Earlier this month we hosted India’s first Energy Data Analytics Summit in Delhi, where one of the discussions led to some people asking “What can governments do with (tons of) Industrial #EnergyEfficiency related Data?
This question to me has a lot of significance. Just as the way all Governments use Health, Economy, Inflation, Education related data for greater good (social and economical), why treat Industrial #EnergyEfficiency related data differently? While one may argue that there is no precedence, but given the age in which we are living, we are seeing use cases evolve every day.
In this blog i intend to initiate dialogue on two of the use cases for greater use of Industrial #EnergyEfficiency related data and who stands to gain and how?
Hard to believe that most industries/sectors do not yet have correct bench-marking methodology/tools available. I am using the term “tool” here because industrial processes have a lot of variables and hence one cannot have a “number”, but there is no excuse to have not been able to develop a “tool” yet.
Will the government make the tool? NO. But they can open up the data for other solution/service providers, let them develop applications on it. Innovation can foster.
Contrary to what many believe “opening up data” doesn’t mean that anonymity can’t be maintained, there is no need to share raw data, connected insights/indicators could do a lot of good straight away. Mix of qualitative and quantitative data (derived output from raw data) allows enough room for innovation.
- Investment Trend & Success
Fact that many governments have been collecting data on Industrial #EnergyEfficiency for over a couple of decades, allows them to keep track of investment trends, returns being yielded, % increase in efficiency YoY, which sector does well and which is lagging etc?
Governance can be simplified drastically if data is put to use. Its happening everywhere, there is no reason why Industrial #EnergyEfficiency has to be ignored. Designing Industrial #EnergyEfficiency policy w/o data points is not worth it.
Some of the other use cases could be:
- AI driven assistance in Measurement & Verification (Example: PAT Scheme in India currently relies on 100% human driven verification process)
- Predicting performance, forecasting demand supply situations instruments linked to Energy Efficiency Projects ( White Certificates/ Energy Saving Certificates/ ESCerts (PAT Scheme))
What’s your take on this? Would love to hear from you on “How your Government could do more with Industrial #EnergyEfficiency related Data?”