Dave Sivaprasad

And in a developing economy such as this, massive trade-offs that you need to manage in terms of where you deploy resources.

Initially, this region was looking at building seawalls, having early warning systems, storm barriers in place that required a fair bit of capital and investment.

In fact, what we found was that a mix of solutions were needed.

So that included mangrove restoration in selected areas as natural defense, and only in certain parts of the coast, investing to build storm barriers and seawalls.

Now with that, the region could consider

with the same amount of resources, maximizing lives saved, livelihoods protected and ecosystems safeguarded.

And on top of this, the cost of inaction, of not doing anything, also meant massive

negative impact for the private sector.

So private enterprises would have had billions of dollars of losses with manufacturing, with critical infrastructure, with commercial real estate being damaged.

Now, having a visibility on this, the government could then engage the private sector on co-developing and co-funding solutions that benefit both private enterprise

and the local community.

Now, this is not a problem only in Southeast Asia.

A city in West Africa, for example, had similar challenges, but compounded with very dense populations along the coast, severe land subsidence, and drainage challenges that were exacerbated by poor solid waste management in some parts of the city.

Now, by integrating climate science data analytics to the local context and tightly linking this to socioeconomic impact, the government was able to manage the trade-offs on how you would balance the deployment of resources to things such as, do I build more drainage infrastructure?

Do I relocate some populations to other parts?

Do I build storm barriers?

What's the right mix?

This is a challenging and complex problem.

And when you look at it, the challenge is every course that you look at is different, right?

They're socioeconomically, physically different.