Sep 22, 2025 | Uncategorized
Ask ten people how they use AI and you’ll get ten different answers. Some weave it into their daily work. Others haven’t touched it at all.
The word task is worth pausing on. Most regular users of ChatGPT and its cousins seem less interested in wholesale job replacement and more focused on automating specific tasks. Think of it as a digital assistant that takes care of the repetitive bits rather than a robot stealing your job.
The productivity impact is wildly uneven. Some see little or no gain. Others call it transformative. In most cases, it isn’t eliminating jobs outright, except perhaps grunt work like simple coding, but it is reshaping how people spend their time. Instead of vanishing, roles are evolving. People shift toward higher-value activities that build on what AI produces.
A recent OpenAI study helps quantify this shift, summarised in this graphic. The standout surprise: only 10% of users pay for a ChatGPT subscription. Given the billions being sunk into infrastructure by the LLM providers, that number points to a future where the providers are anticipating dramatic increases in usage, and are betting big with their Capex. It also means that business models will also change dramatically.
If you want to predict how AI will shape work, don’t look only at the tech. Look at how organisations themselves are changing. Structure and process are leading indicators. Change of the kind anticipated, and what we see starting to happen only occurs under strong leadership with a clear vision. Without the leadership, the power of the status quo exerts itself, and change becomes combative and the results disappointing. This will be the case with the evolution of AI.
MIT research reported in Harvard Business Review shows a brutal number: 95% of AI pilots fail.
That begs the question: what are the 5% who succeed doing differently? Academics, as they do, put their answer into a neat framework: the SHAPE Index. It highlights five traits: Strategic Agility, Human-Centricity, Applied Curiosity, Performance Drive, and Ethical Stewardship. The words may sound fluffy, but the underlying logic is sound. The real hurdle is moving from buzzwords to execution in organisations built to defend the status quo.
One thing is certain: sitting on the fence isn’t an option. AI is already changing the way we work. The only real choice is whether you shape it, or let it shape you.
Are you in the 95% waiting for AI to fail or the 5% figuring out how to make it work?
Aug 25, 2025 | Uncategorized
The NDIS has become the Gordian Knot of Australian public policy. Everyone at the roundtable last week agreed it’s unsustainable in its current form, but agreeing how to rein in spending will be a whole lot harder.
Minister Butler’s announcement of the Thriving Kids initiative is a move in the right direction, but it’s a single thread in a tangled ball of string. When you only pull one thread in a tangle, the rest of the knot tightens with unanticipated and always politically uncomfortable consequences.
This is not a system with one broken part. It’s a complex tangle of eligibility creep, opportunistic providers, diagnosis-driven funding, undercooked systems, inconsistent oversight with some fraud thrown in. Reforming just one part, no matter how well-intentioned, leaves the rest to fester. Every action taken to fix one issue nudges another out of alignment.
The OODA loop: Observe, Orient, Decide, Act, is built for this kind of problem. However, it will not be a single elegant cycle spinning at the centre of government. Rather, it requires dozens of loops running simultaneously, each targeting a separate piece of the mess, but in alignment with the objectives and activity going on in other loops.
Reforming the NDIS means defining the core issues to be addressed, managing priorities, ripping apart compounding complexity, and tackling the revealed challenges transparently, and one at a time.
The NDIS was created to support people with profound and permanent impairments. That mission is too important to be lost in mission creep and misallocated funds.
Observe: See the system, not Just the symptoms
The blowout in costs has become impossible to ignore. Nearly 10% growth year on year, with a target now of 4 to 6%. The Thriving Kids pivot aims to rehouse children with mild developmental needs in a different support stream. It addresses one of the most visible distortions, but it’s just the tip. It is also relocating those with mild learning challenges back to the states, who abrogated their responsibilities when the NDIS funding pool was opened for business.
Over the last few years, eligibility rules have stretched beyond recognition, plan managers are profiting with minimal oversight, administration systems are still working like it’s 2008, and there is enough friction between state and federal responsibilities to make any real-time response slow and clumsy. Fraud may not be rampant, but it’s visible enough to damage public trust.
