🎙️ Episode #83: Trust and Knowledge Management скачать в хорошем качестве

🎙️ Episode #83: Trust and Knowledge Management

With Johannes Dreyer (Knowledge Management Practitioner, Data & Information Engineer, South Africa) Most organizations believe their data problems start with poor data quality, weak platforms, or immature governance. They don’t. They start with broken trust — between people, between teams, and between what the organization says it values and how it actually behaves. In this conversation, Johannes and I went deep into something we rarely discuss honestly in data and AI programs: trust is not soft, emotional, or abstract. It is structural. And when it erodes, knowledge stops flowing long before data pipelines fail. Some hard truths we explored: • Trust is always judged first, then reinforced or weakened by behavior• People do not share knowledge with systems or frameworks — they share it with people they trust• Most data governance failures are not technical failures, they are trust failures• You can have metadata, lineage, dashboards, and AI models — and still have zero decision confidence• Executives often do not distrust data because it is wrong, but because it is opaque, inconsistent, or unpredictable• Knowledge hoarding is not a people problem; it is a signal that vulnerability feels unsafe• If trust is damaged, transparency alone does not fix it — behavior does One insight that really landed for me: We do not lack data.We lack shared meaning. Johannes framed trust as something measurable, not mystical. It shows up in reliability, predictability, competence, and how safe people feel being vulnerable. When those signals are missing, people disengage quietly — dashboards go unused, AI pilots stall, and decisions revert to gut feel or spreadsheets. We also talked about why governance so often becomes a compliance exercise instead of an enabler: Because it is introduced after trust is already broken. And why knowledge management cannot sit outside data management: Because data without shared understanding does not become knowledge — it becomes noise. A powerful takeaway for anyone leading data, AI, governance, or modernization initiatives: You cannot automate trust.You have to earn it — conversation by conversation, decision by decision, behavior by behavior. If you are building data platforms, AI systems, or governance frameworks and wondering why adoption feels forced, slow, or fragile — pause and ask: Do people trust this system enough to rely on it when it matters? Or are we delivering tools without building shared truth? #Trust #KnowledgeManagement #DataGovernance #DataLeadership #AI #DecisionMaking #OrganizationalTrust #LetsTalkAboutData