8 items tagged "sustainability"

  • Green AI: how AI poses both problems and solutions regarding climate change

    Green AI: how AI poses both problems and solutions regarding climate change

    AI and ML are making a significant contribution to climate change. Developers can help reverse the trend with best practices and tools to measure carbon efficiency.

    The growth of computationally intensive technologies such as machine learning incurs a high carbon footprint and is contributing to climate change. Alongside that rapid growth is an expanding portfolio of green AI tools and techniques to help offset carbon usage and provide a more sustainable path forward.

    The cost to the environment is high, according to research published last month by Microsoft and the Allen Institute for AI, with co-authors from Hebrew University, Carnegie Mellon University and Hugging Face, an AI community. The study extrapolated data to show that one training instance for a single 6 billion parameter transformer ML model -- a large language model -- is the CO2 equivalent to burning all the coal in a large railroad car, according to Will Buchanan, product manager for Azure machine learning at Microsoft, Green Software Foundation member and co-author of the study.

    In the past, code was optimized in embedded systems that are constrained by limited resources such as those seen in phones, refrigerators or satellites, said Abhijit Sunil, analyst at Forrester Research. However, emerging technologies such as AI and ML aren't subject to those limitations, he said.

    "When we have seemingly unlimited resources, what took precedence was to make as much code as possible," Sunil said.

    Is AI the right tool for the job?

    Green AI, or the process of making AI development more sustainable, is emerging as a possible solution to the problem of power-hungry algorithms. "It is all about reducing the hidden costs of the development of the technology itself," Buchanan said.

    A starting point for any developer is to ask if AI is the right tool for the job and to be clear on why machine learning is being deployed in the first place, said Abhishek Gupta, founder and principal researcher at the Montreal AI Ethics Institute and chair of the Green Software Foundation's standards working group.

    "You don't always need machine learning to solve a problem," Gupta said.

    Developers should also consider conducting a cost-benefit analysis when deploying ML, Gupta said. For example, if the use of ML increases a platform's satisfaction rate from 95% to 96%, that might not be worth the additional cost to the environment, he said.

    Choose a carbon-friendly region

    Once a developer has decided to use AI, then choosing to deploy a model in a carbon-friendly region can have the largest effect on operational emissions, reducing the Software Carbon Intensity rate by about 75%, Buchanan said.

    "It's the most impactful lever that any developer today can use," Buchanan said.

    Gupta provided the following example: Instead of running a job in the Midwestern U.S., where electricity is primarily obtained from fossil fuels, developers can choose to run it in Quebec, which garners more than 90% of its electricity from hydro.

    Companies will also have to consider other factors beyond energy type when deciding where an ML job should run. In April 2021, Google Cloud introduced its green region picker, which helps companies evaluate costs, latency and carbon footprint when choosing where to operate. But tools like these aren't readily available from all cloud providers, Buchanan said.

    To address the issue, the Green Software Foundation is working on a new tool called Carbon Aware SDK, which will recommend the best region to spin up resources, he said. An alpha version should be available within the next couple of months.

    Other ways to be green

    If the only available computer is in a dirty electricity region, developers could use a federated learning-style deployment where training happens in a distributed fashion across all devices that exist in an electricity regime, Gupta said. But federated learning might not work for all workloads, such as those that must adhere to legal privacy considerations.

    Another option is for developers to use tinyML, which shrinks machine learning models through quantization, knowledge distillation and other approaches, Gupta said. The goal is to minimize the models so that they can be deployed in a more resource-efficient way, such as on edge devices, he said. But as these models deliver limited intelligence, they might not be suited for complex use cases.

    Sparse and shallow trees -- tree-based models partitioned into a small number of regions with sparse features -- can also provide the same results at less cost, Buchanan said. Developers can easily define them with a set of parameters when choosing a neural net architecture, he said.

    "There's an industrywide trend to think that bigger is always better, but our research is showing that you can push back on that and say specifically that you need to choose the right tool for the job," Buchanan said.

    Consumption metrics could be the solution

    The Green Software Foundation and other initiatives are making progress toward measuring and mitigating software's carbon footprint, Buchanan said.

