Four ways digital transformation can help meet sustainability goals IBM Supply Chain and Blockchain Blog
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The pandemic-related events of the past two years have people rethinking their sustainability priorities. Governments are issuing regulatory standards. Investors and financial managers are incorporating sustainability criteria in their investment decisions. And customers and employees have become much more environmentally conscious, seeking brands and employers who share their values. Together these forces are shaping a new corporate agenda. Sustainability has rightly planted itself in the heart of boardroom and operational management conversations.
Despite this rising tide of influence, a new report by IBM’s Institute for Business Value, “Sustainability as a transformation catalyst: Trailblazers turn aspiration into action,” reveals that only 35% of companies have acted on their sustainability strategy. As few as 4 in 10 companies have identified either the initiatives to close their sustainability gaps or sustainability drivers for change. And only one-third have integrated sustainability objectives and metrics into business processes.
Businesses need actionable environmental insights to meet sustainability goals. But current methods are often cumbersome and complex, requiring intensive manual labor, climate and data science skills, and computing power to fully utilize their data.
The good news is that digital transformation can help organizations stay resilient, adaptive and profitable in this new era. Here are four ways a comprehensive data and AI strategy can play a key role in reshaping business operations around a sustainability agenda.
Creating a more resilient infrastructure
The effects of climate change and dwindling natural resources demand that companies extend the life of their buildings, bridges and water lines. By embarking on digital transformation to meet sustainability commitments, companies can uncover new opportunities to optimize their processes, lower costs, reduce waste, attract new customers, increase brand loyalty, and embrace new business models.
AI-powered remote monitoring and computer vision help organizations see, predict, and prevent issues. They can also perform condition-based maintenance based on operational data and analytics to reduce downtime and maintenance costs. Improved asset management can help companies reduce their spare parts inventory. And a company can save on energy costs by pinpointing a small problem before it becomes a bigger, more energy-draining issue.
Building a transparent, trusted supply chain
Supply chain leaders need visibility. When they can’t track the exact amount and location of their inventory they have and where it is, they can over-order, tying up too much working capital. And if supply chain leaders lack transparency and data sharing with their deep-tier suppliers, it’s incredibly difficult to track products from point of origination to delivery in a trusted and controlled way. This makes it harder to identify supplier risk and protect the brand.
Reaching supply chain sustainability goals requires a global, accurate, real-time view of inventory, plus the ability to share data across the supply chain ecosystem in a way organizations can trust. AI helps companies avoid obsolete and unsellable inventory, reduce carbon emissions from logistics moves, optimize fulfillment decision-making, and minimize waste across raw materials, finished goods and spare parts inventories.
Deriving business insights from environmental intelligence
Companies exposed to a wide range of external factors need especially sophisticated predictive tools. Consumer goods companies such as Unilever want data to help them predict environmental impact and make sustainable choices. Insurance companies such as Canada’s Desjardins Insurance want to better predict disruption to policyholders — for example, advanced notice of imminent hailstorms could help its clients take action to avoid damage. Environmental intelligence capabilities help companies plan for and respond to weather events with AI-driven predictions derived from a combination of proprietary and third-party geo-spatial, weather and IoT data. This streamlines and automates the management of environmental risks and operationalizes underlying processes, including carbon accounting and reduction, to meet environmental goals.
Decarbonizing the global economy
In the coming years, utilities will continue to play a central role in the energy transition by accelerating global decarbonization through clean electrification — the process of replacing fossil fuels with electricity produced from renewable sources, like wind, solar and hydro. And they will need a comprehensive asset management strategy for operations, maintenance, and the lifecycle of these renewable energy plants. Digital transformation will be key to decarbonization, and it will help electricity ecosystems deliver clean energy to connected consumers in safe and reliable ways.
Businesses everywhere have entered a new era of digital reinvention, fueled by innovations in hybrid cloud and AI. IBM is uniquely positioned to help our clients advance Sustainable Development Goals (SDGs).
In this radically changed business landscape, IBM is partnering with organizations to deliver five levers of digital advantage that are designed to: predict and shape data-driven outcomes, automate at scale for productivity and efficiency, secure all touchpoints all the time, modernize infrastructures and transform with new technology-driven digital business models.
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