· Insights · 6 min read
ESG for Tech: Environment
Environmental considerations in ESG are increasingly crucial for tech companies, affecting customer relationships and financing outcomes. Key areas for board attention include navigating regulatory uncertainties, implementing efficient data strategies, improving software quality control, and setting clear goals for data science and ML initiatives. Proactive environmental management can lead to cost savings, risk reduction, and competitive advantages.
As I discussed in my introductory post, ESG isn’t just for publicly-traded companies; companies both public and private across all industries have felt the impact of ESG on their customer relationships and financing outcomes. In this post, I’ll focus on the first letter in the ESG triad – E, for Environment, which addresses a company’s impact on the environment.
Regulatory Landscape and Board Implications
In the US, there has been SEC discussion regarding ESG reporting requirements. As of 2024, however, only environmental disclosure requirements have been established…kind of. In March 2024, the SEC released their final climate disclosure rules (“Climate Rules”) that required registrants to identify and describe climate-related risks, the impact on the company’s business operations, financials, and strategy. It also required disclosure of any mitigation or adaptation of the risks, including how the board and management are considering climate-specific risks in their overall risk management process.
The Climate Rules had been set to go into effect at the end of May 2024 (with the earliest required filers making disclosures on their 2025 financial statements), but within a month of publishing the Climate Rules, numerous lawsuits had been filed against the SEC. In April of this year, the SEC chose to stay the implementation of (i.e., not enforce) the Climate Rules while the court completes their judicial review of the legal filings against the SEC.
Even if the Climate Rules do not get implemented as they are currently written, it’s likely that this type of information will be requested from someone. The World Economic Forum’s metrics include a number of disclosures explicitly related to climate, and it’s reasonable to expect that countries may require similar types of disclosures for security filings. Even if not governmentally-mandated, ESG-focused investors may drive these types of reporting, so it makes sense to have your board begin to build in appropriate governance around them.
Environmental Impact in Tech and Professional Services
For technology or professional services companies, the environmental impact might seem less obvious than in industries like natural resource extraction or manufacturing. However, your primary business activities likely involve developing software, executing this software on devices, and analyzing, storing, or transmitting related data – all tasks that correspond to demand for energy usage or natural resource extraction. Notably, the electricity that powers a server and the raw materials that go into devices are also key cost drivers that affect a company’s expenses and profitability.
Saving the environment might save you money, but where do you begin? For many organizations, there is low-hanging fruit to be found in two surprisingly simple concepts: clear requirements and software quality control. As a board member, you should encourage management to focus on these key areas:
1. Data Strategies
Let’s start with clear requirements for data. Most organizations don’t have a purposeful plan driving what data they collect, how they store the data, and when and how they dispose of the data. Given the increasing volume of data, some companies try to capture value by collecting ALL THE DATA. But by collecting the wrong data or keeping it for too long, organizations create unnecessary demand for electricity. By better-targeting customer data collection or optimizing data retention policies, organizations can cut both their costs and risks at the same time. This aligns well with trends in data privacy and compliance, and should be addressed as part of a holistic data privacy program.
2. Software Quality Control
Many organizations that develop software or data products do not consider the efficiency of their data representations, transmission, or storage. As machine learning and data science activities have grown exponentially over the last decade, this issue has become even more problematic. Encourage your management team to prioritize software efficiency as part of the development process.
3. Data Science and ML Goals
When most research teams begin the process of developing a model, there is often no clear goal or metric to guide their effort. As a board member, you should push for clear requirements and metrics for data science and ML projects to help the technical teams within your organization effectively manage the tradeoff between performance and resource requirements. For example, researchers at Harvard found that their machine learning model took 400% more energy to achieve a .1% increase in accuracy beyond the initial model. Consider advocating for a data science maturity assessment and comprehensive data strategy at the board level to ensure that your organization’s technical efforts align with the environmental governance that’s been established.
4. Scaling Up
Many traditional software quality management techniques can have a material impact, especially for software that operates at scale. Encourage your organization to carefully select programming languages, use static analysis to detect unnecessary dependencies or code paths, and employ dynamic analysis like application or network profiling to identify inefficient software or hardware configurations.
Open source projects or organizations that release software can make a difference by using static analysis to detect unnecessary dependencies or code paths; many applications or libraries carry a large overhead of waste, and these extra bytes distributed over the network or loaded into memory add up at scale. Down the supply chain, organizations that “consume” software should also be conscious of their choices; for example, dynamic analysis like application or network profiling can help identify software or hardware that might be inefficient or misconfigured. In general, these efficiencies are best captured when addressed as part of a top-down software development maturity assessment or technology maturity assessment.
Board-Level Considerations
Board members can help drive environmental initiatives that not only reduce the company’s environmental footprint but also lead to cost savings and risk reduction. Here are some key actions to consider:
- Advocate for a comprehensive environmental impact assessment of the company’s tech operations. Technological improvements over even the past few months have greatly improved the efficiency and reduced required resources; implementing newer solutions may reduce the overall financial cost of operations.
- Encourage the development of clear metrics and KPIs for environmental performance in tech operations.
- Ensure that environmental considerations are integrated into the company’s overall risk management strategy.
- Push for regular reporting on environmental initiatives and their impact on the company’s bottom line.
- Consider forming a board-level sustainability committee or assigning specific environmental oversight responsibilities to an existing committee.
By taking action to get ahead of these concerns – especially where the effort aligns with other key opportunities like data privacy and data science – your company will find itself ahead of the pack. As environmental considerations become more important for customers, employees, and investors, your proactive approach will position the company for success in an increasingly eco-conscious market.
In my next post, I’ll explore the ‘S’ in ESG, discussing the social responsibilities and opportunities for tech companies in today’s interconnected world.