Because governance metrics vary among companies and encompass qualitative issues like independence and accountability, investors and boards are still learning how to clearly convey and analyze governance indicators. However, with increased data capabilities, driven by new technologies and a culture of transparency, investors and boards are beginning to better understand and act on governance issues.

Fundamentals of governance

Corporate governance frameworks include some fundamental requirements, such as having a clearly defined core business, open communication with shareholders, designated committees, e.g. for audit, and so forth. However, governance is most directly dependent on a strong board of directors. The board ensures that a company fulfills its loyalty and fiduciary responsibilities to its stakeholders, such as maximizing shareholder return at public companies.

These responsibilities are more than just box-ticking exercises: for long-term investors, good governance is central to performance.

“If investors intend to hold assets for decades, they have to look at governance more closely,” says Ashby Monk, executive and research director of the Global Projects Center at Stanford University.

For example, he says, without a board that is empowered, balanced and sufficiently knowledgeable about the business, it is easier for companies to take shortcuts on cost and quality, whereas a strong board holds management accountable to plan for the long term.

To measure board strength, both investors and boards can use benchmarking and assessment tools—including relatively simple ones like Excel-based scorecards—to determine whether directors have the right skills and rate their performance.

Good governance also incorporates social balance, such as diversity within boards. This governance metric can be a bridge between qualitative and quantitative analysis. For example, investors can look at the quantitative data of board make-up within their investments. This data then reveals whether they’re investing in companies that embody strong governance qualities, such as creating a corporate culture that supports multiple viewpoints to spot new risks and opportunities. The data can then be a launch point for investors to engage with boards on how they support diversity and how that helps companies meet their goals.

“It’s obvious that a company that doesn’t empower women and is underrepresented by people of color is not sustainable,” adds Mr. Monk. “If I’m going to buy something to hold for a long time, I want to know if the company is properly addressing many of the hard-to-quantify risks. This governance angle helps account for it. It is a nice proxy for whether or not the firm is addressing risk well overall.”

Better data, not just more data

As governance metrics across companies can be inconsistent and sometimes limited, investors need to not only obtain governance data but also engage with boards and analyze companies’ actions to determine whether they truly have strong governance practices.

“It is very easy to quantitatively look at the structure of governance practice. But quantitative data is much harder in terms of capturing the essence of whether that mindset is being embraced and put into practice,” says Anthony Muh, chair of the Asian Corporate Governance Association.

Since data alone cannot tell the full governance story, boards need to provide investors with complementary qualitative information, such as explaining how they source candidates for board seats, to show that they are not just checking a box.

“More data is always a good starting point,” says Mr. Muh. “That said, I warn [analysts and investors] to be careful about how that data is provided. It’s increasingly hard to differentiate between information and noise.” He adds, “Notwithstanding the general premise that more data is a good thing, what I would say is that if a company provides more data for governance, that they need to provide that data with context and an explanation.”

Fortunately, technology advancements make both quantitative and qualitative information easier to share and comprehend.

Data and technology change the scope of governance

New technologies in areas like data management, predictive analytics and machine learning can help both investors and boards improve governance through more accurate assessments and communication.

For example, predictive analytics tools give boards the ability to better forecast issues ranging from customer retention to fraud, rather than relying on just intuition. When providing critical oversight such as evaluating an acquisition, boards can work with predictive analytics providers and tools to look at their own sales data, as well as those of the potentially acquired company, to see how joining together might affect future growth and shareholder value. Boards can then share this data with investors to show that they are providing proper governance in evaluating the acquisition, rather than making a decision based on improper factors such as personal enrichment.

Boards can also use data and analytics tools to better calculate and understand other important considerations, including pay ratios between management and staff, as well as diversity within company ranks. Having this data enables boards to make better decisions based on proper governance protocols. Boards can then share this data with investors to prove they’re acting with proper governance in mind. 

From there, investors can similarly use predictive analytics and other data tools to make their own assessments and see how those align with what boards share. Together, this information helps investors ascertain whether companies are on a solid long-term path.

Regulators can also use new technology to identify improper governance, explains Mr. Muh. “Not long ago, regulators were trying to analyze market data manually. Today they use quantitative systems with AI [artificial intelligence] programs to spot abnormal patterns very quickly, directing regulators to exceptional and suspicious trades with a level of clarity about who is doing a trade when and at what volume,” he says. 

Big data and AI also help auditors do their jobs more efficiently. In the past, auditors only had the resources to examine a sample of a company’s data and therefore had a high probability of missing important governance problems. When auditors use these modern tools, however, they can sample larger datasets in greater depth. And when companies set performance targets linked to executive pay, for example, auditors who can analyze more data will better determine whether companies are properly reaching these targets, or whether there are potential governance issues, e.g. fraud or improper risk, used to reach those goals.

Understanding the full governance story

Good governance is an increasingly important consideration for investors and boards. As it becomes more prevalent, investors are becoming more proficient at analyzing and questioning governance issues, and boards are recognizing the need to clearly communicate with investors.

For example, during engagement meetings, shareholders may challenge boards to improve on environmental and social issues. Companies practicing good governance will clearly disclose those engagements and any measures taken in response. Informed stakeholders, in turn, hold directors and management accountable in future engagements. This feedback cycle pushes organizations to act on the governance that they claim to uphold.

With better technology, investors can then combine this qualitative information with quantitative data (e.g. greenhouse gas emissions data if the concern is environmental) to get a full picture of corporate governance. Doing so helps investors best determine the long-term viability of their investments.