Feb 14, 2025 | Governance, Leadership
Trust has been trashed. Governments, institutions, and entire communities have eroded it for decades. The decline started in the late ’60s and has not slowed.
We are heading into an election in a few months.
Last time, both major parties barely scraped a primary vote in the 30’s. In my lifetime, that number has dropped from close to 50%.
People no longer trust the system.
I’ve been around long enough to remember when this rot set in. The Vietnam War was the turning point. The official reports were a little more than wishful thinking and deception. Every night, TV screens told a different story from what the official version of what was happening told us. It was the start of an endless conga line of lies, misdirection, and cover-ups that continue today in Europe and the middle east, as well as everywhere else it seems.
As the lies piled up, trust in institutions crumbled. For years, the erosion was slow. Then, in the mid-’90s, the internet arrived and kicked it into high gear.
Suddenly, we had access to opinions, ideas, and facts that had been previously unseen by all but a few. Today, we carry the internet in our pockets. The moral authority that institutions once held is gone. They may still have legal power, but their credibility is best likened to an old fashioned snake-oil salesman.
The world has shifted from ‘Ownership’ to ‘Performance.’
Consumer behaviour and expectations have changed far more quickly than the institutions that supposedly govern that behaviour. Ownership is way less important than previously. It is being replaced as we speak by ‘Utility’. Increasingly we seek to control the outcome far more than we seek to control the means by which that outcome is achieved.
We don’t want to own cars. We want transportation. We don’t need DVDs. We want instant access to movies, music, news, and so on.
Business models have shifted from ownership to pay-as-you-go. The advantage is the reduction and often removal of entry and exit costs. Without sunk costs, we are free to move when we become dissatisfied for any reason.
People now pay for results, not promises. Performance, not possession. That means institutions of all kinds, including businesses, must be transparent and accountable.
Trust, Accountability, and the Business of Outcomes
I’ve spent 25 years as a consultant, building trust by guaranteeing outcomes. I’m not McKinsey with a glossy reputation. I’m an old bloke who’s been there, done that, and has the results to prove it. Clients trust me because I make them a simple promise: if I don’t deliver, they don’t pay. That’s real accountability.
Banks, politicians, corporations, service providers, every institution of every type, should take note. People aren’t buying your stories anymore. They are buying results, and they have the wherewithal to check your claims against the outcome.
Even churches face this challenge. Selling faith has worked for centuries, but evidence of the afterlife only comes after you’re dead. That makes customer retention an act of faith only. That said, religious institutions are among the best marketers in history. If anyone can adapt, they can. However, to an agnostic like me, they have not shown anything like the agility required to retain followers as the capacity for critical thinking and fact checking increases.
The bottom line? Humans need something to believe in.
If institutions want trust back, they need to earn it, not just tell us they deserve it.
Feb 10, 2025 | Leadership, Management
When most people hear the word dissent, they think, troublemaker.
And sure, dissent can ruffle feathers. It challenges the status quo, pokes at comfort zones, and often triggers defensiveness or knee-jerk loyalty to “the way we’ve always done it.”
But here’s the thing: dissent, when done right, is one of the sharpest tools in your decision-making arsenal.
Dissent can expose blind spots, cracks in logic, and perspectives you might otherwise miss. It’s also constructively contagious. When one person feels safe to question the narrative, others find the courage to share their own opinions. That is how real progress gets made.
Too often, dissent is misread as a personal attack. Instead of hearing a critique of an idea, people take it as a critique of themselves. Cue the drama, defensiveness, and derailed conversations.
This is a sensitive balancing act for leaders.
Effective leaders know dissent isn’t just a “nice-to-have,” it’s essential. If you’re surrounding yourself with “yes people,” you’re not leading, you’re herding.
Leadership means being secure enough to invite challenges to your thinking. It says, “I care more about the right outcome than about being right.”
I once worked with a leader who actively encouraged what he called “impersonal dissent.” It was not a free-for-all. It was a structured process where we played devil’s advocate on every significant decision. The thinking was simple: the more diverse the viewpoints expressed, the more we leveraged available relevant data, the better we would understand the problems, explore possible solutions, and therefore optimise the odds of a positive outcome.
One plus one was not just three, it was exponential in value.
