When the 2030 agenda for Sustainable Development was adopted by United Nations member states, it was made clear that businesses have the responsibility to act quickly and the power to see it through, regardless of size, industry, or location. From merely being a philanthropic pursuit, organisations have also realised why achieving sustainable goals was important from a business point of view.
For businesses today, sustainability is one of the key ways to reduce operating costs and stay insulated from resource shortages and price shocks. CXOs, in particular, are under mounting pressure to comply with regulatory requirements, mitigate risks, and improve their environmental footprint. To achieve these goals, organisations are increasingly leveraging data analytics, the science of extracting insights from raw data, to drive sustainable practices and boost efficiencies.
In this blog, we explore how data analytics is transforming sustainability across various industries and provide insights into the key challenges, opportunities, and best practices for harnessing data to drive sustainability. Not only is data crucial for a company to fully understand current needs, but the right analysis can help organisations improve their impact and transform the way they do business. By collecting and analysing data on a wide range of sustainability-related factors, sustainability analytics can generate deep insights that companies need, to guide their sustainability-related initiatives and improve their overall resource efficiency.
The New Way
The business community has long viewed sustainability as a trade-off between doing what's good for the world and what's good for the bottom line. But as data unlocks exciting possibilities, those goals are increasingly becoming aligned. With a comprehensive data-driven strategy, enterprises can meet sustainability goals to satisfy customers, employees, and investors. There was never a better time for leaders across industries to explore what's possible with ESG data at the heart of the enterprise.
1. The power of data in driving sustainable practices
The Swedish furniture retailer IKEA started a subscription-based leasing option on a trial basis in 2019 to reduce its environmental footprint by encouraging product reuse. IKEA aims to become a circular business, that is, reuse, refurbish, remanufacture, and recycle, by 2030, using data and analytics to implement changes across its operations spanning 50 countries. Apple is another company using data to improve product design to make their products last longer, lower the environmental cost of production and make the supply chain more efficient. With an ambitious goal of carbon neutrality by 2030, Apple is leveraging all available data towards achieving its target.
A similar trend is witnessed across industries – for instance, in the energy sector, utilities are using data analytics to optimise energy efficiency, reduce carbon emissions, and enhance grid reliability. By analysing energy consumption patterns, weather data, and other variables, utilities can identify opportunities for demand-side management and dynamically adjust power generation to meet fluctuating energy demands. Similarly, data analytics enables manufacturing companies to identify inefficiencies and minimise waste while improving product quality and ensuring regulatory compliance.
2. The challenges of harnessing data to drive sustainability
Despite its immense potential, leveraging data analytics to drive sustainability comes with a host of challenges. One of the most significant challenges is the lack of standardization and interoperability of sustainability data across industries. With disparate data sources, varying definitions, and different standards, it can be challenging to collect, analyse, and report sustainability metrics accurately. Additionally, privacy concerns, data security risks, and ethical considerations pose barriers to collecting and managing data.
3. Best practices for harnessing data to drive sustainability
To overcome the challenges of data analytics, companies must adhere to best practices that prioritise data governance, quality, and transparency. By adopting a data-centric approach, companies can create a robust data governance framework that defines data standards, ownership, and management processes. Furthermore, prioritising data quality assurance and validation ensures that data insights are accurate, reliable, and actionable. Perhaps most importantly, companies must be transparent about their data collection and reporting processes, showing stakeholders how they use data to drive sustainable practices.
4. Opportunities for leveraging data analytics to drive sustainability
The opportunities for leveraging data analytics to drive sustainability are extensive. Besides reducing costs, enhancing efficiencies, and mitigating risks, data analytics can enable companies to improve their environmental and social impact, enhance their brand reputation, and differentiate themselves from competitors. Data analytics also enables companies to identify new opportunities for innovation and improve decision-making with real-time insights into customer behaviour, market trends, and stakeholder needs. With advanced analytics, companies can minimise price shocks and supply disruptions and understand emerging risks to stay ahead of the competition.
Getting started on 'The New Way'
1) Understanding the impact: The first step in leveraging data analytics for sustainability is to understand the impact your business is having on the environment. This means collecting data on energy consumption, waste output, and carbon emissions. By analysing this data, you can identify areas where your business is consuming energy or generating waste unnecessarily. This information can then be used to make more informed decisions about energy usage and waste reduction initiatives.
2) Setting targets: Once you have a clear understanding of your environmental impact, you can begin to set specific sustainability targets that align with your business goals. For example, if you identify that your business is using a significant amount of energy during non-peak hours, you can set a target to reduce energy consumption during these hours. By setting specific targets, you can track progress and continue to make improvements.
3) Real-time monitoring: In addition to setting targets, it’s also important to monitor your progress in real-time to ensure you’re on track to meet your sustainability goals. Data analytics can be used to track energy consumption, waste output, and other key sustainability metrics in real-time. This can help you identify areas where you’re falling behind and make adjustments to ensure you stay on track.
4) Collaborating with suppliers: Sustainability efforts don’t stop at the boundaries of your own business. To truly drive sustainability, you’ll need to collaborate with suppliers, vendors, and other partners in your supply chain. By sharing data and insights, you can work together to identify areas for improvement and create more sustainable processes.
5) Driving innovation: Finally, data analytics drives innovation and creates new, more sustainable solutions. By analysing data and looking for patterns, businesses can identify new ways to reduce waste, improve energy efficiency, and make other sustainability improvements. This type of innovation can not only drive sustainability efforts but also create new business opportunities and competitive advantages.
Revving up on 'The New Way'
Leveraging data analytics to drive sustainability is crucial for companies that aim to mitigate risks, reduce costs, and enhance their environmental impact. While challenges such as data governance, standardisation, and privacy concerns continue to persist, embracing best practices and staying abreast of advances in data analytics can enable companies to unlock significant opportunities for sustainability. With the right data-driven approach, companies can stay ahead of the curve and lead the charge towards a more sustainable future while enjoying a competitive advantage in the marketplace.
(The article is written by Srikrishna Koneru.)(Articles under 'Fortune India Exchange' are either advertorials or advertisements. Fortune India's edit team or journalists are not involved in writing or producing these pieces.)
(Srikrishna (Kris) has over 30 years of experience in sourcing and procurement in Manufacturing, Consulting, and EPC companies with exposure across a wide variety of equipment, commodities, and services. As a global practice head for S&P, LPO, and New Service Lines at Infosys BPM, Kris is one of the pioneers in building and offering next-generation procurement systems, services, and innovative delivery models for our clients.)
((Articles under 'Fortune India Exchange' are either advertorials or advertisements. Fortune India's edit team or journalists are not involved in writing or producing these pieces.)