Microsoft for energy and resources

Achieve more in the energy and resources industry with trusted data and AI solutions

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Transforming the global energy industry is not a small feat, nor one that happens without the collective work of dedicated partnerships and innovative technology. The standardized data model and secure data sharing in Microsoft Azure Data Manager for Energy along with operations data management powered by Azure AI and Microsoft Copilot can accelerate innovation across the end-to-end CCS value chain. Copilot and Azure Data Manager for Energy put data and AI to work, integrating industry datasets, applications, and other cloud services—managing intensive workloads at global scale, and quickly ingesting data for analytics and decision-making. These are high-impact capabilities that ultimately help energy companies accelerate their transition to more sustainable practices by reducing time, costs, and risks associated with their complex operational requirements.     

Enhancing energy operations with modern data management  

Data modernization is a critical component in advancing sustainability and CCS efforts within the energy sector. By leveraging Azure Data Manager for Energy, energy companies can efficiently manage and analyze vast amounts of data—enabling more accurate and comprehensive simulations of subsurface reservoirs. This capability is essential for identifying optimal CO₂ storage locations and ensuring the safe and efficient injection and storage of carbon dioxide.  

The platform’s robust, scalable, and secure data management solutions allow for real-time data integration and continuous model refinement, which are crucial for making informed decisions and mitigating risks. Additionally, Azure Data Manager for Energy’s high-performance computing capabilities enable rapid simulations, which significantly reduce the time required for planning studies and optimizing reservoir performance. These high-impact capabilities ultimately help energy companies accelerate their transition to more sustainable practices by reducing time, costs, and risks associated with their complex operational requirements. 

Harnessing the power of AI with Copilot 

Along with data modernization and robust data analytics, Azure Data Manager for Energy users will have the option to take advantage of Copilot to interact with well data. Azure Data Manager for Energy helps ingest and organize domain-specific data from across the enterprise data landscape to enhance data access, analysis, and application interoperability. Developed in alignment with OSDU® standards, Azure Data Manager for Energy helps get the right data organized within the right domain workflow while providing trustworthy data delivery that sets the stage for improved and timely analysis.  

However, the enterprise data landscape for any analysis may extend beyond domain-specific data types and require reports with different file types, as well as images, data and records stored in other databases, spreadsheets, and shared folders. Further, the entire value chain extends into data from operations, supply chain, health, safety and environment (HSE), enterprise resource planning (ERP), legal and compliance, and even social media—some of which may be hosted on external platforms.  

In these scenarios, generative AI capabilities can help users optimize data for enhanced insights—faster. One example of how to approach this is with Microsoft Fabric, an end-to-end analytics and data platform. Fabric can help integrate the data in Azure Data Manager for Energy with other adjacent data sources, ultimately preparing it for analysis and other interactions through AI and Copilot. This means users can potentially run traditional AI-powered workflows such as automated interpretation of data or event prediction through machine learning-driven algorithms. They can also leverage Copilot to chat with the data or implement intelligent search, domain-based intelligent assistants, or cross-domain intelligent advisors.  

In doing so, end users—people in roles across geoscience or petrophysics—have an easier and faster way to interact with and query their data, both within and outside Azure Data Manager for Energy. Plus, data engineers and data scientists have a foundation from which to build similar solutions for their end users. The Copilot capabilities also mean simplified research processes and the generation of valuable data insights, enabling enterprise and business unit leaders, as well as data scientists and geophysicists, to make more informed decisions and take advantage of greater efficiencies in reservoir management.  

Optimize carbon capture and storage and enhance reservoir management 

Building on the capabilities of Copilot and Azure Data Manager for Energy, we can further optimize CCS to work towards a more sustainable future. Reservoir modeling is a critical aspect of modern energy management, playing a vital role in the underground storage of CO₂. This multidisciplinary field involves the integration of geological, geophysical, thermal, and engineering data to create detailed models of subsurface reservoirs. Reservoir engineers create models that simulate the behavior of fluids within the reservoir to predict future performance and optimize injection and production strategies. With global energy demand projected to increase 47% by 2050,² the need for sustainable energy solutions and CCS is paramount.  

Microsoft is working with partners to provide the efficiency, predictive power, and speed of reservoir simulations and optimizations. Built on top of Azure Data Manager for Energy, customers can now leverage Azure’s robust enterprise capabilities in security, scalability, and reliability, while accessing its domain-specific solutions and maintaining full control over their data.   

Traditionally, identifying optimal CO₂ storage locations requires lengthy studies, sometimes spanning months or even years. The work Microsoft is doing with partners transforms this process by enabling scalable and efficient simulations. This will enable engineers to run numerous models in parallel, leveraging high-performance computing to quickly analyze vast datasets and identify the best storage locations. The ability to perform rapid simulations at scale significantly reduces the time required for planning studies.

Explore more energy solutions and resources 

At Microsoft, our dedication and commitment to accelerating the energy transition to carbon-free resources is matched only by the power of our partner ecosystem and the knowledge-sharing that makes it all possible. With Azure Data Manager for Energy, industry leaders can connect to an open ecosystem of interoperable applications from independent software vendors (ISVs) and the Microsoft ecosystem of productivity tools. By harnessing capabilities and features from across Microsoft and partner solutions, energy leaders can optimize value across their entire enterprise while working towards sustainability goals.  

Ready to dive deeper? Check out additional resources to learn more. 

• Learn how Azure Data Manager for Energy can accelerate your journey to data modernization.
• Read the Microsoft Industry Blogs: Energy and resources  to learn about themes and actions critical for energy transition.
• Learn how to achieve more in the energy and resources industry with trusted data and AI solutions from Microsoft.

¹ McKinsey & Company, Global Energy Perspective 2024, September 2024.

² S&P Global, Global energy demand to grow 47% by 2050, with oil still top source: US EIA, October 2021.

The post Driving operational efficiency and sustainability with AI and data modernization appeared first on Microsoft Industry Blogs.

Microsoft Cloud for Sustainability

Record, report, and reduce your environmental impacts using the power of data and AI.

Try it today

Tighten your emissions goals with what-if analysis—now generally available

Conducting what-if analysis in Sustainability Manager allows organizations to evaluate their current carbon emission trends against the projected effects of altering variables within their business practices. Put simply, companies can intelligently forecast the long-term effects of altering their practices on their emissions footprint. With this GA release, the what-if analysis capability is enhanced to help businesses advance toward their objectives more quickly.  

Organizations can now extend their forecast horizons longer, based on the amount of historical data incorporated, by utilizing the what-if analysis feature. Typically, the forecast horizon spans about half the duration of the historical data used. An organization with four years of historical data, for example, can expect to see a forecast of up to two years. This allows businesses to create more informed and strategic plans for reducing their carbon footprint. By estimating the long-term effects of different emission reduction strategies, companies can help identify actions to take toward meeting reporting requirements and enhancing their progress toward goals.  

