In the game of energy forecasting, you’re never 100 percent right. And for developing countries, forecasters face rapidly expanding economies and high political expectations.
Such is the case in India. With its relatively young population (median age of 26), India is expected to take over China as the world’s most populous nation around 2025[i]. India’s energy industry has been in the process of deregulating for the past 20 years and still has a few areas that are state-owned. According to the International Energy Agency[ii], this partial deregulation “prevent[s]a more thorough implementation of a well-functioning and financially sound energy sector.”
I was introduced to the uniquely complex Indian energy market through our customer, Reliance. As I began to understand their business, I gained a deeper appreciation for their desire to be more data-driven. In addition to political pressures, volatile fuel prices require that decisions have clear financial benefit in order to keep the company out of the red. For the largest Indian utility company, this meant that they needed to improve forecast accuracy.
Reliance embarked on an ambitious project to implement SAS Demand Driven Forecasting. They now predict that they will recognize a full return on investment within a year. This is largely due to improved forecast accuracy, which reduces their financial exposure to the spot market. In the video below, they detail the “before and after” of this impressive initiative.
Optimizing Power Inventory with SAS
Prior to the use of SAS, forecasts were purely dependent upon senior staff experience, gut-feel, and spreadsheets. Rajiv Sharaf, SVP and Head of IT at Reliance, noted that “When the numbers are large, spreadsheets simply don’t work. You need to have a proper analytics solution in place.” This has also been the conclusion reached by other energy forecasting customers of SAS.
Now that Reliance has been infected with analytic success, they are prioritizing other opportunities to improve data-driven decisions. One area is in their cement business, where the cost of the logistics to make the product is more expensive than the materials themselves.
This will be an interesting story to follow. When combined with ambitious national intentions, I hope it is an early prediction of the promise of analytics for Reliance and other Indian utilities.
[i] IEA population growth projections, WEO 2011. http://www.worldenergyoutlook.org/
[ii] Understanding Energy Challenges in India. OECD/IEA, 2012. International Energy Agency. http://www.iea.org/publications/freepublications/publication/India_study_FINAL_WEB.pdf
1 Comment
It's a good approach to study the Brazil. We have a large and complex environment data. Our environment affect all world including ocean and climate change. We have a tropical rainforest, a real forest with biodiversity, not reforestation.
Our institution produce data in economics and statistics that need more and more analyses and interpretation for management.
An package with forecasting ability are welcome.