By Fawad Qureshi, Global Industry Field CTO at Snowflake
There are no two ways about it, humanity is on the cusp of a climate crisis. According to the United Nations, the global temperature is rapidly approaching the threshold of 1.5ºC above the pre-industrial level. This will result in the effects of climate change becoming more severe and that is not sustainable.
Corporate India is driving sustainability efforts by using data. SEBI has also taken cognizance and made it mandatory for all companies to disclose their ESG scores. According to Deloitte’s CXO Sustainability Survey 2023, 81% of Indian chief experience officers say sustainability investments are up in the past 12 months, with 27% characterising these as ‘significant’ growths in investment. India also has massive potential, with McKinsey estimating that the country could create carbon space equivalent to nearly half of the current global carbon budget. However, many organisations still struggle with managing sustainability challenges. For one, the same McKinsey report notes that the current pace of emissions intensity reduction in India is insufficient, especially in view of the government’s net zero by 2070 target.
The Importance of Measuring Sustainability Efforts
It is often said that what gets measured, gets done. This is no different when it comes to an effective sustainability strategy. The key to driving effective action lies with data. Today, business leaders have overwhelmingly identified modernising technologies to take full advantage of data and artificial intelligence (AI) as critical.
Not only does measuring boost reporting, it also resolves the perceived tension between profitability and climate conscious operations. Certainly the pressures around environmental, social and governance (ESG) disclosures has grown in importance for the business’ partners and customers. Fostering these relationships and retaining customers naturally, then, hinges on keeping sustainability at the forefront of their data strategy.
While reporting identifies gaps, companies need a data platform that enables them to effectively implement mitigation plans, transform operations, and help efforts to better the environment.
The first step to doing this is leveraging modern tools and solutions to embed ESG in the enterprise strategy. Legacy processes are not equipped to facilitate this, and often exacerbate silos and other inefficiencies. Moving away from them is crucial to capturing the necessary data so that decision-makers can swiftly identify the direction of the business vis-a-vis sustainability. In fact, they can also drive successful data monetisation strategies. Ideally, supporting this with a top-down policy promoting data literacy and sustainability will also make the business future-ready.
No Short Cuts When It Comes to Sustainability
Achieving net zero takes time, and a good jumping off point is to start with sustainable IT. The Fourth Industrial Revolution means that new technologies are springing up at a rapid pace. Designing IT systems that promote sustainability is critical. For instance, organisations can be more energy efficient by utilising data infrastructures with highly scalable compute resources. This will allow for fluctuating demand to be handled more sustainably, especially when juxtaposed with the regimented sizing of a data warehouse.
Under scope-3 regulations companies must report the carbon emissions across their entire value chain. This can become tricky as corporate value chains are extremely complex. Companies need to build practices which facilitate data sharing across the entire value chain in a transparent, frictionless, low-latency, and fully governed way.
While the current business climate is uncertain, the headwinds businesses face today does not mean that short-term concerns need to contend with long-term sustainability goals. In fact, leveraging artificial intelligence (AI) and machine learning (ML) to improve data visibility and broaden data utilisation are already proving to be key enablers in overcoming this.
Doing so enables companies to build practices that allow data to be shared across the entire value chain in a transparent, frictionless, low-latency, and fully governed way.
In addition to internal data and supply chain data, external sources – such as geospatial data and satellite imagery – can give organisations a panoramic view of the business environment. Different kinds of datasets in different formats are needed for this, and here is where data marketplaces come in, as they can boost data collaboration and offer multiple levels of supply chain visibility.
Improve Insights by Decentralising Data Architecture
Today’s organisations are generating more and more data from growing numbers of sources. ESG has undoubtedly contributed to this, and many enterprises are ill equipped to keep up with this explosion and derive more value from their data quickly.
A decentralised data organizational approach such as data mesh can address the challenges that come with trying to be more data-driven, so much so, that it could even be the key to understanding and meeting sustainability goals.
As an operating model, data mesh categorises data as a product under the purview of teams closest to it. This is far more efficient than a model in which data is pooled together in a single, centralised data lake or warehouse.
Within a data mesh, sustainability can be defined as a key cross-functional use case for data. Teams that are closest to that data can then better understand its sustainability implications. This empowers teams, removes barriers to data and delivers value at scale.
As the world grapples with the urgent need to slow climate change, businesses in India can play a leading role by leveraging AI and ML to gain better, more actionable insights that drive sustainability initiatives.