    For example, Microsoft made energy consumption metrics available last year within Azure Machine Learning, making it possible for developers to pinpoint their most energy-consuming jobs. The metrics are focused on power-hungry GPUs, which are faster than CPUs but can consume more than 10 times the energy. Often used for running AI models, GPUs are typically the biggest culprit when it comes to power consumption, Buchanan said.

    However, what's still needed is more interoperable tooling, Buchanan said, referring to the piecemeal green AI tools that are currently available. "The Green Software Foundation is doing one piece," he said, "but I think cloud providers need to make concerted investments to become more energy efficient."

    Ultimately, the goal is to trigger behavior change so that green AI practices become the norm, according to Gupta. "We're not just doing this for accounting purposes," he said.

    Author: Stephanie Glen

    Source: TechTarget

  • Green businesses are on the rise: a dive into the global ESG developments

    Green businesses are on the rise: a dive into the global ESG developments

    Many investors and other stakeholders have been actively expressing the need for greater transparency on the ESG (environmental, social and governance) strategies of companies. Adding to this, the COVID-19 pandemic has further brought sustainability into the spotlight, raising awareness about the negative impact climate change and social justice issues are having on the world. At the same time, the pandemic has highlighted the value of ESG considerations in financial markets, as global sustainability benchmarks outperformed traditional market benchmarks and ESG funds achieved record inflows. The pandemic seemed to confirm what ESG pioneers have long propagated: that companies with superior ESG performance can be expected to be better prepared to weather such crises and to operate in the post-crisis world. This is because they are well-managed companies, with stronger competitive advantages, healthier balance sheets and a better social license to operate than their non-ESG peers.

    This growing attention is underscored in this year’s look at the progress that is being made on environmental sustainability, as many publicly-traded companies take additional steps to improve their situations. For example, in 2011 approximately 20% of the largest 500 companies in the U.S. published a sustainability report.The volume has been increasing steadily ever since, reaching 75% of these companies in 2014 and a record 90% in 2019.

    This section highlights a number of important trends we are seeing as corporations focus more effort on their environmental performance. It should be noted that company reported data does not yet provide coverage of the abrupt COVID-19-related decreases in global carbon emissions observed since March 2020.

    Companies mentioning ESG for the first time in SEC filings are on the rise

    ESG reporting has remained largely voluntary in the U.S. The Securities and Exchange Commission’s (SEC’s) general disclosure guidance, which includes ESG issues, emphasizes materiality − the extent to which a reasonable investor would consider information important in relation to an investment decision. There have been a total of 597 different publicly-traded U.S. companies mentioning ESG in SEC filings since 2006. While this only represents approximately 16% of all public  companies in the country, the number mentioning ESG in their SEC filings for the first time has been steadily increasing − from 9 companies in 2016 to 36 in 2018 and 90 in 2019. We look forward to the opportunity to provide continued updates on this significant trend.

    Over the past five years, there has been a growing trend in the number of companies publishing sustainability reports, with 90% of the largest 500 companies in the U.S. reporting in 2019 – an 11% increase since 2015. A range of frameworks and standards are being used, including those provided by the Global Reporting Initiative (GRI), Sustainability Accounting Standards Board (SASB), and Taskforce on Climate-related Financial Disclosures (TCFD). While 51% of the S&P 500 reporting companies use GRI, support continues to grow worldwide for the framework recommended by the TCFD and increasingly mandated by regional governments.

    There’s been a steady growth in the number of companies supporting TCFD

    According to the TCFD, which was established in 2015, better disclosure will lead to more informed and more efficient allocation of capital, and help facilitate the transition to a lower-carbon economy. Backing for the framework has surpassed initial expectations, with the number of supporting companies exceeding 1,500 in 2020 − over five times that in 2017. This includes every major type of financial market participant, plus nearly 60% of the world’s 100 largest public companies that either support the TCFD, report in line with its recommendations, or do both.

    Financial sector accounts for half of TCFD supporters

    Half of all companies that support the TCFD are in the financial sector. Asset management/investment management, banks, and pension funds together represent 75% of the supporting organizations in the sector. According to the TCFD, larger companies are more likely to disclose information aligned with the recommendations. On average, 42% of companies with a market capitalization greater than $10 billion U.S. disclosed in 2019, while the average was 15% for companies with a market cap less than $2.8 billion.

