Couple of days back I recored my latest Podcast, which kind of touched upon the idea of having definite #EnergyDataAnalytics (Data Analytics in general too) strategy which can lead to transformational change in the way an organisations wants to improve #EnergyProductivity.
This post is really about questioning (reasoning) the current myths/practices that most organisations have in relation to their data strategy (Being from Energy Productivity space, ill focus around it)
- Been there, done that- Most organisations and Energy Managers in particular would certainly like to reason that they are doing enough with their data assets but thats not entirely true. Having an Energy Monitoring System (EMS) or an Energy Management Systems (EnMS) is one thing and having a definite #Energy data strategy is another thing.
To be fair the ones who have the most successful or even evolving strategy, are the ones who would have tagged it along the overall digital transformation goals of the organisation.
- Can see it on my dashboard– Well the world has move much beyond dashboards, it’s time to move from real time data to onetime insights and call to actions. Significant amount of productive time (money as well) is lost in trying to interpret data points.
Have an integrated system using #AI (algorithms for specific use case to mine data and generate specific insights) that enables your teams (energy managers, production managers) to collaborate better on insights and call to actions.
- Need investments to get started– If an organisation is really at the bottom of pyramid when it comes to the data landscape, its absolutely certain that investments would be required to get started with data acquisition etc.
Idea is to maximise to whatever extent possible, overall value creation one could do from existing data assets. Being able to demonstrate a couple of PoCs (Proof of Concepts) or being able to solve even a few problem statements (getting close as well), can go a long way in influencing management to take decisions on #EDA strategy investments.
Greetings from Melbourne!
Yesterday I saw a twitter post from ACEEE that kind of spoke about how companies could do more on investing in #EnergyEfficiency. I have engaged in so many offline and online conversations around #EnergyEfficiency, often see that Industries get the last spot!
Without a shadow of doubt the residential, commercial buildings and the “space cooling” markets are extremely relevant as they have direct connect with consumers, utilities (often state run) have it in their interest to manage the demand- supply situation. But spare a thought, globally industries contribute to around 36% of the total energy consumption.
Industrial #EnergyEfficiency becomes more important for emerging or developing economies who are into manufacturing of goods or delivering services that are energy intensive. Take the case of Bangladesh, Industries account for over 40% of the total energy consumption, out of which the Textile sector contributes to more than half of the consumption.
Completely understand that every narrative of selling #EnergyEfficiency is part of a bigger “narrative” which may or may not bear the same relevance for each country. I speak for emerging / developing economies, here is how policy makers and think thanks look to change the narrative on Industrial #EnergyEfficiency and make it work:-
- Industrial #EnergyEfficiency has direct connect with #EnergyProductivity, which is a better macro indicator when it comes to tracking economic output vis-a-vis energy consumed. #EnergyProductivity should become the default indicator for all energy performance assessments and target setting in Industries
- Have an Industrial policy that is forward looking, integrates aspects like Industry40, IIoT. A country may have the best of Energy Efficiency norms, but a policy that supports import of outdated equipments (linked to process) may not get them anywhere.
- Some of the sectors, especially in the Small Businesses (SME segment) (Foundry, Forging etc) have often had problems in taking up new technologies or processes that can help them have transformational change. Open up these challenges under Industry-Startup partnerships, let them solve the problem and deploy solution at scale.
- Foster sectoral-regional collaboration, create mechanisms in which insights could benefit the sector at large. Understand “sharing of Data” is a challenge, there are business models and use cases one could look at and attempt to overcome these challenges.
Emerging/ developing economies rely significantly on manufacturing as against to services. Any form of inefficieny has a direct link to macro socio-economic indicators of that country.
Would love to know your thoughts?
Episode 3 of the podcast series is out and this one is special.
Here we talk about challenges/risks that CXOs need to watch out for before designing and investing in a consolidated energy data strategy.
#EnergyManagement #EnergyProductivity #Innovation #FacelessReporting #Accountability #Innovation
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