With increased customizability, organizations can select specific fields to manipulate within forecasts, rather than being restricted to the default fields available in earlier versions. Fields can also be layered together to enable the prediction and comparison of different reduction strategies’ outcomes in a single view. Up to three forecasts can be layered to help identify optimal reduction opportunities. 

Figure 1. Customizable what-if analysis allows users to alter variables to deliver more precise insights. 

With customizable what-if analysis, organizations ultimately enable greater precision and flexibility in their sustainability efforts. They can make more informed decisions, tailored to specific needs and goals, and drive more targeted progress toward reporting and long-term sustainability objectives. Moreover, through intelligent forecasting, they can preempt potential issues and sharpen strategic planning to help save time and resources. 

Figure 2. With layered forecasting, organizations can estimate and compare the outcomes of different reduction strategies in a single view. 

Strengthen analysis and decision-making with intelligent insights

Building on the predictive capabilities of what-if analysis, intelligent insights in Microsoft Sustainability Manager further assists decision-making by enabling deep, AI-driven data analysis and actionable insights. The intelligent insights capability, also now generally available, helps organizations analyze complex data patterns and drive meaning from data to make more informed decisions. This feature helps identify data trends and gaps as well as hidden opportunities for efficiency, allowing businesses to optimize costs, form targeted strategies, and make better progress. 

Used with what-if analysis to simulate different scenarios, businesses can assess the potential impact of various decisions, evaluate the outcomes of different strategies before implementation, and understand potential risks and benefits. As a result, businesses can plan more effectively and avoid potential pitfalls. 

Overall, the intelligent insights capability provides businesses with a competitive edge by enabling them to make smarter, more data-driven decisions. By leveraging AI to help analyze complex data patterns, businesses can uncover valuable insights that drive better outcomes and support long-term success. Whether it’s optimizing operations, accelerating sustainability progress, or responding to market expectations, intelligent insights offer a wealth of benefits that can help transform the way businesses operate.

Tackle multiple reporting standards with Project ESG Reporting

Project ESG Reporting (preview) offers a collection of templates, frameworks, and directives that can be populated and reused for future reports, helping organizations streamline the reporting process. These tools are designed to support organizations in their sustainability reporting journeys, making it easier to track progress, identify areas for improvement, and communicate their sustainability efforts effectively. 

New SASB templates (preview) enable drafting responses to Sustainability Accounting Standards Board (SASB) Standards across a wide array of industries. Overseen by the International Sustainability Standards Board (ISSB), SASB Standards facilitate reporting on industry-related sustainability risks and opportunities over short, medium, or long terms, across 77 industries. Get more information about the templates for SASB and other standards. 

Figure 3. Organizations can streamline the reporting process for SASB and other standards, using Project ESG Reporting (preview). 

Improve greenhouse gas calculations with DEFRA emission factors

Microsoft Sustainability Manager also now includes Department for Environment, Food, and Rural Affairs (DEFRA) 2023 and 2024 emission factors in the factor library. With DEFRA factors, organizations can calculate greenhouse gas (GHG) emissions from a range of activities, including energy use, water consumption, waste disposal, recycling, and transport activities.

Learn more about sustainability solutions with Microsoft

Bookmark Microsoft Industry Blogs: Sustainability for the latest updates, including new capabilities in Microsoft Cloud for Sustainability.    

Discover solutions with Microsoft Sustainability Manager.   

Explore the Microsoft Cloud for Sustainability Community, where you can find answers to questions and connect with peers and experts.   

See what’s new in Microsoft Cloud for Sustainability.    

The post Microsoft Cloud for Sustainability: Drive specific reduction and reporting targets with AI appeared first on Microsoft Industry Blogs.

• AI
• Energy

Learn more about how we’re making progress towards our sustainability commitments in part 1 of this blog: Sustainable by design: Innovating for energy efficiency in AI, part 1.

As we continue to deliver on our customer commitments to cloud and AI innovation, we remain resolute in our commitment to advancing sustainability. A critical part of achieving our company goal of becoming carbon negative by 2030 is reimagining our cloud and AI infrastructure with power and energy efficiency at the forefront.

We’re pursuing our carbon negative goal through three primary pillars: carbon reduction, carbon-free electricity, and carbon removal. Within the pillar of carbon reduction, power efficiency and energy efficiency are fundamental to sustainability progress, for our company and for the industry as a whole.

Explore how we’re advancing the sustainability of AI

Explore our three areas of focus

Read more 

Although the terms “power” and “energy” are generally used interchangeably, power efficiency has to do with managing peaks in power utilization, whereas energy efficiency has to do with reducing the overall amount of power consumed over time.

This distinction becomes important to the specifics of research and application because of the type of efficiency in play. For an example of energy efficiency, you might choose to explore small language models (SLMs) with fewer parameters that can run locally on your phone, using less overall processing power. To drive power efficiency, you might look for ways to improve the utilization of available power by improving predictions of workload requirements.  

From datacenters to servers to silicon and throughout code, algorithms, and models, driving efficiency across a hyperscale cloud and AI infrastructure system comes down to optimizing the efficiency of every part of the system and how the system works as a whole. Many advances in efficiency have come from our research teams over the years, as we seek to explore bold new ideas and contribute to the global research community. In this blog, I’d like to share a few examples of how we’re bringing promising efficiency research out of the lab and into commercial operations.

Silicon-level power telemetry for accurate, real-time utilization data

We’ve made breakthroughs in delivering power telemetry down to the level of the silicon, providing a new level of precision in power management. Power telemetry on the chip uses firmware to help us understand the power profile of a workload while keeping the customer workload and data confidential. This informs the management software that provides an air traffic control service within the datacenter, allocating workloads to the most appropriate servers, processors, and storage resources to optimize efficiency.

Working collaboratively to advance industry standards for AI data formats

Inside the silicon, algorithms are working to solve problems by taking some input data, processing that data through a series of defined steps, and producing a result. Large language models (LLMs) are trained using machine learning algorithms that process vast amounts of data to learn patterns, relationships, and structures in language.

Microsoft copilotTry Copilot

Simplified example from Microsoft Copilot: Imagine teaching a child to write stories. The training algorithms are like the lessons and exercises you give the child. The model architecture is the child’s brain, structured to understand and create stories. Inference algorithms are the child’s thought process when writing a new story, and evaluation algorithms are the grades or feedback you give to improve their writing.¹

One of the ways to optimize algorithms for efficiency is to narrow the precision of AI data floating-point formats, which are specialized numerical representations used to handle real numbers efficiently. Working with the Open Compute Project, we’ve collaborated with other industry leaders to form the Microscaling Formats (MX) Alliance with the goal of creating and standardizing next-generation 6- and 4-bit data types for AI training and inferencing. 

Narrower formats allow silicon to execute more efficient AI calculations per clock cycle, which accelerates model training and inference times. These models take up less space, which means they require fewer data fetches from memory, and can run with better performance and efficiency. Additionally, using fewer bits transfers less data over the interconnect, which can enhance application performance or cut network costs. 