    Europe, Asia and North America are home to most TCFD supporters

    The European Union is among the leading major economies when it comes to tackling greenhouse gas (GHG) emissions. By 2018, it had cut GHG emissions by 23% compared to 1990 levels, and is committed to achieving a 40% reduction by 2030. Not surprisingly, therefore, it represented 38% of organizations supporting the TCFD in 2020. With typhoons and floods becoming more intense and frequent in Asia, companies here are showing their concern with climate change, with the region representing 30% of organizations supporting the TCFD in 2020. North America was third at 21%, leaving these three regions accounting for 88% of overall support in this year.

    Source: S&P Global

  • Measuring and managing sustainability for IT leaders  

    Measuring and managing sustainability for IT leaders

    How can IT leaders know if they’re tracking greenhouse gas emissions comprehensively? The introduction of AI and machine learning are painting a clearer picture.

    As companies attempt to take sustainability to the next level and gain a more complete view of their greenhouse gas emissions, there’s a growing need to quantify results and track progress.

    If you can’t measure it, you can’t manage it,” says Autumn Stanish, associate principal analyst at Gartner, Inc. “In order to take initiatives to the next level -- particularly as organizations look to expand beyond Scope 1 and Scope 2 tracking -- there’s a need for more advanced and granular measurement tools.”

    It’s no small problem. Boston Consulting Group (BCG) reports that while 85% of companies are interested in reducing their emissions, only 9% of companies measure their total emissions comprehensively. Worse, only 11% have reduced their emissions in line with their goals over the last five years.

    How can companies get a better handle on their carbon footprint? How can CIOs and other IT leaders ensure that tools are in place for tracking emissions comprehensively? Although developing a framework remains a challenge, the introduction of AI and machine learning are changing the picture. “Tracking tools are becoming more refined and more useful,” Stanish says.

    Emerging Tech for Measuring Emissions

    Gaining insight into sustainability is becoming easier. Tools for measuring Scope 1 emissions (produced by company facilities or vehicles) and Scope 2 categories (purchased energy) have advanced considerably over the last few years. Yet, most organizations still lack an extended view of external emissions, referred to as Scope 3. These emissions extend out to the value chain and include products that have been sold.

    This lack of visibility is making it difficult for organizations to assemble a strategic framework and road map. BCG found that 57% of companies that measure all three types of Scope emissions see a significant decrease in emissions versus 31% that only partially measure emissions. Adding to the challenge: A measurement system must be accurate to pay dividends. Remarkably, firms BCG surveyed admitted a 30% to 40% error rate on their measurements.

    “It’s difficult to obtain a comprehensive view of a company’s footprint, says Mike Lyons, a managing director at BCG. “It’s very easy to get the carbon accounting or a boundary wrong, especially as organizations attempt to get a handle on Scope 3 emissions and understand product and technology lifecycles at a granular level.” In addition, a lack of expertise within organizations, even among environmental, social, and governance (ESG) teams, serves as an impediment.

    Most of today’s tools generate numbers based on widely used carbon accounting methodologies while allowing users to view their results against specific goals and targets. For example, software tools and platforms such as Salesforce Sustainability CloudSphericsEnviziSource Intelligence and Carbon Analytics provide dashboards that extend out to Scope 3 emission categories.

    Cloud providers, including AWS, Azure and Google Cloud, also offer tools that provide insights into compute cycles, energy consumption, and carbon output. For example, Google has several tools that allow organizations to track carbon emissions, including Carbon Footprint, which highlights gross carbon emissions data in reports and disclosures, visualizes carbon insights via dashboards and charts, and offers tools designed to reduce gross emissions from cloud applications and infrastructure.

    Tools tracking Scope 1 and Scope 2 emissions typically plug in power and fuel consumption, using power bills, meter readings and other sources. Many rely on aggregate and average figures collected from reports, documents, audits, and user inputs. Highly distributed businesses and organizations gauging Scope 3 emissions face steeper challenges. “Things can get difficult if you are a retailer and have thousands of stores, all with different bills at different rates, and you start peering into the supply chain,” says Casey Herman, ESG Leader at PwC US. “The question becomes, how do you accumulate all the data and convert everything into carbon output?”

