Access and Feeds

Why Information Governance is So Difficult for Industrial Companies

By Dick Weisinger

Information governance is the process of managing the creation, use, storage, and disposal of information and data in an organization. It involves policies, procedures, roles, and technologies that ensure the quality, security, privacy, and compliance of information assets. Information governance is essential for any organization that wants to leverage its data for innovation, growth, and success.

However, information governance is especially challenging for industrial companies, which operate in complex and dynamic environments. Industrial companies face several obstacles that make information governance difficult, such as:

  • The diversity and volume of data sources and types. Industrial companies collect and generate data from various sources, such as sensors, machines, products, customers, suppliers, and partners. They also deal with different types of data, such as structured, unstructured, semi-structured, streaming, and geospatial. Managing and integrating these data sources and types requires sophisticated tools and skills.
  • The legacy and siloed systems and processes. Industrial companies often have outdated and incompatible systems and processes that hinder data sharing and collaboration. They also have siloed data repositories that prevent a holistic view of the data landscape. Breaking down these barriers and modernizing these systems and processes requires significant investment and change management.
  • The regulatory and ethical requirements and expectations. Industrial companies operate in highly regulated industries that impose strict rules and standards on data management. They also face increasing expectations from stakeholders and society to be responsible and transparent with their data practices. Meeting these requirements and expectations requires robust governance frameworks and mechanisms.

Despite these challenges, industrial companies can benefit from information governance if they adopt some of the emerging trends in this field, such as:

  • AI and intelligent application-development trends will impact the enterprise the most in 2024. AI can help industrial companies automate and optimize their data processes, such as data quality, metadata management, privacy and security, and information life cycle management. AI can also help industrial companies generate new insights and value from their data, such as generative AI, which can produce original content from data or existing content. However, AI also requires trust, risk, and security management to ensure the ethical and responsible use of AI models and applications.
  • Hybrid cloud-based ECM will offer the best of both worlds: the scalability, flexibility, and cost-effectiveness of cloud computing and the control, security, and compliance of on-premise systems. Hybrid cloud-based ECM can help industrial companies integrate their data across different platforms and services, as well as with their on-premise systems and applications. Hybrid cloud-based ECM can also help industrial companies access advanced capabilities and features that are not available or affordable on-premise.
  • Improved information governance will be essential to ensure compliance with regulations, standards, and policies related to content management. Improved information governance can help industrial companies manage their data more effectively and efficiently, as well as reduce risks and costs associated with data breaches, fines, lawsuits, and reputational damage. Improved information governance can also help industrial companies enhance their performance and competitiveness by enabling better decision-making, collaboration, innovation, and customer service.

Information governance is not easy for industrial companies, but it is not impossible either. By overcoming the challenges and embracing the trends in this field, industrial companies can transform their data into a strategic asset that drives their future success.

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