubs or connectors within the network, facilitating the spread of innovations and ideas.
  • CVi​ is the climate value of node i, indicating the node’s potential impact on climate solutions.
  • PMi​ is the portfolio multiplier for node i, representing the synergistic effect that the node has when combined with others in the portfolio. A higher PMi​ indicates that the node not only contributes individually but also amplifies the contributions of others. PMi​ introduces the concept of collaborative advantage, encouraging the selection of ventures that not only promise individual success but can also contribute to a stronger ecosystem through collaboration and synergy.
  • Si​ is the support factor for node i, reflecting the qualitative and quantitative support that CCC provides to the node, which could include financial investment, strategic guidance, or access to the CCC network. This factor can be strengthened through targeted actions to fill network gaps. Si provides a feedback loop for CCC to measure and improve the effectiveness of its support mechanisms, ensuring that each node can reach its potential within the network.
  • Ri​ is the relevance multiplier for node i, signifying the alignment of a node with CCC’s mission.

By analyzing and optimizing each factor, we can methodologically identify gaps in our network and where we can facilitate better support, introductions and knowledge sharing.

For example, if certain nodes have low EVi but high CVi​, it could be beneficial to connect these nodes with others that have high EVi​ to increase their influence and potential impact. Similarly, nodes with high PMi​ but low Si​ may indicate an opportunity to provide additional support to maximize the network’s portfolio multiplier effects.

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