    It's critical to understand how equipment, data centers, systems, and devices consume greenhouse gas emissions on a more granular level, Herman points out. “Many tools use conversation factors that may or may not be accurate.” Although major equipment manufacturers often share data about their products, assembling all the pieces into a complete picture can prove daunting. “Many business and IT leaders realize that they are missing lots of data or they have the carbon accounting wrong,” Lyons says. For now, “They have no way to understand what is really taking place.”

    Dialing Down Emissions

    BCG found that 86% of organizations continue to use spreadsheets to track carbon emissions. Overall, 53% of business and IT leaders say that they have trouble making and tracking decisions. An incomplete picture of assets and consumption is partly to blame but business leaders also complained that measurements take place too infrequently, and a lack of automation is a problem.

    More advanced platforms that incorporate AI and machine learning are emerging. BCG, for example, has introduced an artificial intelligence-based software platform called CO2 AI that strives for a more complete and accurate view across the supply chain. Its software connects to ERP systems and pulls operational data about materials that go into products; the physical movements of planes, trains, and trucks; e-waste streams, and much more. It essentially creates a digital twin of the enterprise.

    Meanwhile, Tata Consultancy Services (TCS) has developed a suite of solutions, including a product called TCS Clever Energy, that tap the IoT, AI, machine learning, and the cloud to help organizations decipher intricate energy performance factors, including heating and cooling, process energy optimization, demand response, intelligent tariff management, emission management and sustainability compliances with integration to sensors, meters, and assets across the organization. It runs on the Azure Cloud platform.

    The goal, Lyons says, is to gain a deeper understanding of how various options, trade-offs, and decisions impact the carbon reduction process. As organizations delve deeper into the space, there’s also an opportunity to run simulations and identify cost savings and potential funding issues. “It’s possible to view what-if scenarios and understand their impact in 2030 or 2050. An organization can spot gaps, including funding, and identify steps to address them,” he says.

    Of course, as firms venture into the realm of Scope 3, success typically revolves around other companies sharing data, which can present obstacles. As Lyons puts it: “Right now, there’s no expectation of sharing data among companies and, in some cases, a business may do so at its peril.” He says that in order for businesses to further advance initiatives, there’s a need to develop ecosystems that allow organizations to share data securely and sometimes anonymously across partners and supply chains.

    Herman says that organizations should focus on a strategy that incorporates tools and calculators but also presses vendors to provide more detailed information about the carbon footprint of their products. While there’s a need to gather, verify and vet various methods and data to ensure that everyone and everything is in sync, the approach helps build a framework for greenhouse gas emissions reduction. Along with training and an ongoing focus on integrating data into environmental, social, and governance programs, it’s possible to adopt a framework of continual improvement and progress.

    Concludes Stanish: “We’re setting moonshot goals for greenhouse gas reduction. Organizations must adopt better tools and processes to gauge progress and deliver meaningful and actionable insights.”

    Author: Samuel Greengard

    Source: InformationWeek

  • Q&A: How does AI technology affect climate change?

    Q&A: How does AI technology affect climate change?

    With more companies building supercomputers and infrastructure that requires a lot of compute power, AI may be doing more harm than good to the planet.

    Severe wildfires, raging storms and other extreme weather conditions are all indications that the climate is changing and not for the better.

    Earlier this month, the United Nations Intergovernmental Panel on Climate Change released its sixth report on the assessment of global climate conditions. The report looks at environments that are growing warmer, rising sea levels and species becoming extinct. The warning is clear: Something must be done to save the climate.

    But some have attempted to use AI to combat climate change.

    For example, Microsoft's AI for Earth is meant to create AI projects that fight global climate change. Also, Nvidia has revealed plans to build a supercomputer that predicts climate change.

    However, the use of AI technology to counter climate change is in some ways contradictory because of the technology's tendency to consume large amounts of energy.

    In this Q&A, Neil Sahota, lead artificial intelligence advisor to the United Nations and CEO of AI vendor ACSILabs, discusses both how AI technology is helping to mitigate climate change, and the harmful effects of the technology. According to him, the key to using AI for climate change is innovative thinking.

