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Sammo Energy


Sammo Energy Uses Quantrix to Model New Energy Industry


“They were impressed with how I was able to present results using Quantrix”

Didier Varlot, CEO


There are a number of innovative ways to generate energy, but no matter how potentially profitable the project, they all need financing. And that requires a detailed financial model that identifies the costs, revenues and the risks based on a variety of scenarios, and the proposed timeframe for key metrics such as payback and return on investment. For Sammo Energy, a UK-based start-up developing its first projects in Romania, Quantrix is the key to discovering the answers to those necessary questions.

Sammo Energy’s idea is simple: it uses traditional geothermal turbine technology to transform waste heat into usable electricity.  Targeted for energy-intensive industries such as cement plants and metallurgy facilities, these projects require long-term contracts and significant financial investment. Sammo measures numerous factors to determine viability, including technical performance variations, waste heat predictions, market price evolution, legal issues, carbon tax costs, interest rate fluctuations, and currency.

“Financiers want to dynamically view scenarios based on multiple factors, and have very specific presentation and reporting requirements,” says Didier Varlot, CEO, Sammo Energy. “Each project I’ve worked with requires a minimum of €12+ million investment, so the model and presentation needs to be rock-solid.”

Varlot used Quantrix in a former job, and knew the business modeling and analytics solution could handle the task of creating multiple scenarios requiring numerous variables and assumptions. “Quantrix enables me to make scenarios that include sensitivities, so I know how to protect the company during negotiations,” says Varlot. “This is too complicated to do in a program like Excel, but it’s very simple in Quantrix. It’s easy to make a matrix with a variety of scenarios, and then to extend the model with new dimensions.”

In one case, Varlot prepared project finance models for a group of financiers, which requested what-if scenarios based on a number factors for 10 projects, including market price evolution over the course of 20 years, on projections based on carbon taxation, on a variety of interest rates and financing options, and on the ratio between debt and equity. The financiers gave him 48-hours notice for an important strategy meeting; Varlot had the models ready within 12 hours.  “They were impressed with how I was able to present results using Quantrix,” says Varlot. “I incorporated sensitivity analysis, and displayed financial data visually, which is often easier for people to interpret.”

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