Energy Data Analytics: An Indian perspective

28 Sep 2017

By Umesh Bhutoria, CEO, EnergyTech Ventures

Today we live in a digital world that generates increasing amounts of data. This presents an opportunity for industry, where energy systems data can be mined and anaylsed to uncover potential for energy savings and other insights to better shape business strategies. In India, industries have been slow to move on the ‘Energy Data Analytics’ front, but we are seeing signs of change. This article looks at four reasons why Energy Data Analytics is critical to India’s economic success.

1. Competitiveness

When we look at the energy productivity of Indian companies, we can see that while some sectors like cement and fertilizer are setting global energy productivity benchmarks, many others are not. This is true for example of the automobile, textile, and iron and steel sectors. In each, there is considerable opportunity to improve energy productivity (see table below).



Relevance on Energy /Resource Productivity


~7% Contribution to GDP[1]

Automobile sector directly engages a lot of Small and Medium Scale Enterprises from sectors like Foundry, which are quite far from the global benchmarks in terms of energy productivity/ energy intensity.


~4% Contribution to GDP[2]

There is an opportunity to improve energy efficiency of the sector by around 22%, with significant variation in specific energy consumption across different companies.[3]

Iron & Steel

Accounts for 15% of India’s Industrial Energy Consumption

In India, the average primary Specific Energy Consumption (SEC) from selected major steel plants was 27.3 GJ/tcs. Globally, the Best Available Technology (BAT) has a benchmark of primary SEC of 16.4 GJ/tcs through BF-BOF route, 19.3 GJ/tcs by the smelt reduction (COREX)-BOF route, 19.1 GJ/tcs through coal based DRI-EAF route and 15.9 GJ/tcs from gas based DRI-EAF route.[4]


The energy productivity gap in respect to global benchmarks widens when we look at MSMEs. This is significant, as MSMEs contribute around 6.11% of India’s manufacturing GDP and 24.63% of the GDP from service activities, as well as 33.4% of India's manufacturing output[5].

These gaps show that Indian industries, both big and small, have to improve or even double their energy productivity in short span of time to stay competitive and relevant. Energy Data Analytics is a powerful strategy that could help industries understand operational behavior, make the right investments on energy productivity and track their effectiveness. As most low hanging fruits in terms of energy efficiency improvements have been exhausted, it is imperative that a systems approach is taken up by industries. Such an approach is not going to be fruitful without a comprehensive Energy Data Analytics Strategy, one that takes care of key aspects like ‘purpose’ (defining key objectives), thinking big but acting small (learn and evolve) and change management (people and systems need to evolve with time).[6]

2. Automation/ Industry 4.0

Most of the success of emerging economies was driven by access to low cost resources, including human resources. The advent of new technologies, automation and Industry 4.0[7] means that this is not going to be the differentiator anymore. Industries therefore not only have to become smart and foster productivity, but also ensure that there is greater inter-team and better human-machine collaboration. This would also give an opportunity to the workforce to upgrade their skills and learn a lot about working with a greater deal of automation around. Energy Data Analytics provides that missing link.

3. Data is “Debt”

Whether it is installing a simple Energy Monitoring System or building up on network of data assets, most industries have gone ahead without a definite Energy Data Analytics strategy. Because of that, most of the data assets lie unused and essentially become a “debt”, at times confusing people and conveying different outcomes/insights. With the size of sensors becoming small and the cost coming down, most equipment manufacturers are now providing significant data acquisition capabilities along with the machines, meaning that the “data debt” is going to get bigger. Forward-looking organisations will be investing to connect streams of different data assets (e.g. energy, production, process) to unravel operational behaviors and be in better control of the overall process.

4. Designing an industrial energy efficiency policy that works for industries

Various stakeholders in the energy efficiency ecosystem have been collecting significant amounts of energy and production related data from industries/ MSMEs for the past two decades - sometimes even longer, depending on the amount of data that has been digitized. Even with so much of data collected the insights available from them are limited, restricting the better design and implementation of industrial energy efficiency policy.

Digitizing the data sets and deriving insights from raw data could foster innovation. More importantly, it could allow government agencies to design and implement better industrial energy efficiency policies. The entire process of target setting and M&V can become a lot more certain and transparent.[8] This was highlighted in a recent report from the United Nations Industrial Development Organization (UNIDO) on Industry 4.0[9], which emphasised the challenges facing policy makers in designing enabling policies and frameworks that foster the market, in particular given the fast pace at which markets evolve and grow.


Energy Data Analytics has a big role to play in increasing the energy productivity of India’s industries. In the years to come, we will witness growing investments into Energy Data Analytics as consumption of innovation begins to happen at scale – and innovation is happening. Start-ups are devising different ways to use energy analytics and bigger companies are building platforms that can handle industry grade Big Data. What is true for India also holds true for many other emerging economies – perhaps even more so. We are entering a world in which industry is moving from ‘Real Time Monitoring’ to ‘On Time Call to Actions/Insights’. The ability and need to create the right value from data assets is going to inspire and continue to trigger this change. Leveraging data and technology will provide a much-needed impetus to the entire effort of improving energy productivity.


Mr. Umesh Bhutoria is Founder & CEO of EnergyTech Ventures, a leading IP driven company that develops sector/purpose specific algorithms that help industries make the maximum out of their data assets and move towards improving energy productivity.

Umesh has over 10 years of experience in energy markets and is a thought leader in the energy data analytics space (Industrial Energy Efficiency, IIoT). His publications on SlideShare have a viewership of more than 60,000.


[1] IBEF Website (https://www.ibef.org/industry/india-automobiles.aspx

[2] IBEF Website (https://www.ibef.org/industry/textiles.aspx)

[3] TERI report ( http://www.teriin.org/projects/green/pdf/National-Industry.pdf).

[4] A Study of Energy Efficiency in the Indian Iron and Steel Industry 2013 http://www.cstep.in/uploads/default/files/publications/stuff/CSTEP_A_Study_of_Energy_Efficiency_in_the_Iron_and_Steel_Industry_Report_2013.pdf)

[5] CII Website (http://www.cii.in/Sectors.aspx?enc=prvePUj2bdMtgTmvPwvisYH+5EnGjyGXO9hLECvTuNuXK6QP3tp4gPGuPr/xpT2f)

[6] Steps to take before starting with EDA Strategy https://www.slideshare.net/eetpl/things-to-know-before-getting-started-with-eda-strategy

[7] Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. Industry 4.0 creates what has been called a "smart factory".

[8] Why not to ignore #data while designing an Industrial Energy Efficiency Policy https://www.slideshare.net/eetpl/why-not-to-ignore-data-while-designing-industrial-energyefficiency-policy

[9] https://www.unido.org/news/press/new-unido-report-exp.html