Localisation Across Sectors
Localisation extends beyond humanitarian and development work. Explore how power, institutional governance, knowledge and accountability shape localisation across sectors.
Critical insight for institutions navigating complexity.
Analysis, reflection and practice-based knowledge on the questions shaping institutional, social, political, technological and organisational life, to help institutions think more clearly, act more responsibly, and respond to change with judgement and care.
Localisation extends beyond humanitarian and development work. Explore how power, institutional governance, knowledge and accountability shape localisation across sectors.
The founder’s dilemma emerges when a growing business remains dependent on its founder. Learn how organisations can scale, delegate and build systems without losing quality, culture or founder knowledge.
Article 4 of the EU AI Act makes AI literacy an organisational responsibility. Learn what this means for organisations using ChatGPT and other AI tools in everyday professional work.
How the Centre for Transnational Development and Collaboration created a distinctive model for research, strategy, learning, organisational transformation and responsible innovation
Political risk management helps organisations prepare for conflict, geopolitical instability, regulatory change, economic disruption, and shifting relationships between states.
The recent reporting on safeguarding failures in humanitarian programmes in eastern Chad has prompted important conversations about organisational accountability, investigations, and survivor support.
Organisations are often spoken about as structures: policies, departments, strategies, reporting lines, budgets, and systems.
When safeguarding failures become public, organisations often respond in familiar ways.
Reports that more than £28bn of UK taxpayers’ money may have reached terrorists, hostile states, organised crime networks and other hostile actors through public funding channels, including aid payments, should not be treated as an isolated scandal (For the full story).
Organisations are increasingly turning to AI to draft policies, summarise complaints, analyse workplace culture, and support internal decision-making.
When cases of sexual violence against children become public, societies often move quickly towards shock, naming, exposure, and demands for punishment.
Why Organisations Struggle to Move Forward After Conflict — And What Actually Helps
Why Organisations Struggle Without Clear Frameworks — Even When They Have Strategy
Why Organisations Cannot Improve What They Do Not Clearly Understand
Why Research Often Fails to Reflect Reality — And What Organisations Can Do Differently
Why Most Workplace Learning Does Not Work — And What To Do Instead
Why Diversity and Inclusion Efforts Often Fail — And What Organisations Miss
Education is often framed as a neutral good something that equips individuals with knowledge, skills, and opportunities. The dominant assumption is that if systems are expanded and content is improved, education will fulfil its promise.
Across contexts, what we see repeatedly is not disengagement from politics, but a growing sense of exhaustion with how politics is currently organised.
In moments of crisis, organisations often ask the same question: how do we respond? The answers tend to be familiar. Activate safeguarding protocols. Issue guidance. Expand wellbeing provision. Coordinate through formal structures.
Across organisations working in unstable or conflict-affected contexts, one assumption persists: that care can be maintained through policies, goodwill, or isolated wellbeing initiatives.
Accountability is often treated as a compliance requirement—something to be reported, audited, or demonstrated after the fact. Yet, in reality, organisational accountability is far more fundamental. It is not a static mechanism but a continuous, evolving process that shapes how institutions relate to power, people, and purpose.
Bias is often framed as a personal defect—an individual failure of judgement that can be corrected through awareness, training, or better intentions. In this view, bias resides primarily in the minds of individuals, and the solution lies in learning to recognise and correct our prejudices.
Artificial intelligence is often framed as either a threat to human distinctiveness or as a neutral productivity tool. Rarely is it discussed as something that may meaningfully support neurodivergent people and equally rarely do we ask what AI could become if it were shaped by neurodivergent ways of thinking.
We are living through a moment in which technological acceleration is being narrated as inevitability.
For many people, the most disorienting part of the Jeffrey Epstein story is not the fact of abuse alone, but its apparent durability: the sense that harm could be so extensive—and remain survivable for those enabling it—for so long.
AI does not only affect how we write. It changes how we handle data, how we interpret evidence, and how easily our work can travel into decision-making spaces.
AI tools are now woven into everyday research practice. They can draft text, summarise articles, generate interview questions, propose analytic categories, and produce outputs that look coherent enough to pass as competence.
The UK Department for Education’s recent policy paper on generative artificial intelligence (AI) in education represents an important and timely intervention.
Much of the advice on career transition in the age of AI is relentlessly individualised. The focus, we are told, should be on personal reinvention: mastering the art of self-promotion, pivoting rapidly, accumulating credentials.
The prevailing story of artificial intelligence in the workplace is, at first glance, deceptively simple: as jobs change, people must reskill or risk being left behind.
Over the last four blogs in this series, we have examined how AI is reshaping the educational landscape: the abundance of online offers, the disappearance of identifiable educators, the inflation of accreditation badges, and the rise of synthetic content that mimics expertise without embodying it.
Before the rise of AI, the primary concern for learners was whether a course was relevant, rigorous, or well-designed.
Accreditation has long been used as a marker of legitimacy in education. Universities, training centres, and institutes rely on accrediting bodies to validate the quality of their programmes and assure learners that the content meets agreed standards.
One of the most significant shifts in the learning ecosystem today is not simply the rise of AI-generated content, but the disappearance of identifiable educators behind many online offers.
Over the past decade, the global learning landscape has transformed. From universities and think tanks to independent educators and consultancies, education has increasingly moved online.
Across safeguarding and protection systems, a recurring assumption persists: that better outcomes require more data. More forms, more reporting channels, more numbers.
Across CTDC’s consultancy practice in the development, humanitarian, and human rights sectors, we review dozens of tenders and contracts every year. Many come wrapped in the language of partnership, justice, care, and localisation.
A CTDC reflection on affect, confidentiality, power, and the hidden harms organisations overlook
For years, international organisations have pledged to make their safeguarding systems “culturally sensitive.”
Artificial intelligence (AI) is transforming how organisations operate, from recruitment and project management to research and reporting. It can now generate content, analyse data, and design frameworks at unprecedented speed.
Putting feminist MEAL into practice begins with intentional design. Every stage of monitoring, evaluation, accountability, and learning can be re-imagined reflecting justice and relational ethics.
At the Centre for Transnational Development and Collaboration (CTDC), we see Monitoring, Evaluation, Accountability, and Learning (MEAL) not as a bureaucratic checklist, but as a set of living processes that shape how institutions learn, care, and grow.
Rethinking Monitoring, Evaluation, Accountability, and Learning through a Feminist Lens
Global safeguarding frameworks are often described as victim-centred, but in practice they frequently reproduce the same hierarchies they aim to dismantle.
Leadership does not only set strategies; it shapes the cultural fabric of organisations. When leadership fails, the consequences extend beyond inefficiency.
When we think of leadership, we often focus on strategy, vision, and structures. Yet, what truly binds an organisation together is not only its policies or plans; it is its culture.
“Localisation” has become a buzzword in development, human rights, and humanitarian fields. It promises to shift resources, power, and leadership to local actors, making aid more just and sustainable.
When organisations lose their memory, they lose more than files. They lose context, relationships, and the ability to adapt with integrity. This post outlines what institutional memory is, why it’s political (not neutral), and how to protect it; ethically and practically.
Today’s organisations are operating in contexts defined by uncertainty, complexity, and rapid change. Whether in the corporate sector, civil society, or multilateral spaces, structures designed for stability are being tested by shifting political, social, and economic realities.
In today’s organisations, managers are not just responsible for achieving targets; they are also key to building safe, empowering, and respectful workplaces. As highlighted in our Organisational Safeguarding Best Practices and Procedures, preventing abuse in the workplace requires conscious leadership, systemic change, and relational accountability.
18 publications from our research and practice since 2015, each free to download in full.