But here’s the kicker: it wasn’t a democracy. When all the arguments were on the table, the leader made the final call. And when the decision was made, the dissenting voices stopped, by convention, the decision became a group decision which all supported. That balance between encouraging dissent but knowing when to move forward was key to our success.
I discovered the downside when that person to whom I had been reporting left the business. I was elevated into his role, now reporting to an MD of the group whose view of dissent was different. Being still young, and somewhat impervious to his displeasure, believing I had the runs on the board to claim the right to ask questions and argue a dissenting perspective, I did not last beyond the first ‘restructure’.
Header courtesy Scott Adams and Dilbert.
Feb 6, 2025 | Analytics
The Rule of 72 is a ‘rule of thumb’ calculation used to quickly estimate how long it will take for an investment to double in value, given a fixed annual rate of return.
It was first introduced by Italian mathematician Luca Pacioli in 1494, a collaborator of Leonardo Da Vinci. Pacioli is best known as the codification of double entry book-keeping, and the reporting of transactions via journals and ledgers, and outcomes via profit and loss and balance sheet.
His Rule of 72 is widely used in the initial ‘back of the envelope’ assessment of investment options.
The formula is: Years to double = 72/Annual rate of return.
For example, if an investment has an annual rate of return of 8%, it will take around 9 years to double. (72/8 = 9)
The rule can be used to make reasonable estimates of a range of outcomes, such as how long it will take for money to lose value due to inflation, the impact of compounding interest on debt, and evaluating the impact of service fees.
Be careful however, at best the calculations will be estimates, reasonably accurate at rates between 5% and 10%. Outside this range, the accuracy will suffer due to the non-linear nature of compounding growth.
Feb 3, 2025 | AI, OE, Small business
Sledgehammers in skilled hands can be both a significant tool of productivity, and a destructive force.
AI is the newest sledgehammer on the commercial and personal block.
It gives everyone the opportunity to write a blog, book, opera, make a movie, paint a landscape or portrait, or post an outrageous opinion. It is the most democratising technology ever invented.
What AI does not do, and will never do, is replace the quality of thought and creativity that humans are able to bring to a problem, situation, or creative exercise. However, AI can amplify human ingenuity by offering the opportunity to greatly increase the quality, efficiency, and breadth of thought an individual can bring to a situation.
For small manufacturing businesses and their supply chains, AI is typically seen as a productivity tool. Indeed, it excels at optimising operations, streamlining workflows, and enhancing quality control. More importantly for the future however, it is a tool that expands capabilities, enabling businesses to innovate faster, respond dynamically to market demands, and identify new opportunities before competitors do.
Imagine brainstorming sessions supercharged by AI, where potential solutions are generated, refined, and paired with actionable deployment plans in real-time. This can give small manufacturers a significant edge, allowing them to pivot swiftly in response to challenges and lead their industry through innovation rather than follow.
This has profound implications for talent acquisition and retention.
Rather than just focusing on traditional technical expertise, increasingly available via AI, businesses should prioritise those with ‘flexible minds.’ These individuals may not always be top-tier engineers in terms of mathematical skills, extremely creative marketers, or inquisitive operations managers, but they excel at envisioning multiple outcomes and solving complex problems creatively and rapidly. They can visualise scenarios, identify risks, and devise solutions backwards and forwards, often outperforming those who think only sequentially.
This ability will equip employees for the increasingly complex, variable, and competitive world of modern manufacturing. By leveraging AI to empower employees to perform tasks outside their established skill sets, small businesses can boost innovation, adaptability, and resilience. This not only enhances productivity but also builds a workplace culture that fosters satisfaction, motivation, and long-term growth.
In the past, I have advocated that the primary consideration in identifying productive employees, after being very clear about the required skills to do a job, is curiosity. The emergence of AI elevates curiosity almost to the level, and in some cases, above, the requirement for specific skills.
The risks of ignoring AI adoption are stark. Competitors who embrace AI will gain efficiencies, reduce costs, and innovate faster. Businesses that delay integrating AI will find themselves outperformed, struggling to keep up with quality expectations and delivery timelines.
The question small manufacturing businesses should ask themselves is: Are we willing to risk falling behind, or are we ready to lead the industry through smart, strategic AI adoption?
