LEAD WITH DATA Podcast

Konnexus

Where we explore the career stories & experiences of some of the most successful people in the field of Data and Analytics.

  1. Season 6 - Episode 2 - “Why data and AI teams need translators not just tools” with Clare Kitching

    27 APR

    Season 6 - Episode 2 - “Why data and AI teams need translators not just tools” with Clare Kitching

    Why Data Teams Need Translators, Not Just ToolsIn this episode of Lead With Data, Rina Gami sits down with Clare Kitching, a senior data leader who works closely with organisations navigating complex data and AI decisions. The conversation explores why many data and AI initiatives stall and not because of tooling gaps. The conversation unpacks how data teams are navigating generative AI, agentic AI and increasing pressure to move quickly, often without the shared language, context and alignment required to succeed. Clare shares what she is seeing first-hand across organisations grappling with executive expectations, shadow AI, governance concerns and the widening distance between technical teams and business leaders. This episode focuses on the growing importance of translators in data teams' people who can bridge strategy, technology and value and what leaders should be paying attention to before scaling AI. In this episode, we cover: Why tools alone do not solve AI and data challengesThe shift from traditional data initiatives to generative AI and agentic-based AIThe critical role of senior executive sponsorship in AI successHow translators help close the gap between technical teams and the businessPractical ways organisations can start or scale AI responsiblyEvolving roles in data teams, including analytics translators and AI governance specialistsCommon challenges such as shadow AI, data quality and organisational buy-inIndicators that signal true readiness to scale AIWhy value-led AI initiatives matter more than experimentation Timestamps00:00 – AI as a high-return capability in modern data teams 01:32 – Claire’s career journey and move into consulting 03:16 – What has changed in data and AI over the last five years 04:00 – Where organisations are really at in their AI journeys 05:24 – Pressure to move quickly and what gets missed 06:03 – Executive sponsorship and its impact on outcomes 07:30 – Data team structures and emerging gaps 08:53 – Organisational barriers to AI adoption 10:38 – Shadow AI and responsible use 12:34 – Initial assessment points when working with organisations 14:47 – Asking the right questions to align AI to value 17:11 – Why communication is now a core data capability 19:09 – Telling the data story in a way the business understands 22:18 – Structuring data teams for sustainable AI outcomes 25:26 – Evolving roles across data, engineering and governance 28:11 – Everyday AI, generative AI and agent AI explained 32:21 – Leadership priorities when advancing AI initiatives 33:49 – Signs an organisation is ready to scale AI responsibly 35:11 – Maintaining momentum without creating risk 36:08 – Hiring for AI capability beyond technical skills 38:25 – When and why to involve external expertise 41:17 – The value of an external perspective 44:48 – Avoiding stagnation in AI programs 45:27 – Communication and storytelling as critical capabilities 46:16 – Leadership alignment and organisational readiness 46:44 – Final reflections and next steps Resources & LinksExperian Data Studio – supporting stronger data governance and trustClaire Kitching Linkedin Website - cambiq.com.au

    47 min
  2. Season 6 - Episode 1 - Why "fail fast" is a powerful mindset if you want to succeed in Data Innovation

    13 APR

    Season 6 - Episode 1 - Why "fail fast" is a powerful mindset if you want to succeed in Data Innovation

    In this episode, Nick Jameson shares his journey from aerospace engineering and defence to data leadership. He discusses why the fail fast mindset is important for Data Innovation, how high-stakes environments influence building resilient data platforms, the importance of problem-solving, stakeholder engagement and managing technical debt. Gain insights into effective leadership, balancing innovation with foundational stability and the future of data engineering and analytics. Data Engineering, Data Leadership, High-Stakes Environments, Data Platforms, Analytics, Tech Debt, Leadership, AI, Data Strategy Key topics: Transferable skills from aerospace to dataBuilding resilient and scalable data platformsManaging technical debt and platform maturityLeadership principles in data teamsThe impact of AI and emerging technologies Chapters 00:00 Embracing Opportunities and Learning from Failure 02:50 Transitioning from Aerospace to Data Analytics 05:58 Core Principles from High-Stakes Engineering 08:33 Decision-Making Under Pressure 11:41 Balancing Processes and Flexibility in Data Analytics 14:36 Managing Expectations and Prioritization 17:16 Building Robust Data Platforms for Future Challenges 20:04 The Interplay of Data Engineering and Advanced Analytics 22:25 Building Robust Data Pipelines 23:23 The Risks of Premature Analytics 25:46 Challenging Assumptions in Data Teams 27:16 Balancing Investments in Data Tools 28:43 Leadership Lessons from Engineering 31:03 Managing Stress in Leadership 34:38 Advice for Nonlinear Moves into Data 36:07 Building a Modern Data Platform 38:26 Investing in People as a Leader 40:15 The Future of Data Engineering and Analytics Resources Experian Data Solutions Nick Jameson on LinkedIn

    39 min

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Where we explore the career stories & experiences of some of the most successful people in the field of Data and Analytics.