    How is AI technology helping to combat climate change?

    Neil Sahota: There's a lot of things you can do in terms of modeling, digital twins, using AI with generative design to try to figure out new [tools] to try and remove carbon from the atmosphere. From a tool process side, AI has been helpful.

    On the flip side, all this comes with a cost. AI requires a lot of computing power, a lot of data, a lot of infrastructures, and all that does contribute to climate emissions.

    These big powerhouse servers and supercomputers that we need to enable the AI capabilities [involve] a lot of carbon that gets generated from the production. There is unfortunately some hazardous material waste in making some of these machines and then they have to be transported to the locations where these data centers are.

    Now we're building these gigantic buildings to house all these computers and power AI and cloud services.

    How can we mitigate the negative effects of AI on the global environment?

    Sahota: People are looking at more eco-friendly ways of producing computers to restrict some of the electrical consumption and emissions and the use of fans.

    Our bigger challenge is that we are so used to how computers work, or how we think they work, that we are not thinking more disruptively. We are not asking ourselves: Is there a completely different way to manufacture a computer? Should we power computers without fans or anything like that?

    It is really about finding [new] ways to actually manufacture and run servers; that's going to be the real mover for us. It is just a lot of people are not wired to think that way.

    Even if we solve the hardware side, we still need to address the software side. We're not looking at optimal ways to code and run structures because memory storage CPU power is cheap. If we pay attention to that, that will also help.

    I think [it] require more radical changes in how we develop hardware and software to reduce the impact from all our technology on the climate.

    How do you get people to think innovatively about climate change and AI technology?

    Sahota: It involves how we teach people about these tools and how to program. We are so focused on the technology and the capability enablement that we've kind of stripped out some of the infrastructure and impact concerns. And we need to reintroduce all these things and help people understand and be more consciously aware of [their impact] when we do something.

    Should there be a pause with AI innovations?

    Sahota: I am not calling for a pause. I am calling for a more proactive approach.

    The real challenge we have is we don't make that investment in fine-tuning. We must try and plan things out a little bit more to better understand [where] ripple effects come into play.

    It's just like what we see with all the cryptominers taking tons of cloud resources. All that kind of stuff takes a big environmental toll. Again, is this the most effective way to mine Bitcoin? No, we know that. But it works. That it works is not good enough.

    Do you have any final thoughts on AI technology and climate change?

    Sahota: We have a real opportunity here because as other technologies come up, talking about the metaverse and all that, it's going to exacerbate the problems.

    This is not a problem that is going to get solved magically in two years.

    Everything we do in our lives has some sort of impact. Human beings are good at dealing with that fast-moving immediate threat. That is the way we are wired.

    It is the slow-moving long-term threats that we are not good at. And if we do not start doing something about climate change, we are toast.

    Author: Esther Ajao

    Source: TechTarget

  • Reducing CO2 wth the help of Data Science

    Reducing CO2 wth the help of Data Science

    Optimize operations by shifting loads in time and space

    Data scientists have much to contribute to climate change solutions. Even if your full-time job isn’t working on climate, data scientists who work on a company’s operations can have a big impact within their current role. By finding previously untapped sources of flexibility in operations, data scientists can help shift loads to times and places where the electricity grids have a higher share of carbon-free energy, such as wind and solar. This load shifting allows the grid to transition faster to higher shares of carbon-free energy, and it can also reduces operating costs as well.

    Data Science contributions to climate solutions

    Before getting into specific opportunities in optimizing operations or infrastructure, I would like to acknowledge the broad stage that data scientists have in working on climate. Much of the current excitement about applying data science to climate has been around applications of ML and big data, and rightly so. An excellent starting point is climatechange.ai, an organization of volunteers that has built an extensive community of people who work at the intersection of climate change and AI. Their website includes summaries of each of dozens of “climate change solution domains’’ described in the 2019 paper Tackling Climate Change with Machine Learning [1]. While the solution domains are intended as a guide to high impact ML climate applications, many domains also lend themselves to more “classic” data science methods from statistics and operations research. The list of possibilities is vast, and it can be difficult to know where and how to get started. For data scientists looking to get more engaged on climate problems, either on 20% projects or in pivoting their career trajectory, the Terra.do bootcamp and the workonclimate.org Slack community are good places to meet others and find resources.

