Companies are quickly adapting and focusing on corporate social responsibility, notably when it comes to reducing their carbon footprint. A McKinsey report noted that almost two-thirds of Fortune 500 companies are working toward ambitious carbon reduction targets for 2050. These targets and goals are no longer just another metric to track. They have become clear strategic goals for long-term efficiency and impact.
ESG measures have also seen a spike due to the influence of climate change and social justice on investors. The lack of robust ESG data is seen as a hurdle for 46% of North American investors, according to a Capital Group ESG Global Study. And, 70% said that standardization of tools and data is needed to analyze and implement ESG initiatives. Clear, concise and consolidated data is the key to understanding the impact and developing data-driven strategies. The solution? Technology and AI.
Data collection at scale
When it comes to tracking environmental impact, companies need data on energy consumption, water usage greenhouse gas (GHG) emissions, vendor efficiency and waste generation. With reliable data, companies can monitor progress toward sustainability goals and identify areas for improvement, such as conserving resources, limiting emissions, or reducing waste.
According to Deborah Kaplan, global head of sustainability at SAP customer success, collecting and understanding disparate data is the biggest challenge for organizations — regardless of their sustainability preparedness. Companies not only need to find ways to collect accurate data, but be able to organize it for reporting, at scale, across their organization. Luckily, technology can help.
Collecting data is one piece of the equation that technologies focus on heavily. This is the next step to ensuring accurate and valuable reports. Developing a connected network of devices helps to ensure that a company collects data with real-time visibility to empower decision-making.
For example, in assessing waste generation, smart waste metering technology in the form of dumpster sensors and AI software can accurately measure the level of waste and recycling produced across every business location. These measurements provide actionable insight into the amount and type of waste produced and will support the opportunity to divert more waste from landfills and the overall impact of reducing GHG emissions.
AI supporting consolidation
Data collection and management technologies are undoubtedly essential for company-wide, standardized reporting. IDC analysts predict that by 2024, 30% of organizations will use ESG data management platforms to steer ESG KPIs through a centralized system of record for reporting purposes and real-time operational decision-making support. Consolidation is one of the biggest challenges for enterprises with multiple locations and large amounts of data, but today’s new AI technology can support that.
With the use of sensors and AI technology, data that was previously unattainable, unreliable and impossible to manage at scale can now easily be collected, processed, organized and analyzed through a central system. These systems enable reporting while providing actionable insight for companies to adjust their sustainability strategies and see progress in near real time.
Reporting on impact
According to IDC, within the next three years, 45% of G2000 organizations will operationalize integrated sustainability in the supply chain and effectively report impact data, enabling 10% reduction in waste and improving competitive advantage. With the clear benefits of sustainable operations, companies have a lot to lose by not utilizing sustainable-based plans and the technologies that fuel them.
Not only are investors looking at a company’s impacts, but consumers and employees are beginning to notice as well. Software AG reports that beyond the cost of non-compliance, the majority (84%) of organizations believe that without a clear sustainability strategy, they are also likely to lose staff. Ignoring environmental metrics will cost a business a lot more than money; they will lose trust.
Ultimately, companies can’t manage what they don’t measure. Reporting challenges for large companies and enterprises will continue, but AI and data management technologies can help. In waste and recycling management, these technologies are already making a significant impact.
Technology streamlines operations, creates vendor oversight and provides data that not only informs sustainability strategy but also enables accurate, standardized reporting of reduced carbon impact. Data-collection technology may be the key solution for companies to succeed when it comes to ESG.
This article was written by Graham Rihn and RoadRunner Recycling from VentureBeat and was legally licensed through the DiveMarketplace by Industry Dive. Please direct all licensing questions to [email protected].
