Going Digital: Guide to Data Governance Policy Making
The Going Digital Guide to Data Governance Policy Making (hereafter the
Guide) aims to advance the development, revision and implementation of policies for data governance, by helping to overcome key related policy tensions. Addressing the complexities arising from the nature of data as an intangible infrastructural resource of global strategic importance, the Guide helps policy makers design effective, technology-neutral, forward-looking and coherent data governance policies across sectors, policy domains and jurisdictions. It proposes a set of questions and highlights promising policy approaches based on three policy tensions and objectives that characterise
data governance policy making: 1) Balancing data openness and control while maximising trust; 2) Managing overlapping and potentially conflicting interests and regulations related to data governance; and 3) Incentivising investments in data and their effective re-use.
Data Governance Essentials Handbook
Definitions of Data Governance are numerous. However, they agree on a key principle - that it’s dedicated to the organisation of people, processes, and technology to enable effective data management.
Ensuring Compliance with the Protection of Personal Information Act (PoPIA) in South African Public Entities
South African public entities must comply with PoPIA by ensuring lawful data processing, security safeguards, and transparency. Key steps include appointing an Information Officer, conducting audits, implementing policies, training staff, and monitoring compliance. Regular reviews help maintain compliance, protect personal data, and mitigate legal risks while fostering trust.
Unlocking the Power of Data Governance: A Strategic Approach to Data Management
Data governance ensures data integrity, security, and usability by establishing policies and standards. Emerging models like data cooperatives and public trusts offer new approaches. Best practices include strategic alignment, accountability, and transparency. Effective governance mitigates risks, enhances decision-making, and drives business success in a data-driven world.
Agile Risk Mitigation Framework
Software organisations follow different methodologies for the development of software. The software development methodologies are mainly divided into two categories, including plan-driven and agile development. To attain project success, it is very significant to consider risk management during whole project. Agile development is considered risk-driven, but many risks are unreported at the industrial level.
The Human Factor: Unravelling the Complexities of Behavioural Risk in Decision-Making
Behavioural risk management is crucial for organisational success. Human factors like cognitive biases and emotions significantly impact decision-making. Tools such as risk identification methods, analytics software, and training programmes help manage behavioural risks. Best practices include clear policies, employee involvement, and continuous improvement. Leadership plays a vital role in fostering a risk-aware culture.
Beyond Ethics: The Strategic Economics of Digital Trust
Digital trust is fundamentally the belief that digital technologies and organisations will act securely, ethically and transparently, building stakeholder confidence that enables greater economic growth and resilience. Organisations that excel in digital trust practices—such as robust cybersecurity, ethical data usage and transparent processes—see tangible benefits including increased consumer loyalty, reduced risk, and enhanced market reputation. Recent consulting and research findings show that even a small increase in digital trust can significantly boost GDP per capita and business growth. However, the digital trust gap—differences in perceived versus actual trust in digital platforms—can impede innovation and market development, leaving societies vulnerable to cybercrime and undermining the value created by digital transformation.
In practice, embedding digital trust within strategy, risk and audit functions fosters lasting economic advantage, as strong trust environments lower transaction costs, encourage innovation and ensure higher rates of digital adoption.
Dynamic Risk Assessment
The power of four. An evolution in risk assessment that applies sophisticated algorithms and advanced data analytics together in a KPMG proprietary methodology to identify, connect and visualise risk in four dimensions.
From Registers to Results: Embedding Risk as a Driver of Decision Quality
Risk management often fails leaders because it is applied as an isolated process, generating static registers and qualitative reports disconnected from real decision-making needs. Organisations must embed risk management within decision quality disciplines, prioritising cultural and contextual foundations before quantitative analytics. Approaches like Pelorus Insights' COURSE™ framework and the Risk Capability Pyramid™ demonstrate how integrating risk into strategic choices—and using robust quantification—enables actionable, fit-for-purpose insights that drive confident, resilient decisions in uncertainty (AuditBoard, 2025; PECB, 2025; Pelorus Insights, 2025).
From Box-Ticking to Boardroom Strategy: Elevating Risk Management for Modern Organisations
Decision-centric risk management integrates risk analysis into all strategic and operational decisions, enabling organisations to anticipate threats and opportunities, thus driving value and resilience. By contrast, compliance-centric risk management focuses on adherence to laws, regulations, and internal policies, prioritising the avoidance of breaches over strategic enablement. While both approaches safeguard the organisation, the decision-centric model is proactive and dynamic, embedding risk into business strategy and innovation, whereas compliance-centric methods may foster a checkbox mentality. Leading organisations combine both, ensuring compliance forms a foundational baseline while decision-centric practices drive growth and competitive advantage.