Orient: Understand the performance barriers, drivers, and objectives
We are dealing with a big system in urgent need of a tune-up. To do the job properly, it must be broken into the component parts, and given the ability to evolve. Trying to reform the NDIS in one go is like jumping off a cliff and trying to build a glider before you hit the bottom.
Each major component: eligibility, fraud controls, provider oversight, participant experience, administration architecture and processes needs its own OODA loop. That will be how you handle complexity, not by centralising decision-making, but by decentralising learning.
The political reality is that every decision will create losers. Some of those will be legitimate cases who fall between the cracks. Others will be families who have relied on NDIS support, but whose circumstances were never quite aligned with the original intent of the scheme. Still others will be those who learned how to play the system.
The danger lies in pretending there are no trade-offs. You can’t trim billions without someone yelling. But you can explain why you’re doing it, and who benefits when the system works better.
Decide: Trade political safety for effectiveness
Reform doesn’t have to be elegant. It has to work.
The launch of Thriving Kids should be treated as a testbed, not a destination. Start small, measure obsessively, and be prepared to change course. At the same time, the government should quietly empower an oversight taskforce with real teeth. It must be able to audit, freeze funding, publish outcomes, and prosecute where necessary.
Eligibility needs rethinking. Not through the lens of diagnosis alone, but through function and long-term need. Payment structures must reward value, not volume. Plan management should be transparent, capped, and linked to performance.
The back-end co-ordinating processes must talk to each other in real time, not through some bureaucratic or political committee which obscures and compromises outcomes, as well as being friction in the system. Each decision here needs to trigger a loop. Decide. Test. Measure. Refine. Then decide again.
Act: Move with purpose and learn
Forget big-bang reforms. Focus on sequencing. Stabilise the pressure points. Target the areas with the fastest runaway costs. Act on what you’ve learned, not what the headlines say.
When those making the changes act, they need to ‘own’ the story and tell it creatively. Don’t let it be told by those who feel short-changed. Make the case publicly and repeatedly: this isn’t about austerity. It’s about protecting the integrity of something Australia needs for the long haul.
Jeff Bezos uses the analogy of ‘batwing’ doors. For some, and probably most decisions, you can move ahead, and if it looks good keep going, but if it looks dodgy, back away through the batwings. Only a few decisions will be ones that are not able to be reversed. Public institutions are lousy at admitting error, explaining the reasons, and moving ahead in a slightly different path. To properly ensure public trust in the NDIS, they need to get better at it.
Rinse and repeat. Treat Reform as a process of continuous improvement, not a political slogan
Reform is not a one-shot fix. It’s a process of continuous adaptation and learning.
Nested loops allow the system to flex and adjust without collapsing. The eligibility loop refines definitions as new cases emerge. The provider loop weeds out inefficiencies. The fraud loop works in real time to prevent erosion of trust as well as preventing funding being misused. The IT loop upgrades infrastructure to handle the load. The communications loop ensures the public stays informed and supportive.
These loops aren’t hierarchical. They’re interdependent. If one fails, the pressure leaks into the others, which is why each loop needs autonomy, clear reporting lines, and real decision-making power.
The NDIS funding problem will not be solved with a single grand plan. It must be outpaced by a smarter system of reform. That means moving faster than the problems emerge. Responding in weeks, not years. Watching data and acting, not waiting for headlines and doing a review.
This is a race against complexity, not ideology. If we get it right, the prize isn’t just a healthier budget, it’s a fairer, more sustainable system for Australians who genuinely rely on it.
I wonder what the chances of that happening are?
I suspect the can will be repackaged, and kicked down the road, again
Perhaps the hardest bit will be political resilience and determination to deliver the original objective of assisting Australians with profound and permanent disability.
Aug 22, 2025 | Analytics, Branding, Marketing, Uncategorized
The Pareto principle, the 80/20 rule with variation in the numbers, works in every situation I have ever seen.