Driving efficiency of LLM inferencing through phase-splitting

Research also shows promise for novel approaches to large language model (LLM) inference, essentially separating the two phases of LLM inference onto separate machines, each well suited to that specific phase. Given the differences in the phases’ resource needs, some machines can underclock their AI accelerators or even leverage older generation accelerators. Compared to current designs, this technique can deliver 2.35 times more throughput under the same power and cost budgets.²

Learn more and explore resources for AI efficiency

In addition to reimagining our own operations, we’re working to empower developers and data scientists to build and optimize AI models that can achieve similar outcomes while requiring fewer resources. As mentioned earlier, small language models (SLMs) can provide a more efficient alternative to large language models (LLMs) for many use cases, such as fine-tuning experimentation on a variety of tasks or even grade school math problems.

In April 2024, we announced Phi-3, a family of open, highly capable, and cost-effective SLMs that outperform models of the same and larger sizes across a variety of language, reasoning, coding, and math benchmarks. This release expands the selection of high-quality models for customers, offering practical choices for composing and building generative AI applications. We then introduced new models to the Phi family, including Phi-3.5-MoE, a Mixture of Experts model that combines 16 smaller experts into one, and Phi-35-mini. Both of these models are multi-lingual, supporting more than 20 languages.

Learn more about how we’re advancing sustainability through our Sustainable by design blog series, starting with Sustainable by design: Advancing the sustainability of AI.

¹Excerpt from prompting Copilot with: please explain how algorithms relate to LLMs.

²Splitwise: Efficient generative LLM inference using phase splitting, Microsoft Research.

The post Sustainable by design: Innovating for energy efficiency, part 2 appeared first on Microsoft Industry Blogs.

Now, we’re sharing additional learnings—from our efforts and those of our global ecosystem of partners and customers, and from advice we’ve received from external sustainability experts—in the Leader’s Guide to Sustainable Business Transformation. The guide offers practical tips to help business leaders consider what steps can help their organizations build a culture and infrastructure around ESG data, and provides context for taking the Microsoft ESG Data Readiness Assessment.

For quick examples of industry-specific considerations addressed in the guide, see the chart below.

ESG Data Readiness Assessment

Take the assessment

Leveraging the Leader’s Guide

When we began our own sustainability journey, we learned that to make progress on our ESG goals we had to bring sustainability out of siloed reporting efforts and into the core of our business. The Leader’s Guide discusses approaches to this operational shift, including ways to facilitate cross-functional conversations within your organization around the value of harnessing ESG data.

The guide also shows how Microsoft customers in different industries are using sustainability solutions to transform their operations. For example, international forestry group Södra had been limited to a labor-intensive process—siloed within its sustainability unit—to answer routine inquiries about its environmental data. Since collaborating to adopt Microsoft Sustainability Manager in 2023, Södra’s IT and sustainability teams have been generating significant insights for stakeholders, including the organization’s estimate that its positive climate impact is equal to about one-fifth of Sweden’s reported carbon dioxide emissions.

We’re ready to partner with your organization so you can also use ESG data to uncover operational insights to support your sustainability progress.

How ESG data supports business resilience

As organizations worldwide try to predict and prepare for emerging ESG disclosure requirements, they also need to respond to expanding market expectations. Investors, consumers, and shareholders are tracking companies’ sustainability commitments, and they’re looking for products and solutions that champion those commitments.

Our customer King Steel, a Taiwan-based global shoe manufacturer, faced this situation when major brands like Nike and Adidas began expecting sustainable and recyclable products. To align with its customers, King Steel started collecting and digitizing its ESG data using Dynamics 365 and capabilities within Microsoft Cloud for Sustainability. This shift to a digitized data estate not only enabled King Steel to deliver transparent data to demanding customers, it also helped the company uncover insights into materials and operations that resulted in more sustainable production, reduction of waste, and innovation of new customizable products.

By implementing a robust ESG data infrastructure, your organization can also respond to sustainability-driven market demands with speed and insights.

From commitments to solutions

Early in our journey, we quickly realized our environmental commitments necessitated better tools to manage the increasing number, size, and complexity of our ESG datasets. We also needed to unify siloed data and ensure traceability and transparency—to execute our plan to publicly self-disclose our ESG progress, and to prepare for the evolution of sustainability reporting requirements. Simultaneously, we wanted to use our ESG data to identify opportunities to drive sustainability efficiencies and business growth.

This led us to Microsoft Fabric and AI tools built on Microsoft Azure. By adopting these capabilities, we’ve now integrated our ESG, operational, and financial data, empowering our employees to access timely data intelligence so they can contribute ideas and innovate.

But to meet our ambitious sustainability commitments, we must also drive change across our value chain. In 2023, we estimated that 75% or more of our carbon footprint was coming from indirect, or Scope 3 emissions, which organizations accrue from suppliers. To address this, the Microsoft Procurement team needed customized ESG inquiries, granular data, and flexible, collaborative reporting. The team partnered with Microsoft engineers to add new capabilities to our data technologies, including low-code customization and self-service features to help our value-chain partners find ways to reduce their environmental impact.

Then we carried these robust solutions forward to our customers, so organizations like US farming powerhouse Land O’Lakes can access their ESG data for day-to-day decision-making. For example, the company relies on Azure Data Manager for Agriculture to collect and unify data on weather, soil, and irrigation—freeing Land O’Lakes data scientists to help optimize planting decisions. The Azure-based ESG data infrastructure also boosts the Land O’Lakes competitive stance by providing consumers with visibility into the organization’s farming practices and environmental outcomes.

Exploring industry-specific considerations

With the right tools, ESG data can support each industry’s unique set of goals, challenges, and opportunities.

Here’s a look at some of the issues our Leader’s Guide and ESG Assessment can help you start exploring:

Visit the Leader’s Guide for in-depth information and resources.

Next steps

As you rethink operations to support your organization’s sustainability progress, we’re ready to share our learnings and continuous innovation to help advance your ESG priorities, accelerate your growth, and partner for a shared sustainable future.

The post Driving business value with ESG data readiness appeared first on Microsoft Industry Blogs.

Earlier this summer, my colleague Noelle Walsh published a blog detailing how we’re working to conserve water in our datacenter operations: Sustainable by design: Transforming datacenter water efficiency, as part of our commitment to our sustainability goals of becoming carbon negative, water positive, zero waste, and protecting biodiversity.

At Microsoft, we design, build, and operate cloud computing infrastructure spanning the whole stack, from datacenters to servers to custom silicon. This creates unique opportunities for orchestrating how the elements work together to enhance both performance and efficiency. We consider the work to optimize power and energy efficiency a critical path to meeting our pledge to be carbon negative by 2030, alongside our work to advance carbon-free electricity and carbon removal.

