SUSTAINABILITY FOCUS 10

How data analytics is enabling businesses to practice sustainability To build sustainable operations and practices, businesses need data and analytics to find efficient ways of managing their processes and assets. By Sunil Senan, Senior Vice President and Business Head, Data and Analytics, Infosys

  • 2 years ago Posted in

Sustainability is being able to meet the needs of the present without sacrificing those of future generations. Today, sustainability is no longer a good-to-have CSR initiative. Instead, it is central to all businesses as it creates value by driving efficiency, lowering the cost of operations, and encouraging innovation. Most importantly, sustainable companies can become profitable in the long run, as the discussion at the World Economic Forum in 2020 proved. 

At the heart of the future of enterprises is data. It is driving new business models, new experiences, and a new data economy. For instance, a global auto major is leveraging data and vehicle connectivity to provide a multi-modal transport to create new experiences and payment option that includes car-pooling, car-sharing, or car subscriptions. 

With the advent of cloud, AI, and ML, enterprises are able to reimagine their industry play, often even crossing the traditional industry boundaries. Data is used to make enterprise digital that works with the clock speed governed by real-time, every-time operations. No matter the nature of your business, data analytics helps you transform to a live enterprise (synonymous to living organisms that can sense, respond, and evolve with context and experiences) as well as sustainable. For example, a US-based power utility company is using data and analytics to mitigate wildfire risks. Data Analytics is the cornerstone to everything: building an efficient supply chain, adopting green banking, or designing a sustainable office campus while ensuring data privacy, security, and compliance.

The emerging role of sustainability in businesses

To build sustainable operations and practices, businesses need data and analytics to find efficient ways of managing their processes and assets. Connected devices, sensor technologies, instrumentation, and the Internet of Things (IoT) network can lead to better data collection. A well-defined data management strategy built on AI and predictive analytics can draw insightful analysis out of this data to create advanced industrial systems that can support sustainable ecosystems. 

For instance, typically, a supply chain contributes to 90 percent of most companies’ environmental impact. According to a PwC study, AI can potentially help reduce global greenhouse gas emissions by up to four percent by 2030. Another study by Deloitte in March 2021 found one out of every three consumers claimed to have stopped purchasing certain brands or products because they had ethical or sustainability-related concerns about them. So, it is not only worth it but also prudent to build an environmental-friendly supply chain.

By leveraging data, businesses can bring new automation power to their supply chains. Data Analytics can help optimise supply chain flow by forecasting demand, facilitating planning activities, planning predictive maintenance, and reducing error rates significantly. AI systems built on strong data analytics can also help discover and predict consumer habits and anticipate demand trends thereby, minimising unwanted inventory and wastage.

Similarly, using the expertise of technology companies, banks can create an index that considers multiple parameters as charted by UN sustainability strategies. Banks can use this index to make smarter and faster decisions on incentivising corporate customers who meet climate protection guidelines in earnest. These incentives, such as lower interest rates on loans—can push organisations to score better on the Green Banking Index by focussing on sustainability goals.

As James Gorman, the CEO of Morgan Stanley, perfectly explained the importance of sustainable finance: “If we don’t have a planet, we’re not going to have a very good financial system.”

Several companies already collect and report sustainability-related data across their operations. Such companies are now turning to analytics to define their sustainability agenda by collecting data from a wide range of points.

For instance, collecting real-time data using sensors and IoT devices in an office building or campus can help derive relevant insights on energy and water usage patterns, seasonal factors and occupancy levels. These can help in making automated decisions on how to optimise energy and water consumption or reduce waste.

These insights can also help make business systems work better so that employees are healthier and more productive. As a result, you have an organisation that’s not only lean and agile but also attracts and retains quality employees.

To build a sustainable campus, organisations must start by articulating the success metrics and prioritising smart infrastructure and operations, smart user experience, and smart environmental design. Importantly, they must collaborate with expert partners who have been through the journey themselves.

Between 2007 and 2018, Infosys used Smart Spaces methods to achieve the following results at our Mysuru campus: we reduced per capita electricity consumption by 34 percent, water consumption by almost 60 percent, and increased the share of renewables in our campus energy mix from 30 to 80 percent.

By doing so, we were able to promote sustainable usage of scarce resources such as energy and water and impress our current and potential customers while simultaneously exceeding all applicable regulations.

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