  • Supporting Sustainability with Business Intelligence and Data Analytics

    Supporting Sustainability with Business Intelligence and Data Analytics

    Digital tools and technologies are helping businesses rewire, reformulate, and repackage to support sustainability. But of course, IT needs to support those efforts.

    There’s mounting pressure on organizations of all shapes and sizes to take sustainability efforts to the next level. But while much of the focus is on IT executives to wring out inefficiencies in data centers, servers and on various devices, there’s another aspect that often winds up overlooked: the role of IT in supporting more sustainable products and services.

    Various digital tools and technologies -- including analytics, artificial intelligence and digital twins, computer aided design, machine learning, and deep learning -- can help businesses rewire, reformulate, and repackage products and services to meet the needs of different business groups, including R&D, operations, and logistics.

    For a consumer goods company, this may translate into a bottle that’s derived from plant-based materials. For an airline, it might mean moving to synthetic hydrocarbon fuels that cost less and dramatically reduce the waste stream. For a clothing retailer, it’s likely about using recycled fabrics and more sustainable materials. For just about everyone, there’s a need to reduce packaging materials.

    Make no mistake, as businesses look to improve environmental, social, and governance (ESG) metrics, reduce carbon emissions and minimize environmental impacts, IT input is crucial. Organizations require the right IT foundation -- increasingly an agile cloud-first framework -- to support ESG initiatives and unleash innovation at scale.

    “Just as digital transformation required every company to become a technology company, with technology at its heart, now every business needs to become sustainable -- and technology is again taking centerstage,” explains Sanjay Podder, managing director and technology sustainability lead at Accenture.

    Unlocking Value

    There are more than altruistic reasons to weave sustainability into the fabric of an organization. Nearly two-thirds of consumers (66%) plan to make more sustainable or ethical purchases, according to a recent Accenture and World Economic Forum report. Companies with ESG programs in the top quartile realized financial returns about 21% better than peers for a seven-year period ending in 2020. They also achieved 2.6 times higher total shareholder returns.

    Seeding technology innovation across an enterprise requires broader and deeper communication and collaboration than in the past, says Aapo Markkanen, an analyst in the technology and service providers research unit at Gartner. “There’s a need to innovate and iterate faster, and in a more dynamic way. Technology must enable processes such as improved materials science and informatics and simulations.”

    Digital twins are typically at the center of the equation, says Mark Borao, a partner at PwC. Various groups, such as R&D and operations, must have systems in place that allow teams to analyze diverse raw materials, manufacturing processes, and recycling and disposal options --and understand how different factors are likely to play out over time -- and before an organization “commits time, money and other resources to a project,” he says.

    These systems “bring together data and intelligence at a massive scale to create virtual mirrored worlds of products and processes,” Podder adds. In fact, they deliver visibility beyond Scope 1 and Scope 2 emissions, and into Scope 3 emissions. “It’s vital to understand the impact of a change both short-term and long-term, and the ripple effect resulting from various decisions and trade-offs,” Markkanen explains.

    For example, a more sustainable agricultural product used for packaging may eliminate plastic along with fuel and natural resources. Yet plant-based materials can introduce new challenges. This includes product freshness and shelf life, and different demands on the environment and various resources. It can also lead to new problems, such as developing a separate waste stream system to dispose of the bottles.

    This data framework is also crucial for identifying issues and factors that can easily fly under the radar, such as how an industry-wide shift toward a more sustainable source material -- say bamboo or used cooking oil -- impacts sourcing, pricing, transportation and shipping, and environmental concerns.

    Sustainability By the Numbers

    There’s good news. Tools and technologies now exist to support next-generation sustainability efforts and business executives have gotten the memo. Accenture found that 73% of CEOs identified “becoming a truly sustainable and responsible business” as a top priority for their organization over the next three years.