The rapid growth in demand for AI innovation to fuel the next frontiers of discovery has provided us with an opportunity to redesign our infrastructure systems, from datacenters to servers to silicon, with efficiency and sustainability at the forefront. In addition to sourcing carbon-free electricity, we’re innovating at every level of the stack to reduce the energy intensity and power requirements of cloud and AI workloads. Even before the electrons enter our datacenters, our teams are focused on how we can maximize the compute power we can generate from each kilowatt-hour (kWh) of electric power.

In this blog, I’d like to share some examples of how we’re advancing the power and energy efficiency of AI. This includes a whole-systems approach to efficiency and applying AI, specifically machine learning, to the management of cloud and AI workloads.

Driving efficiency from datacenters to servers to silicon

Maximizing hardware utilization through smart workload management

True to our roots as a software company, one of the ways we drive power efficiency within our datacenters is through software that enables workload scheduling in real time, so we can maximize the utilization of existing hardware to meet cloud service demand. For example, we might see greater demand when people are starting their workday in one part of the world, and lower demand across the globe where others are winding down for the evening. In many cases, we can align availability for internal resource needs, such as running AI training workloads during off-peak hours, using existing hardware that would otherwise be idle during that timeframe. This also helps us improve power utilization.

We use the power of software to drive energy efficiency at every level of the infrastructure stack, from datacenters to servers to silicon.

Historically across the industry, executing AI and cloud computing workloads has relied on assigning central processing units (CPUs), graphics processing units (GPUs), and processing power to each team or workload, delivering a CPU and GPU utilization rate of around 50% to 60%. This leaves some CPUs and GPUs with underutilized capacity, potential capacity that could ideally be harnessed for other workloads. To address the utilization challenge and improve workload management, we’ve transitioned Microsoft’s AI training workloads into a single pool managed by a machine learning technology called Project Forge.

Currently in production across Microsoft services, this software uses AI to virtually schedule training and inferencing workloads, along with transparent checkpointing that saves a snapshot of an application or model’s current state so it can be paused and restarted at any time. Whether running on partner silicon or Microsoft’s custom silicon such as Maia 100, Project Forge has increased our efficiency across Azure to 80% to 90% utilization at scale.

Safely harvesting unused power across our datacenter fleet

Another way we improve power efficiency involves placing workloads intelligently across a datacenter to safely harvest any unused power. Power harvesting refers to practices that enable us to maximize the use of our available power. For example, if a workload is not consuming the full amount of power allocated to it, that excess power can be borrowed by or even reassigned to other workloads. Since 2020, this work has recovered approximately 800 megawatts (MW) of electricity from existing datacenters, enough to power approximately 2.8 million miles driven by an electric car.¹  

Over the past year, even as customer AI workloads have increased, our rate of improvement in power savings has doubled. We’re continuing to implement these best practices across our datacenter fleet in order to recover and re-allocate unused power without impacting performance or reliability.

Driving IT hardware efficiency through liquid cooling

In addition to power management of workloads, we’re focused on reducing the energy and water requirements of cooling the chips and the servers that house these chips. With the powerful processing of modern AI workloads comes increased heat generation, and using liquid-cooled servers significantly reduces the electricity required for thermal management versus air-cooled servers. The transition to liquid cooling also enables us to get more performance out of our silicon, as the chips run more efficiently within an optimal temperature range.

A significant engineering challenge we faced in rolling out these solutions was how to retrofit existing datacenters designed for air-cooled servers to accommodate the latest advancements in liquid cooling. With custom solutions such as the “sidekick,” a component that sits adjacent to a rack of servers and circulates fluid like a car radiator, we’re bringing liquid cooling solutions into existing datacenters, reducing the energy required for cooling while increasing rack density. This in turn increases the compute power we can generate from each square foot within our datacenters.

Learn more and explore resources for cloud and AI efficiency

Stay tuned to learn more on this topic, including how we’re working to bring promising efficiency research out of the lab and into commercial operations. You can also read more on how we’re advancing sustainability through our Sustainable by design blog series, starting with Sustainable by design: Advancing the sustainability of AI and Sustainable by design: Transforming datacenter water efficiency. 

For architects, lead developers, and IT decision makers who want to learn more about cloud and AI efficiency, we recommend exploring the sustainability guidance in the Azure Well-Architected Framework. This documentation set aligns to the design principles of the Green Software Foundation and is designed to help customers plan for and meet evolving sustainability requirements and regulations around the development, deployment, and operations of IT capabilities.   

¹Equivalency assumptions based on estimates that an electric car c

The post Sustainable by design: Innovating for energy efficiency in AI, part 1 appeared first on Microsoft Industry Blogs.

Azure Data Manager for Energy

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Enabling energy industry innovation through modern technology

The process of finding suitable CCS sites is costly and time consuming, and not without its own unique information security risks. Traditional energy industry technologies used during this process both increase in cost over time and contribute to the data silos that exist between the site selection process and operational concerns like site-specific safe liquid CO2 injection speeds and storage capacities. These factors have led to challenging commercial margins of CCS as a process, presenting a barrier to entry for many interested businesses.

The process is not unfamiliar to Microsoft, which has already invested in multiple large-scale CCS projects around the world, including Northern Lights, a partnership between the Norwegian government and energy companies Equinor, Shell, and TotalEnergies. Northern Lights was created to help accelerate the decarbonization of European industry and mitigate its otherwise unavoidable emissions. The project facilitates the capture and transport of industrial CO2 emissions, which it then liquifies and stores safely in the pores of saline aquifers 2,600 meters below the seafloor.

By 2030, Microsoft plans to have an established system that removes five million metric tons of carbon from the atmosphere each year. With Azure Data Manager for Energy and operations data management powered by Azure AI and Microsoft Copilot, Microsoft aims to help increase the return on investment (ROI) of CCS projects, helping customers optimize their costs with AI, automation, and the discovery of new best practices. Additionally, organizations can employ Microsoft Cloud for Sustainability—a growing set of powerful data and AI capabilities designed to help businesses create more accurate and reliable data intelligence to drive impact reduction efforts and business transformation. These solutions help users gain actionable insights to drive sustainable practices, providing visibility into sustainability performance with advanced analytics and reporting. The global Microsoft partner network, with its industry specific expertise and highly targeted CCS solutions, further strengthens these capabilities, providing customers with valuable resources and support

The path forward for carbon capture storage

There are two divergent paths ahead for the emerging CCS industry, both recursive in nature. On the first and more positive path, companies will see a clear value in negating and offsetting their carbon emissions efficiently and effectively. On the other path, companies could lack the tools that efficiently connect the dots between carbon emissions and offsets, and hence be left with a less clear value proposition. By underpinning the positive path with technology, Microsoft hopes to help industry and humanity at large meet their shared sustainability goals.

Azure Data Manager for Energy is aligned with the highly secure OSDU® and OPC Unified Architecture (OPC UA) data standards, which will ease the development of new services and workflows that transcend today’s data silos. This standardization also paves the way for the adoption of co-pilots and other time-saving AI solutions. Combining Azure Data Manager for Energy with other services, such as Microsoft Fabric, Environmental Credit Service, and Microsoft Sustainability Manager, helps organizations in the energy industry validate and demonstrate their CCS efforts and carbon credit purchases to regulators in the rapidly emerging and expanding ICM business.

