Articles

AI has been thrust with full force into the zeitgeist over this past year thanks to the transformative and media-worthy feats of generative AI, but putting aside the hype, AI is truly transforming the way we live and work. AI (both generative and classical) will undoubtedly revolutionise industries, massively improve efficiency, and create opportunities we couldn’t have foreseen. However, as the oft-quoted part-time philosopher / superhero Spiderman put it: With great power comes great responsibility....

We Know You… I’m going to play back two attempts at hyper-personalisation that have actually happened over the last 5 years - the names of the companies involved have been removed to protect embarrassment (and lawsuits). If you’re not sure what hyper-personalisation is please sit in the unknown for a few more paragraphs - we’ll get to that. Story 1: Beverage Company I’ve popped out for the weekend to get some shopping in for my other-half’s upcoming birthday - I know what I want to get, I’m an efficient shopper, so I walk in with a purpose and head to a particular store....

Preface This article has been sitting in the backlog for a while - it’s been a culmination of thoughts and experiences across several decades of working in high change, high innovation areas. Where I’ve watched the sheer pace of change frighten, exhaust, burn out, inspire, and enthuse many different individuals over and over again. And with the industry at a crossroads thanks to the petrifying? exhilarating? (fill in the right adjective yourself) explosion of AI technologies in the last several years with the velocity of innovation only increasing it feels like an apt time to finish a short retrospective on my experiences with rapid innovation....

Your data has been de-identified. You are anonymous. We have pseudonymised your information. Your private data is masked. The Personally Identifiable Information (PII) has been scrubbed. What if I told you there’s a good chance none of that matters? A research paper from Carnegie Mellon University back in the year 2000 showed that: 87% (216 million of 248 million) of the population in the United States [were uniquely identifiable] based only on [postcode], gender and date of birth....

There are a few “hot topics” that come up in every data strategy, innovation or future-focused conversation and none come up more frequently than real time data. For some years now it’s been the talk of the town and is often (incorrectly) seen as a flex as to how customer centric and modern you are as an organisation. “We want real-time data!” “Let’s talk about streaming!” “I hear that BigTechCompanyXYZ has an event-first data architecture”...

As the Data Mesh hype train continues to work its way through the data landscape (with good reason) data departments are finding themselves rushed to build Data Products, often before they have the processes, people or experience to understand what separates products that have the potential for success vs those that are destined to fail. Data Products are sitting unused and expensively idle at an ever-increasing rate due to the focus on technology and buzz instead of the most important aspect of any product…the customer....

Remember the days when there used to be significant justification before the appointment of a CIO? Yeah, you probably don’t, neither do I - but it really wasn’t that long ago. Let me put it in context, the movies Pretty Woman and Home Alone both came out in 1990 and it was around this time that the first CIO roles started to exist across Australia (and likewise across most of the western world)....

Generative AI and Large Language Models (LLMs) have hit the mainstream and caused everyone to take notice - as is often the case when technology moves out of the hands of the niche and into the public zeitgeist there have been all manner of opinions, facts and utter BS thrown around like sugar in a chocolate factory. Humans are spectacular at pointing out the problems with things, as long as those things aren’t themselves, and there has been some amazing displays of this front and centre during the explosion of LLM conversations....

In Part 1 of this 3-part series, I covered the building blocks of a Defensive Data Strategy and when they should be employed - todays article will focus on the art of attack. Defense may win games, as many a sports coach will tell you, but attack is what sells the tickets. Most data professionals and organisational executives alike want to talk about, and hear about, how we can maximise the value out of the data that is sitting a their feet....

Your organisational data strategy should contain elements of both defensive plays and attacking plays - it’s vital to understand the right ratio of defense vs attack to suit your organisational reality and risk appetite. In this series I’ll be walking through the process of landing a data strategy that delivers to organisational outcomes whilst meeting the risk appetite and customer expectations. I’ll be covering: Part 1: What is a Defensive Data Strategy?...