As CDAO Melbourne marks its 10th anniversary with the 2024 conference, it’s an opportune moment to reflect on a decade of transformative evolution in Melbourne’s data and analytics landscape. As a regular participant, I have witnessed firsthand the remarkable progress. This article analyses my observations over the years, aiming to assess the evolution, identify the challenges for large-scale adoption, and develop a practical strategy to address the identified issues. A refle

Your organisation may be tilting at windmills, hiring a Don Quixote for a Chief Data & Analytics Officer if your data strategy is not driving profit. A profound crisis exists: trillions in data investment yield limited returns, marked by a pervasive “two-year curse” instability among data leaders and 50-80% project failure rates. This failure is primarily managerial, as roughly 70% of struggles stem from people and processes. Data leaders often fail to establish Continuous Va

Artificial intelligence (AI) has not created a new category of ownerless decisions in your business. Every outcome generated by an algorithm remains an act of the company, and therefore falls squarely within the legal and moral accountability of the board and executive. AI does not dilute board accountability In corporate law, the company is the decision‑maker, and the board is its collective mind. When a model approves a loan, denies a claim, reallocates staff, or routes co

In 2016, AI pioneer Geoffrey Hinton famously predicted we should stop training radiologists , claiming deep learning would soon outperform human doctors. Similarly, since as early as 2014, Elon Musk has been continuously promising that fully autonomous, sleep-at-the-wheel self-driving cars would be ready next year . Both instances highlight how brilliant minds frequently compress the timeline of complex AI deployment. Now, a bold new prediction has emerged from Microsoft, t