    Cloud and software providers, including AWS, Azure and Google, offer digital twin solutions -- as well as other tools to facilitate projects. It’s possible to plug in sensors and other components that gather data and run sophisticated simulations. Other technologies such as blockchain, machine learning and deep learning and various specialized design and engineering tools are also valuable and can ratchet up initiatives further.

    For example, “Blockchain provides a way to improve transparency and traceability in global supply chains and is increasingly being used to help consumers verify companies’ claims about being resource positive and environmentally friendly,” Podder points out. This information, particularly when used with and sustainability software that tracks carbon emissions, can find its way onto corporate websites, annual ESG reports and other pubic-facing systems.

    When companies get the equation right, remarkable outcomes follow. For example, Coca Cola is moving away from petroleum-based packaging. In October 2021, it unveiled a beverage bottle made from 100% plant-based material. United Airlines is transitioning to sustainable aviation fuel -- made from renewable waste such as old cooking oil and animal fat. It reduces carbon emissions by 80%. Old Navy is producing flip-flops from renewable materials, such as sugarcane and denim made from recycled cotton.

    Technology Unleashes Innovation

    The news isn’t all rosy, however. Only 7% of respondents to Accenture’s sustainable tech survey reported that they have fully integrated their business, technology and sustainability strategies. Addressing these gaps and achieving a “sustainable DNA” involves a three-step process that better links sustainability and profitably. Accenture describes this as “Diagnose, Define and Develop.”

    Not surprisingly, it all starts at the C-suite. “CIOs must have a seat at the table on sustainability decisions. But most do not. Only 49% of CIOs are empowered to help set sustainability goals, and only 45% are assessed on achieving them,” he says. Yet, it’s also vital for IT leaders to help educate other groups about various digital tools and what role they can play within an enterprise sustainability strategy.

    Make no mistake, as climate change accelerates, consumer demand for sustainable products and services increases, and the financial incentives grow, new and reformulated products and services will become the new normal. Businesses of all shapes and sizes will be required to make changes. Says Markkanen: “The tools and technology exist to innovate and iterate faster than ever.”

    Author: Samuel Greengard

    Source: InformationWeek

  • The Latest Insights From Sustainability Related Market Research

    The Latest Insights From Sustainability Related Market Research

    Environmental sustainability is a major trend impacting a broad range of industries, and many different market research publishers have released new reports covering this topic from every angle.

    Here’s a look at key insights revealed in the latest sustainability market research.

    COVID-19 Ignited a Stronger Conviction Towards Sustainability

    “While some challenges may exist regarding the relevance of sustainability in a world which appears to have been turned on its end, many of the latest findings provide evidence that sustainable ideals and attitudes have taken on a higher level of acceleration and importance in consumers’ mindset. In addition, there appears to be evidence that the COVID-19 pandemic may have ignited a stronger conviction towards environmental protection and sustainable behaviors as the fragility and interconnectedness of the human and planetary condition has been made more apparent than ever.”

    — 2022 State of Sustainability in America, 20th Annual Consumer Insights & Trends Report

    Major Corporations Demand Bolder Climate Action

    “In June this year, 70 CEOS of companies including H&M, IKEA, Unilever and Nestlé, and investors worth USD41 trillion, signed a letter demanding bolder climate action, which according to the Global Commission on the Economy and Climate could deliver at least USD26 trillion through 2030 compared with if no action was taken. With increasing pressure to disclose and minimise their impact on the climate, businesses across all industries are embracing low-carbon strategies to reduce their emissions.”

    — From Sustainability to Purpose: Climate Action

    Greater Transparency Creates Opportunities for Differentiation

    "Because consumers expect businesses to operate with people and planet in mind, they expect companies to be transparent related to the impacts of their businesses. To earn loyalty, retailers need to operate ethically and with transparency, pulling back the curtain to allow the consumer to see how the sausage is made. It requires work to provide that visibility, but it unlocks a treasure chest of new opportunity that creates competitive advantage through differentiation. Consumers will pay for products and services that are produced sustainably. They will pay to connect with the brands and people involved in creating and producing their products."