Sustainability data solutions in Fabric offer unique capabilities that provide prebuilt and preconfigured Fabric resources. These resources include data stores in the form of data lakes, prebuilt notebooks, and dashboards to ingest, process, aggregate, and display data for various ESG scenarios. By combining and transforming disparate social and governance data into a standardized data lake, organizations can compute, analyze, and disclose social and governance metrics effectively. 

How scalability, standardization, and security contribute to sustainability

Data standardization and AI readiness are the first steps toward innovative capabilities, especially when paired with the hyper-scalability of Azure. During the process of identifying ideal sites for carbon storage, energy companies run multiple site-specific simulations that traditionally include the manual numerical simulation of seismic data. These simulations are time consuming, complex, and data intensive. They’re also critical to the site selection process, so when companies are given the opportunity to infuse them with AI and run them at scale, there’s massive potential for time savings and efficiency gains.

The ability to scale up the computing power required to run thousands of simulations against hundreds of potential sites when required could help shorten the CCS site selection process substantially. It could also help refine the simulations and their related data models and lead to further efficiency gains. Scaling compute back down after the simulations have been run can help energy companies not only reduce their costs, but also reduce the same carbon footprint the CCS process is helping to address. By running the simulations on Azure, energy companies are taking advantage of hyper-scalability on a cloud that has itself been carbon neutral since 2012.

After months of work going into the selection and analysis of a proper CCS site, energy companies want to make sure their data is not just secure but fully under their own control. If that information were to leak to either the public or their competitors, all that effort and investment could be lost. For this reason, Microsoft is working toward enabling Azure Data Manager for Energy on customer cloud tenants, which will grant them the control they require as well as the layered security of Microsoft managed services in the cloud. For real-time CCS operations data, Microsoft is also developing a reference architecture and toolkit to enable partners to build ICM solutions to deliver value to our customers. 

Clearer skies ahead

With Azure Data Manager for Energy and the power of Azure AI, Microsoft Copilot, and capabilities from Microsoft Cloud for Sustainability, Microsoft hopes to give the energy industry the standardization and systemization that its past technologies may not have provided. To keep global warming within 1.5 degrees, the United States Department of Energy’s Pacific Northwest National Laboratory reports that the world needs to start removing 10 gigatons of CO2 from the atmosphere annually by 2050.¹ To reach that important milestone in time, the energy industry needs a technological foundation to build its next wave of advancements upon.

If, as the Clean Air Task Force states, Europe alone has the storage capacity for 1,520 gigatons of carbon dioxide emissions, helping energy companies rapidly, cost-effectively identify and provision CCS sites is a big step in the right direction, and one which Microsoft hopes to help the energy industry take.²

Explore more on carbon management

• Discover how Microsoft is powering the future of energy with Azure Data Manager for Energy.
• Learn more and connect with us at upcoming energy events:
  • Image: August 24–25, 2024, in Houston, Texas
  • ONS: August 26–29, 2024, in Stavanger, Norway
  • SLB Digital Forum: September 16–19, 2024, in Monte Carlo, Monaco
• Find out more about Industrial Carbon Management.

¹Diverse Approach Key to Carbon Removal, Pacific Northwest National Laboratory, 2023.

2Unlocking Europe’s CO2 Storage Potential, Clean Air Task Force, 2023.

The post Enabling carbon reduction in the energy industry appeared first on Microsoft Industry Blogs.

In India, one of the world’s largest agricultural producers, the sector sustains over 43% of India’s workforce.¹ However, many Indian farmers face challenges due to limited access to crucial information and agronomic expertise. This gap can hamper their ability to access time-sensitive information, like changes in monsoon patterns, making it even more challenging to adapt to the rapidly growing demand for agricultural products. As India’s agricultural landscape evolves, leveraging generative AI not only supports the shift away from harmful pesticides and fertilizers, but it also helps farmers boost efficiency. 

Azure Data Manager for Agriculture

Create a more sustainable future by innovating with agriculture data

Learn more

Copilots: Working toward sustainable change 

Azure Data Manager for Agriculture is a powerful tool designed to enhance agricultural practices by leveraging high-quality datasets and AI capabilities. This platform connects farm data from various sources, enabling organizations to develop innovative solutions that provide valuable insights into farming operations. With Microsoft copilot templates, organizations easily create custom copilots to seamlessly retrieve and analyze data in natural language—making it easier to gain actionable insights. Microsoft supports its customers and partners by offering comprehensive tools and resources, fostering collaboration, and driving innovation across the agricultural value chain. Microsoft is working closely with customers like ITC, a versatile Indian multi-business company, to optimize agricultural decision-making and promote sustainable farming practices. 

ITC is deeply committed to sustainability and the welfare of small holder farmers, and they have developed Krishi Mitra, aptly named “farming friend.” This agricultural super app, created using Microsoft’s copilot template, enables farmers to ask questions in their own language and uses generative AI plugins to provide answers on weather and agronomy. By incorporating natural language chat functionality powered by generative AI, Krishi Mitra offers tailored guidance on crop management, pest control, soil health, water conservation, and more. Additionally, Microsoft language localization tools enable the app to cater to a diverse linguistic audience, ensuring that farmers across various regions can access crucial farming information in their preferred language. 

Microsoft is working closely with partners like ITC to extend Azure Data Manager for Agriculture. Supporting farmers by providing AI-powered tools, Microsoft and its partners are working together to provide optimized agricultural decision-making. ITC plans to bring generative AI to over 100,000 farmers in India by end of 2024, with an anticipated user base of around 10 million by 2030. Plans include integrating the copilot with Azure Data Manager for Agriculture in subsequent phases, allowing for access to a wide range of additional data sources.

A streamlined development process using plugins 

The development process of Krishi Mitra was streamlined using orchestrated plugins, which access specific functionalities—such as weather data and farming advice. This method ensures a flexible and efficient user interface from ITC, eliminating the need for substantial modifications to the core system architecture. Moreover, the application of contextual indexing and retrieval-augmented generation (RAG) techniques has significantly refined the quality of the app’s responses. 

Krishi Mitra’s queries are meticulously processed by a Semantic Kernel-based orchestrator, which then gets responses from Microsoft plugins. This feature empowers farmers to pose questions on weather forecasts and get agronomic advice for crops while the app identifies and utilizes the most suitable plugin to retrieve the optimal answer for each inquiry. This seamless integration and user-friendly interface are what set Krishi Mitra apart, making it an essential tool for farmers aiming to enhance their agricultural efficiency and outcomes. 

Boost productivity and profitability with AI 

In addition to conventional farming challenges such as soil fertility and climate, many farmers contend with limited access to agricultural technology and relevant information that can support their work. Krishi Mitra delivers a comprehensive array of benefits to farmers by equipping them with the necessary tools and information to refine their agricultural practices and market strategies. The app’s core objective is to provide instantaneous access to critical information, boosting the productivity and profitability of smallholder farmers while promoting sustainability and climate resilience.  

