Natural Resources

Purpose-Built for Natural Resources

According to a recent McKinsey report, global electricity consumption doubles by 2050. This is particularly driven by increased electricity demand in buildings and a shift toward electricity as an energy source in road transport. In addition, as the cost of renewables comes down further, many countries will soon reach a tipping point, where new-build solar or wind will be cost-competitive with the fuel cost of existing conventional plants. As a result, renewables are projected to make up over 50% of global generation by 2035.

This burgeoning growth in power generation investments will intensify the following challenges:

Natural Resources Data Challenges


Power investments are becoming more decentralized, requiring smaller deal sizes and higher volume. This higher velocity requires teams to manage more assets with fewer people while maintaining data accuracy across a growing portfolio.


Due to the heterogeneity in assets between traditional power, solar PV, solar thermal, wind, hydro, geothermal, biomass, battery storage, etc., it is critical to capture key operational and financial data at the site level and confidently roll that data up to an aggregate level. For example, what is our EBITDA margin across our entire power & renewables portfolio this month? This type of analysis requires countless hours of manual intervention, across multiple teams, to get right without technology.

Model Complexity

Power investments are some of the most complex assets to model due to several factors. First, electricity power prices are one of the most volatile commodities in the world. Confidently predicting electricity prices 5-10 years out to forecast future power revenues requires sophisticated model forecasting. In addition, power investments have different local, county, state, and federal incentives and depreciation schedules that need to be appropriately accounted for in the model. Making sure these are modeled consistently across a diverse asset class is critical to manage risk-adjusted returns for investors.

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