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Business leaders want to ensure that their organizations do their part to address the impact of climate change. After another year of extreme weather events – from Hurricane Ian in the United States to heatwaves in the UK and floods in Pakistan – the need to move towards a more sustainable world has become clearer than ever and companies are now expected to see new levels of action.
Last year, COP26 – the United Nations Climate Change Conference – emphasized the need for collective urgent action, with greater specificity and short-term goals for reducing emissions this decade, phasing out coal and setting methane targets. The private sector also plays a role, with many companies making important commitments on financing and emissions targets.
In IBM’s Institute for Business Value (IBV) 2022 studyIt was revealed that 48% of CEOs surveyed cite increasing sustainability as one of the top priorities for their organization over the next two years – a 37% increase from the 2021 survey.
Organizations, companies and governments are setting specific sustainability goals – and now people expect to see what they are doing to meet those commitments with tangible, real-life examples. As world leaders gather at COP27 this week, the talks on sustainability will continue to shift from goals and ambition to action and results.
But despite pressure from boards, investors and the public, most organizations still don’t know where to start when it comes to taking action and making progress toward these goals. Fortunately, technology can help.
The problem with data insights
Using data to accelerate sustainability efforts is crucial, but getting there isn’t always easy. Today, the ability to translate sustainability-related data into actionable insights that companies can use to make decisions and take action is a major barrier to success.
the IBM IBV study shows that 44% of CEOs surveyed cite a lack of data insights as a real problem when it comes to meeting sustainability goals – and 35% say they are unsure how technology can help them manage their sustainability goals.
Since short-term action is key in the quest for climate action, companies are now leveraging AI for its potential to tackle this problem. IBM’s Global AI Adoption Index The report found that two-thirds of IT leaders surveyed say their company currently plans to accelerate climate action by applying AI to achieve sustainability goals in the near future, particularly for managing data complexity and reporting.
Businesses can extend the life of physical assets such as machinery, equipment or fleets.
There are practical ways companies can use data, AI and automation technology to take action for their climate goals. Although these systems have been around for a while, they were not always used with a focus on achieving sustainability goals. Fortunately, this field is rapidly maturing and there are several innovative ways to connect net-zero goals with existing technologies. And often the same technologies can also help with operational efficiency and costs.
Businesses can extend the life of physical assets such as machines, equipment or fleets by leveraging IoT data and AI technologies designed to: predict asset failure. AI creates machine learning models that can help break data patterns from their equipment and the causal relationships that help them extend asset life, reduce unplanned downtime, and reduce maintenance costs.
Rishi Vaish — Chief Technology Officer for IBM Sustainability Software — explains that a cement plant is a prime example where predictive maintenance can be effective.
The production of cement and concrete is a major source of energy consumption and greenhouse gas emissions, so it is important to keep equipment in a factory running smoothly to make operations more energy efficient.
According to Vaish, this can be done by “extending the equipment with IoT sensors and capturing the sensor data. The data can then be fed into AI models designed to monitor the equipment and signs of equipment failure, making it possible to to perform predictive maintenance for the plant.”
This same principle can be applied in many industries that rely on manufacturing operations and heavy machinery. Taking into account environmental factors, temperature, vibration and other data points provided by IoT and other sources, applying advanced analytics and AI to understand and optimize the health of these assets can extend their lifecycle and thereby reduce waste. In addition, it can provide information about decisions to make equipment work more efficiently with less energy consumption.
Optimizing real estate
Buildings and factories are large generators and consumers of data from many locations. They are also a huge source of energy consumption and emissions for businesses. Applying AI and intelligent facilities management technologies can help companies manage their real estate more effectively, improve utilization and find opportunities to reduce energy consumption and associated emissions.
Facility management is not a new part of business operations, but integrated workplace management solutions (IWMS) bring cutting edge developments in this area designed to give companies the ability to capture and analyze their data to develop greater operational effectiveness.
Computers, data centers and networks take up about 10% of the world’s electricity.
With these data insights, business leaders are equipped with the tools to minimize the environmental impact of their buildings. Companies need up-to-date occupancy information to know how, when and by whom the space is being used. An IWMS breaks down such information at the company level and provides insight into how these locations can be used more efficiently.
“For example, if a company has a building with about ten floors and only about 15-20 people per floor in the offices, the IWMS software can detect these inefficiencies in building occupancy. The company can then use the software to consolidate and reconfigure the office plan, for example in two floors, so that the company can reduce its energy footprint,” explains Vaish.
Energy-efficient data centers
A EY study shows that computers, data centers and networks consume about 10% of the world’s electricity, which amounts to about 190 terawatt hours of energy per year – which is more than the entire state of New York consumes during the same period. With the shift to efficiency solutions such as cloud computing, number of terawatt hours Consumption by computers has remained relatively constant despite its growth since 2015. Yet it still requires significant amounts of energy, leaving room to improve efficiency even further.
As more cloud platforms promise more elasticity and savings, many companies are moving workloads out of existing data centers. With intelligent automation software — such as: IBM Turbonomic Application Resource Management (ARM) — Enterprises can manage workload density in the data center while addressing increasingly complex business demands.
As Vaish explains, one of the challenges for businesses is to find ways to optimize a particular data center.
A company can have a workload of five servers, but use up to ten servers to run it, using twice the amount of power needed to run the machines when they’re not needed. ARM software is designed to help identify the areas of the data center where there is inefficiency and where it is possible to increase workload density.
In this way, he adds, “companies can manage the utilization of available machines and turn off the machines that are not in use, or move the workload to one data center or the cloud and completely shut down another data center.”
Emerging capabilities in this space can also provide a clear view of the current environmental impact of their IT infrastructure, as well as specific actions they can take to conserve energy by moving workloads in near real time. This approach can enable companies to securely suspend data center hosts to run more applications on less hardware, which can help reduce data center energy waste and the company’s overall carbon footprint.
Even when it comes to the hardware, advancements in server technology can mean: one server can cover the same workload as many others.
The way forward
Business leaders need help connecting the dots between the sustainability goals they set and the operational systems they need to make that happen. As Vaish explains, the technologies described above can be effective when companies ensure that the C-suite connects directly with the people and organizations leading the processes that can make a difference.
CEOs would do well to focus not only on setting sustainability goals, but also showing how their operational systems are connected to these goals, and keeping investors and customers informed of the improvements they are making in the future. make over time.
If this is achieved, companies stand a good chance of making progress in meeting their environmental obligations, which is a critical part of solving the climate crisis.