In 2021, approximately 61,000 metric tons of pesticides were used in India for agricultural purposes.² Some pests that were once minor have become major threats thanks to rising temperatures that alter insect-crop interactions. With access to Microsoft AI tools, Krishi Mitra can continuously learn and adapt from new agricultural data and user interactions. This feature allows the app to improve its recommendations and stay updated with the latest farming techniques and information, helping farmers stay ahead of pest issues and use fewer pesticides when they catch problems early. 

Personalized data enhances farming opportunities  

Maximizing profits for small farmers hinges on determining the optimal harvest time to ensure crops are of the highest quality and yield, while also capitalizing on the best market prices. Krishi Mitra empowers farmers with immediate access to essential information like precise weather forecasts, enabling farmers to align their farming operations with upcoming weather conditions. Additionally, it provides comprehensive market insights, including detailed data on market locations, pricing, and other critical factors. Data like this helps farmers make strategic decisions regarding irrigation, the timing of their harvests, and choosing the most profitable buyers located nearest to their farms.  

The diversity of languages in India has traditionally posed challenges to widespread technological adoption among farmers. Krishi Mitra addresses this barrier with its capability to process natural language queries and offer translations in local languages. This functionality allows farmers to use their smartphones not just for communication but as a tool for receiving actionable farm management advice in a language they understand. The app’s personalized advisories are tailored to meet the specific needs of each farmer, ensuring that the guidance they receive is not only relevant but comprehensible. This personalized support is instrumental in improving agricultural yields and subsequently increasing the income of the farmers, truly making Krishi Mitra a transformational tool in the hands of the Indian agricultural community. 

Discover agriculture solutions 

• Learn more about Azure Data Manager for Agriculture features.
• Explore Microsoft Cloud for Sustainability solutions for agriculture.
• Learn about Headstorm’s AgPilot tool.

¹ World Bank Group, Employment in agriculture (% of total employment)(modeled ILO estimate)—India, February 2024.

² Statista, Volume of pesticides used for agriculture in India from 2011 to 2021, March 2024.

The post AI in the fields: Copilot powers smarter farming appeared first on Microsoft Industry Blogs.

In this blog, we explore the capabilities of this management tool and how it helps simplify reporting on multiple levels. Features include a variety of user-friendly templates, workflow management, and extensibility that accelerate the reporting process and boost accuracy. In addition, we look at a new data trail capability in Microsoft Sustainability Manager that improves transparency in data flow and an alternate emissions feature that helps people accurately quantify emissions. Lastly, for game creators, we revisit the Xbox Developer Sustainability Toolkit, released in 2023, to see how it is helping pinpoint and reduce energy usage for gamers. 

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Simplify the complexities of ESG disclosure

ESG disclosure reporting can be a complex and challenging process for companies. For example, there is no global standardization in ESG reporting, which makes it difficult to know what metrics to report and how to structure disclosures. Organizations are facing challenges as they aim to report against numerous voluntary and regulatory reporting frameworks.  

Project ESG reporting (preview) solves these challenges by enabling customers to create, complete, and approve reports based on multiple ESG disclosure standards across quantitative and qualitative metrics. The solution offers templates, frameworks, and directives that can be populated and subsequently re-used for future reports, reducing the overall reporting process for years to come. The templates can be customized with flexible data input options—from numeric to rich text—to build a comprehensive report and provide accurate insight into an organization’s ESG performance. Customers also have the option to bring in their own templates. Additionally, they can use collaboration and approval workflows to enhance data quality and consistency.  

The solution focuses on multiple areas that simplify the challenges inherent in reporting, across industries. This includes reducing complexity, enhancing efficiency, and providing greater transparency.

Key features include:   

1. Variety of standard templates. To save our customers time and effort, we included a range of ESG standard and framework templates:
   • Corporate Sustainability Reporting Directive (CSRD)
   • Australian Sustainability Reporting Standards (ASRS)  
   • Business Responsibility and Sustainability Reporting (BRSR) 1 and 2 
   • Global Reporting Initiative (GRI) 
   • International Financial Reporting Standards (IFRS) 1 and 2  
   • Numerous Sustainability Accounting Standards Board (SASB) templates 
2. Microsoft Sustainability Manager integration for company profile and CSRD data points  
3. Workflow UI for task management and content approval   
4. Disclosure generation in Excel  
5. Extensibility for custom template creation

Explore our collaborative end-to-end ESG reporting solution.

Follow the workflow of data with Microsoft Sustainability Manager to make better decisions

Sustainability data helps company leaders make informed decisions about sustainability with their apps. To maximize the value of that data, we’ve given Microsoft Sustainability Manager data trail capabilities. This feature covers the entire data lifecycle—from ingestion to reconciliation—providing a complete representation of the data flow. Capabilities include a comprehensive preparation report providing the data trail across different time periods and organizational hierarchies. 

Features include: 

• Understanding how data moves and changes in the app (such as who is responsible for the data, data quality, and the outcome of using data) 
• Visibility into each stage of the data journey, delivering a clear, end-to-end view of sustainability in data flow, transformations, and calculations
• Streamlining data access, traceability, and auditability  

Having a data trail helps companies more easily handle the constantly changing regulatory requirements for data traceability and auditability. For auditors, investors, and stakeholders, it also builds trust. 

Learn more about generating a data trail report.

Create separate emissions versions specific to reporting standards or accounting methods

The regulatory landscape is complicated and continues to evolve. The alternate emissions feature in the Microsoft Sustainability Manager calculations engine empowers customers to accurately quantify their emissions using diverse calculation methodologies. The tool generates alternative emission reports tailored to the requirements of different regulatory bodies or regional reporting standards. Users leverage the same activity data, tailoring emission calculations to specific emission scopes and classifications. This can enhance operational efficiency and mitigate risks associated with non-compliance or inaccurate reporting.

The feature’s flexibility simplifies maintaining compliance with regional or industry-specific reporting standards and variations and ever-evolving regulations. Users can configure multiple emission calculation methodologies for each emission category (Scope 1, Scope 2, Scope 3) and its underlying activity data. That includes the ability to choose destination or classification of emissions along with the output activity category within the calculation model. Such capabilities enable the generation of parallel emission reports for different regulatory bodies, regional standards, and customer requests. Users will also be able to filter emission records based on approach or calculation methodology and visualize the alternate results according to methodology or purpose.  

Learn more about calculating emissions for different standards (preview).

Get the latest factor library updates 

Microsoft Sustainability Manager has added new emission factors to the factor library that you can seamlessly import. They are: 

• National Greenhouse and Energy Reporting (NGER) database: Microsoft Sustainability Manager integrates with the NGER database, enabling users to access accurate and up-to-date emission factors. These factors are essential for calculating greenhouse gas emissions associated with various activities, products, and processes.  