Almost.
It is the exception that makes the rule.
Marketers use it extensively to allocate marketing budgets across competing arenas. Define your ideal customer, understand purchase cycles and habits, recognise different behaviours in different channels and circumstances, and allocate accordingly.
It always seemed to both make sense and work well.
Until it did not.
Research done by Andrew Ehrenberg, Gerald Goodhardt, and Chris Chatfield in 1984 produced a statistical model called the ‘Dirichlet Model‘. It is a statistical reflection of how consumers actually behave across FMCG categories. The model showed that rather than repetitive brand loyalty, most consumers buy from a small repertoire of acceptable options.
The model reveals that many people purchase a brand only now and then, yet collectively they represent a huge share of total sales. This counters the popular pareto model that assumes 80% of profit comes from the top 20% of buyers.
Hovering around supermarket shelves in the eighties, observing consumer behaviour, and interacting where possible, the truth of this counter intuitive behaviour was clear. However, the pull of Pareto was powerful, so we often had a foot in both camps.
It is the mid 1980s, and yogurt is the new category growth star. Ski and Yoplait dominate store shelves. Shoppers have their personal preferences, some lean strongly toward Ski, others swear by Yoplait, and many have their flavour favourite across both. (they prefer Ski Strawberry to Yoplait, but the Yoplait apricot to Ski) A few smaller regional players also vie for attention, but if there’s a promotion, most consumers happily mix it up.
As the marketing manager that included Ski in the brand portfolio of responsibility during these heady growth days, it was easy to assume the Pareto principle held: 80% of profits come from 20% of devoted buyers. Focus on those heavy consumers, turn the moderate fans into loyalists, and watch the profits roll in, right?
The Dirichlet model exposed the paradox, although at the time I had not heard of it. However, the numbers coming from store sales data and simple observation of consumer behaviour in stores confirmed the consumers disassociation from the theory of Wilfredo Pareto.
So, how does the Dirichlet model suggest fast moving consumer marketers build their brands against competitive brands and the power of retailer ‘pirate’ brands?
Acknowledge Mixed Brand Buying.
Even if you’re proud of your loyal fans, don’t be blinded by them. Ski-lovers might switch to Yoplait for a flavour your brand doesn’t offer, or vice versa. The data shows people happily shop around, even if they have a ‘Favorite.’ Acknowlede that behaviour while creatively giving consumers reasons to buy yours in preference to others.
Look for Wider Reach.
Heavy users are part of the story, but broad availability is often the bigger deal. If your products aren’t visible, buyers won’t remember you at that decisive moment.
Keep Things Distinctive.
You’re not just building brand awareness, you’re building mental availability. That’s how you stay top-of-mind when the shopper sees a new promotion or wants a unique flavour. Whether through catchy ads, recognizable packaging, or fun limited-edition variants, it’s all about creating mental triggers.
Rotate and Refresh.
Both leading yoghurt brands tested new flavours and replaced underperformers regularly. This strategy not only sparked interest among loyal buyers but also tempted the light or occasional buyer who came for the novelty, and might just pick you again next time. It also pleased retailers to have a supplier that explicitly had a ‘one in one out’ brand policy.
Ultimately, the Dirichlet model teaches us that brand loyalty isn’t an all-or-nothing affair. Even with strong preferences, people jump around.
Consider that next time you’re rethinking a marketing campaign. It might feel odd to invest in those who buy you only once in a while, but that large group can deliver a collective boost that keeps you on top.
Header by AI
Pareto killed by Dirichlet in blogs
The pareto principle holds in every domain I have ever seen, except one.
To build a brand, you must keep existing customers, increase their preference for your brand, and attract new customers.
A pareto allocation of marketing funds would imply that most of your budget should be aimed at the 20% of customers that produce 80% of your profit.
That allocation would work against you.
Truly loyal customers are less likely to go elsewhere than light or occasional buyers, and such an allocation does nothing to attract new users.
In this case, Pareto was wrong.