    — Retail Strategies for Sustainability Through the Lens of Product Development and Life-Cycle Management

    Real Challenges Remain for the Logistics and Supply Chain Industry

    “The logistics industry will need root-and-branch transformation over the next ten years if climate change targets are to be met. Almost two fifths of logistics industry professionals believe that net-zero goals are unachievable. Compliance is the main motivating factor for environmental initiatives. There are currently no existing alternative fuels that can rival diesel engines.”

    — Logistics & Supply Chain Sustainability Report 2021

    Insurance Industry Faces Mounting Hurdles Amid Climate Change

    “Climate change action is now an essential part of an insurer’s overall strategy. Initially it may have been viewed as good PR, but the ever-increasing nature of severe weather events around the world highlights how important making changes is to the insurance industry. Climate change is particularly damaging for the insurance industry as it leads to more claims and can make large areas of land uninsurable. While combating climate change is the long-term goal across all industries, the immediate threat is from the increasingly severe and common weather events occurring all around the world — costing insurers billions of dollars in claims.”

    — Climate Change and Its Impact on the Insurance Market – Thematic Research

    Author: Sarah Schmidt

    Source: Market Research Blog

  • Why being sustainable as an organization is a key concern for CFOs

    Why being sustainable as an organization is a key concern for CFOs

    In recent years, corporate sustainability efforts have become an important and unavoidable concern for finance executives. Jon Chorley has seen this trajectory from a unique vantage point, holding dual positions as Oracle’s chief sustainability officer and vice president of product strategy for supply chain and manufacturing.

    As the guest on Oracle’s General Ledger podcast, Chorley talked with Kimberly Ellison-Taylor, CEO of KET Solutions, about how his two (seemingly diverse) interests have become inextricably linked in the modern business landscape.

    “I personally find that a tremendous confluence of factors. A lot of things that affect sustainability also impact supply chains, and vice versa,” Chorley says. “There's no question, it's going to change the shape of all the things that we have to do.”

    Using technology to deliver more-efficient supply chains can both streamline business processes and lessen environmental impact. But today, a company’s dedication to environmental stewardship is a big concern for the CFO’s office as well.

    CFOs: Don’t discount sustainability

    Chorley suggests thinking about sustainability as a risk component—one that threatens brand damage, higher insurance rates, and a looming toll from regulators.

    As governments press toward a zero-carbon economy, there will be an enormous cost to businesses that fall behind on pollution mandates and societal standards. That’s why today we see so many large corporations transitioning parts of their businesses to respond better to new economic circumstances driven by climate change, he says.

    There’s also the matter of reporting. Of course, it’s standard practice to thoroughly report financial metrics, but with the emergence of corporate social responsibility (CSR) reports, eventually a similar standard will govern disclosures on sustainable business practices.

    “And that, obviously, is going to impact financial organizations most directly,” Chorley says. “They'll probably be held accountable or have to respond to those additional reporting requirements.”

    Finally, for companies competing for talent, especially younger employees who are extremely concerned about climate change, a poor environmental record is a recruiting liability.

    The first rule of sustainability

    These concerns aren’t the same for every finance executive; they are highly dependent on the nature of their business, supply chain issues, and economic factors in their industry. For that reason, every company must find the approach that suits its goals best.

    “I often say the first rule of sustainability for a business is to stay in business,” Chorley said. No one benefits from measures that ultimately undermine a company’s ability to be successful.

    But Oracle can offer an example of a company that’s extremely focused on business outcomes taking a leading role in navigating the global shift to a greener future.

    Fifteen years ago, when Chorley was exclusively a supply chain product manager, it became “pretty clear that sustainability and environmental factors were going to be an important consideration in Oracle and in all businesses,” he says. “It was something that we had to respond to.”

    So Chorley assembled a small group within Oracle to start thinking about environmental issues in a way that was beneficial to the larger business, sharpening the company’s focus on being a responsible corporate citizen and getting the word out on its achievements.

    That work has led to Oracle recently committing to the ambitious goal of powering all its data centers, all of the Oracle Cloud Infrastructure, as well as its office facilities, entirely with renewable energy by 2025. Oracle has also committed to being net zero in carbon dioxide emissions by 2050.

    “Whenever we look at these issues, there's always a financial component to it, as indeed, there should be,” Chorley says.

    Author: Joseph Tsidulko

    Source: Oracle

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