Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of the Economic Times – ET Edge Insights, its management, or its members

Business,,Technology,,Internet,And,Network,Concept.,Young,Businessman,Shows,The

Data has become more visible on corporate agendas each year, increasing shareholder expectations about creating or protecting customers’ interests.

In today’s big data era, data has become a powerful strategic resource for organisations. During the past decade, data has transformed every aspect of social, economic, and citizen interaction with government and corporations. A growing number of citizens are demanding increased accountability from their governments, healthcare systems, and non-profits. And shareholders are expecting corporations to disclose accurate information to make better investment decisions.

In general, accounting information systems collect data that is eventually transformed into public products, such as financial statements and internal sales reports. In daily operations, poor data quality can have substantial, economic and social consequences either in banking, healthcare or other sectors. Data has become more visible on corporate agendas each year, increasing shareholder expectations about creating or protecting customers’ interests. As per a PWC Chief Data Officer survey, only twenty one percent of the top 2,500 publicly traded companies worldwide currently have a Chief Data Officer (CDO) in place. However, fifty percent of them have been appointed in the last three years.

A chief data officer, holding an executive position in the company or an internal director on board has the potential to gain and maximize the benefits of data, just like a CIO does for technology. In organizations with a chief data officer, the governance of data is formalized through a function often called a data governance function. Data governance provides a policy in an organization that defines the accountability of stakeholders while assessing, monitoring and directing daily data operations. It also provides guidance on decisions that will have to be taken on data related activities.

As data is being increasingly considered an enterprise asset, there is a growing body of research indicating that firms are concerned about more active engagement and communication among directors, board members, and shareholders around data. This is partly fuelled by a mindset change, that data is a product. This furthered the thought that data can be monetized directly and be accounted as money or an asset on a balance sheet. Most fortune 500 organizations have started including verbiage around data, its management, protection and governance on their annual reports.

Having stressed the active management and governance of fast-evolving data in organizations, there has been a recent surge in technology advancements called the modern data stack. This advancement is supposed to ease the data operations while servicing customers better. Certain aspects that have taken precedence are observability, cataloging metadata, streaming data management and its governance.

Compared to the even more recent concept of data governance, IT governance has evolved from the initial concept of corporate governance. This evolution can be associated with the cost of incorrect data for companies that can amount to billions of dollars. The issue doesn’t stop there, but can cascade into provisioning associated with reputational and regulatory risks, while it can also push the company’s risk appetite on a higher side. Moreover, data can have a broad impact across multiple functions in an organization including marketing, pricing, accounting, organizational behaviour, corporate law, ethics, operations, and information technology.

Similarly, certain aspects of data governance add value and influence a firm’s performance. Data is considered a critical asset that organizations will have to protect through a corporate governance framework, aligned with data governance principles. Moreover, organizations must ensure that procedures and practices are in place to assess, direct, monitor, and protect the data and related infrastructure. This is to ensure its value to the enterprise and thereby its stakeholders.

Generally stating, there are two basic models of corporate governance that influence firms’ performance: the shareholder model and the stakeholder model. The shareholder model of corporate governance often describes the formal system of accountability of senior management to shareholders. By contrast, the stakeholder model of corporate governance can be used to describe the network of formal and informal relations between a company and its stakeholders. The stakeholder model also recognises that business ethics and stakeholder relations can also have an impact on the reputation and long-term success of a corporation.

Similarly, there are two basic models of data governance: the inter-governance model and the intra-governance model. Companies increasingly collaborate with external stakeholders, such as suppliers, customers, and competitors, when developing new business models. These include actions by two or more organizations that aim to achieve shared operational objectives that can be achieved by sharing data about customers. The inter-governance model makes it easier for such business models to share, process and protect data while creating value for customers. The other model is driven by policy or best practices to assess, direct and monitor data operations within an organization.

Moreover, there is no single framework or operating model that fits all organizations. The most popular operating models involve a centralized or distributed data management. However, the model can be customized to have centralized governance of data with distributed management of data.

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of the Economic Times – ET Edge Insights, its management, or its members