• Environmental Protection Agency (EPA) factors for 2024: The EPA regularly updates emission factors based on scientific research and industry trends. Microsoft Sustainability Manager has automatically incorporated the latest EPA factors for 2024, ensuring accuracy and compliance with regulatory standards. 

Encourage game creators to create sustainability goals

Reducing the impact of gaming on the environment requires a collaborative effort. Working closely with studio partners, we’ve done that with the Xbox Sustainability Toolkit. To date, we’ve already seen great success with games like Halo Infinite, Fortnite, and Call of Duty.  

Our game creator stories show that identifying and implementing energy efficiency opportunities in game development doesn’t have to be expensive or time intensive. The results can reduce console energy consumption, carbon emissions, and in-home electricity costs for gamers. The energy optimizations help game creators achieve sustainability goals without disrupting players. Visit Microsoft Game Dev Docs to learn more about our partner collaborations and the toolkit.  

We’ll continue to add to the Xbox Sustainability Toolkit as we expand our number of studio partners. We’ll also continue to contribute and participate in the United Nations Playing for the Planet Alliance to support sustainable game design.  

To learn more, visit Gaming Sustainability. 

Learn more about sustainability solutions with Microsoft  

• Bookmark Microsoft Industry Blogs: Sustainability for the latest updates, including new capabilities in Microsoft Cloud for Sustainability.   
• Discover solutions with Microsoft Sustainability Manager.  
• Explore the Microsoft Cloud for Sustainability Community, where you can find answers to questions and connect with peers and experts.  
• See what’s new in Microsoft Cloud for Sustainability. 

The post Streamline ESG disclosures with new and expanded reporting solutions appeared first on Microsoft Industry Blogs.

Last month, we unveiled our Datacenter Community Pledge, emphasizing that datacenters are not only the backbone of modern technology but also a force for good in the communities they serve. As part of this commitment, at Microsoft we recognize our crucial role in protecting and replenishing freshwater resources both in the regions where we operate and around the world.

That’s why in our datacenter operations, one of the essential engineering questions we ask each day is: how can we continue to conserve water while meeting growing customer demand for cloud and AI innovation?

In datacenters, water is primarily used for cooling and humidification. As demand for high performance cloud and AI applications has grown over the past few years to fuel customer applications and enable a new frontier of discovery and innovation, so have the power requirements for silicon chips—the basic building blocks of cloud and AI computing—that sit within the racks and servers of datacenters. Because advanced chips typically utilize more power, they also generate more heat. To prevent the chips from malfunctioning, more intensive cooling is needed, and this has historically required consuming water.

To reduce the water required for operations, a critical path to our company goal of becoming water positive by 2030, we’re innovating everywhere from our datacenter buildings all the way to the chips. Collectively, this work is delivering substantial results. From our first generation of owned datacenters in the early 2000s to our current generation in 2023, we have reduced our water intensity (water consumed per kilowatt-hour) by over 80%. This shows that it’s possible to significantly reduce how much water our datacenters use per kilowatt of power even as our cloud infrastructure expands.

Today, we are sharing more about two focus areas for continuing to drive down water intensity: (1) conserving water at every stage of operations, and (2) innovative technologies that reduce the amount of water needed for cooling.

Conserving water at every stage of operations

At all locations, we work to minimize the amount of water we require for cooling. This includes operating our datacenters at a temperature that allows us to cool with outdoor air the majority of the year, reducing the need for ambient cooling, and conserving water at every stage of day-to-day operations.

We conduct regular audits of our datacenters to identify inefficiencies and areas where design and day-to-day use don’t align. Our 2022 audit resulted in targeted improvements that eliminated 90% of the instances in which excess water was used. In addition, we’re building advanced prediction models that help us anticipate water requirements based on real-time weather and operational data. Comparing anticipated needs to actual consumption patterns enables us to quickly identify inefficiencies, such as water leaks that may otherwise go unnoticed.

To minimize freshwater requirements from municipal water systems, we employ conservation strategies that are tailored to the bioregion of the datacenters. For example, in Texas, Washington, California, and Singapore we’ve expanded our use of reclaimed and recycled water. In the Netherlands, Ireland, and Sweden we’re harvesting rainwater, and we’re also bringing this capability to new datacenters in Canada, the United Kingdom, Finland, Italy, South Africa, and Austria.

Innovative technologies that reduce the water needed for cooling

Advancing sustainabilityLearn more

Innovative cooling technologies are essential to Microsoft’s water strategy, and we are rapidly expanding proven solutions across our datacenter portfolio. This includes solutions that bring cooling directly to the source of heat generation—the chip itself.

Cold plates are a prime example of this: a direct-to-chip cooling technology that provides heat exchange in a closed loop system. Cold plates dissipate heat more effectively than traditional air cooling, directly chilling the silicon and then recirculating the cooling fluid, like a car radiator. This solution significantly improves cooling efficiency and enables more precise temperature control compared to traditional methods.

To harness the increased efficiency cold plates offer, we’re developing a new generation of datacenter designs optimized for direct-to-chip cooling, which requires reinventing the layout of servers and racks to accommodate new methods of thermal management as well as power management. In existing datacenters, we’re also using innovations like the ‘sidekick,’ a liquid cooling system we’re already using adjacent to racks of Microsoft Azure Maia AI Accelerator chips, circulating fluid to draw heat away from the cold plates attached to the surface of the chips.  

We’re also evolving cold plate technologies through our work with microfluidics, a technology that brings cooling inside the silicon by integrating tiny fluid channels into chip designs. Embedding the liquid cooling inside the chip brings the coolant right next to the processors, resulting in even more efficiency and precision.

Our newest datacenter designs are optimized to support AI workloads and consume zero water for cooling. To achieve this, we’re transitioning to chip-level cooling solutions, providing precise temperature cooling only where it’s needed and without requiring evaporation. With these innovations, we can significantly reduce water consumption while supporting higher rack capacity, enabling more compute power per square foot within our datacenters.

Reducing global water use through partnership, investing to replenish water

Our water positive goal guides us to consider not only how we can shift our business practices to reduce our water footprint but also how this work can benefit customers and partners working toward similar goals. The five pillars of water positive: reduction, replenishment, access, innovation, and policy all play important roles in our water positive journey.

Over the past year, we grew our water replenishment program significantly, nearly doubling our water replenishment portfolio to include more than 49 replenishment projects around the world. Together, these have the potential to replenish more than 24,000 Olympic size swimming pools over the lifetime of the projects. We also met our 2030 water access target to provide 1.5 million people with access to clean water and sanitation services.²

In addition, we’re working to reduce global water use by collaborating with customers, partners, local communities and municipalities to advance water infrastructure and policy around the globe. Because corporate approaches to water management generally lag investments in carbon reduction¹, we’re taking an active role in championing effective and innovative water management practices and water policies. Some of our advocacy projects include: (1) serving on a coalition to increase water reuse and recycling across the United States, (2) funding projects that support Tribal Nations and state governments in increasing water security, and (3) supporting research, analysis, and advocacy on water in the European Commission.

Learn more about how Microsoft is advancing sustainability

Learn more about how we’re advancing sustainability through our Sustainable by design blog series, starting with Sustainable by design: Advancing the sustainability of AI. For more information on our progress towards our sustainability goals, read the Microsoft 2024 Environmental Sustainability Report.

Explore Microsoft’s approach to water replenishment

¹Why investment in water is crucial to tackling the climate crisis, World Economic Forum, 2024.

²2024 Environmental Sustainability Report, Microsoft.

The post Sustainable by design: Transforming datacenter water efficiency appeared first on Microsoft Industry Blogs.

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In this blog, we explain how creating scorecards and goals empowers you to curate sustainability metrics and track against your organization’s key business objectives. We also share other recent updates to Microsoft Cloud for Sustainability designed to help you manage, track, report, and gain better insight into your sustainability data. 

Use scorecards and goals to achieve your sustainability objectives

Sustainability reporting can be a complex process. Sustainability Manager includes a new capability that simplifies the process, making it more accessible and manageable for you to communicate your organization’s sustainability achievements. With scorecards and goals, you can curate your organization’s sustainability metrics and track them against your organization’s business objectives. 

Create a scorecard, which you can use to chart your organization’s sustainability metrics, encapsulate them within a scorecard, and designate an owner to guide its advancement. 

Create goals, the benchmark of your organization’s sustainability trajectory, which can be seamlessly integrated with the scorecards. These goals, whether entered manually or derived from interconnected data streams, provide a dynamic framework for sustainability targets, adaptable to the shifting tides of your organization’s needs. 

Using the scorecards and goals feature, you can mark goals as aligning to the Science Based Targets initiative (SBTi), giving your organization the ability to highlight the scientific rigor and global recognition of its sustainability efforts. By including a baseline year, the goal-setting process deepens, offering a historical perspective from which you can measure and assess progress. Finally, the dual capability of manual updates or automated system tracking enables you to not only set but actively pursue and achieve your organization’s sustainability goals.  

The scorecards and goals capability transcends the mere establishment of targets, fostering a culture of engagement and accountability. It provides a centralized platform for setting, monitoring, and updating sustainability goals, which is crucial for accurate disclosure reporting. With the ability to connect goals to data sources, you can ensure that your organization’s reporting is data-driven and reflects real-time progress towards its sustainability targets. This feature simplifies the complex process of sustainability reporting, making it more accessible and manageable for organizations of all sizes to communicate their sustainability achievements transparently to stakeholders.  

Calculate emissions using IEA factors within Sustainability Manager 

Multinational organizations can now calculate emissions using International Energy Agency (IEA) emission factors within Sustainability Manager, with some restrictions as governed by IEA. Using the IEA factors can help you understand your organization’s carbon footprint and develop strategies to reduce emissions, as well as help with regulatory compliance, risk management, and cost reduction. 

The IEA factors library is available to download from Microsoft Cloud Solution Center. The IEA emission factors are available to use alongside all other emission factor libraries within Sustainability Manager. This feature is available within Sustainability Manager Premium.

Learn how to calculate emissions with the IEA emissions feature. 

Create and associate meter entities with a facility within Sustainability Manager 

For Scope 1 and Scope 2 emission categories, customers collect utility consumption data from utility providers through bills and, in some cases, through real-time devices like meters. The consumption reported in utility bills and real-time devices are recorded through utility meters (per collection device configuration). 

Now deprecated, Sustainability Manager previously included an optional meter text attribute for purchased energy and stationary combustion. However, since the consumption is recorded at a facility level and the meter is the device used to record this consumption for each facility, the meter must be associated with a facility within Sustainability Manager. 

You can now create and associate multiple utility meters (entities) with the facility entity in Sustainability Manager. This will enable you to track and report energy consumption for emissions calculations, as well as water usage at a facility level within your organization. 

Note that reports by meter is a future enhancement. In the meantime, you can use custom reports to add meter-based pivot views. 

Transfer data connections across deployments 

Sustainability Manger includes advanced ingestion capabilities. A connection is made of several parts:   

• The data source connectivity specifications  
• Mode of ingestion such as Power Query, Excel, or from a custom data provider  
• Mapping of source shape to the Sustainability Manager data model  
• Execution context, such as scheduling  

Enterprises need repeatable, verifiable processes across deployments; so, once a connection is specified, it can be transferred across deployments or environments. Now, environment administrators can use application lifecycle management (ALM) with Microsoft Power Platform to transfer connections across environments.   

Learn more about how to copy connections from one environment to another. 

Gain insights into your organization’s sustainability progress with Microsoft Copilot Studio templates 

The Sustainability Insights Copilot template (preview) was recently added to Copilot Studio. The template enables you to get insights and see data about your organization’s sustainability goals and progress and can be tailored to suit your organization’s specific needs. Information can be publicly shared in the form of reports, documents, and records. For example, a company’s sales and marketing professionals might be required to respond to queries from customers about the company’s sustainability progress on various sustainability fronts like measuring across environmental metrics, social and governance stats and indexes, energy meters, pollution indexes, and biodiversity impact.  

You can create and deploy a Sustainability Insights Copilot template as you would for any other Copilot template in Copilot Studio. 

Once deployed, your copilot is ready to field questions.  

You can configure the template with more sources of knowledge and other system of records, leveraging connectors to respond to related queries better.  

Enhanced Scope 3 categories now generally available in Sustainability Manager 

We’re excited to announce that Sustainability Manager has successfully completed the verification process for several Scope 3 categories of the Greenhouse Gas (GHG) Protocol. The following categories are now generally available:  

• Category 3: Fuel-and energy-related activities  
• Category 10: Processing of sold products  
• Category 11: Use of sold products  
• Category 14: Franchises  
• Category 15: Investments 

This update spans across various features, including import, activity data, calculations, and documentation, ensuring a seamless user experience.  

The verification process was comprehensive, involving a rigorous assessment and validation of data, methodologies, and calculations related to these Scope 3 categories. Independent experts conducted a thorough review to ensure accuracy, consistency, and compliance with industry standards.  

We’re committed to providing you with reliable and transparent tools to manage your sustainability efforts. The general availability of these enhanced Scope 3 categories marks a significant milestone in our journey towards empowering organizations to achieve their environmental goals. 

Learn more about sustainability solutions with Microsoft 

• Bookmark Microsoft Industry Blogs: Sustainability for the latest updates, including new capabilities in Microsoft Cloud for Sustainability.  
• Discover solutions with Microsoft Sustainability Manager. 
• Explore the Microsoft Cloud for Sustainability Community, where you can find answers to questions and connect with peers and experts. 
• See what’s new in Microsoft Cloud for Sustainability June 2024.

Want to learn more about Microsoft Cloud for Sustainability? Sign up for news and updates. 

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