By increasing participation, independence, and the breadth of employee skills through AI integration, small businesses can secure their competitive advantage and thrive in an AI-driven world.
Jan 29, 2025 | AI, Governance, Strategy
The tech news of the decade blew up on Monday January 27, 2025.
Nvidia, the darling stock of the AI revolution dropped six hundred billion (17%) in market capitalisation in one day. This is the biggest one day loss in stock market history. It sparked a selloff of other tech stocks, leading to a sector drop of 5.6%.
Has the bubble burst, or is it just the theories of Clayton Christianson writ large, again?
The spark was the recognition of the impact of the Chinese AI architecture represented by DeepSeek R1 by the technical wizards and stock analysts.
Surprisingly, DeepSeek released a research paper outlining their approach to AI training. This details an architecture that dramatically reduces cost and complexity of training LLM’s while delivering results at least as good as OpenAI and comparable models. It took a week or so for the described technology and results to be absorbed and understood, culminating in Mondays panicked sell-off.
Is this a bubble bursting or just a sensible reordering of expectations?
Two factors outside corporate malaise have dogged my innovative efforts over the years, both of which are in play here:
- The notion that innovation takes place in an environment of constraints. While history demonstrates the truth of this, the stories we tell ourselves celebrate what appears to be great innovation emerging as a result of chaos. In this case, the restrictions placed on China getting the existing technology created restrictions they have beaten.
- What I call the ‘Christianson effect’, better known as the Innovators Dilemma, after Harvard professor Clayton Christianson is proven accurate time after time, after time. Again, Christianson accurately saw that a high cost solution to a problem would eventually be replaced by a much lower cost solution to the same problem. DeepSeek is just another example of the power of his observation.
The US under the Biden administration for security reasons put export bans on Nvidia chips, chipmaking tools, and development software. These bans covered US allies in an effort to isolate China from the Intellectual capital as well as the means to bridge the technology gap that suddenly appeared. It would appear that rather than accepting the ban and going home, the Chinese reacted by using the ban as a motivator to rethink the engineering of the guts of AI systems, and come up with a solution that addressed the two hurdles facing current AI:
- The enormous amounts of data required to train the models.
- The huge drain on power required to process even modest requests to the models for a response.
Both it would seem, are gamechangers, as the cost reduction probable for AI platforms is enormous.
The real question for those who run businesses that use this technology, or are starting to use it more generally in our lives, which is all of us, is what comes next?
Here is what I think, assuming the initial hype is close to the mark, and not another chimera like the Theranos scam.
- The huge allocations of capital being made by the big US companies, Microsoft, Google, Amazon, and Meta, will be put on ice. Nvidia has hundreds of billions of dollars in orders from these giants that it cannot currently adequately fill. Some if not many will be quietly cancelled.
- More billions allocated to build the infrastructure to accommodate the models, big chunks of expensive land, and power sources will also be slowed down. For example, the project called the ‘Stargate project’ triumphantly announced last week by the president involving a 500 billion dollar investment by the government will become just another Trump press release consigned to the round file. The project as outlined is a JV with Oracle, Microsoft, Softbank, and others to build AI capability in the US. It represented an equity investment by the government in the commercial leveraging of emerging technology, a first. I also speculate that the proposal to fire up a mothballed nuclear reactor at 3 Mile Island by Microsoft will require a rethink, although it may have just been at best, a thought-bubble.
- The disruption created by the DeepSeek technology will redirect the tsunami of capital towards Chinese technology, until the next innovation iteration comes along. This will both geometrically accelerate the rate of adoption necessary by business if they want to keep up with competitors, and make the current security concerns surrounding Tik Tok look trivial by comparison.
- The disruption might ‘democratise’ the use of AI in the sense that it will be more widely available once the costs are dramatically reduced. Alternatively, it may mean that the existing ‘moat’ controlled by the current crop of AI platforms, all American, will be replaced by a Chinese moat.
- Regulating AI in some way has been a topic of frantic debate since OpenAI launched Chat. To observe that regulators have no idea would be accurate. Now, instead of regulators being caught with their pants around their ankles, it is apparent that their pants, if they own any, are secure in the wardrobe. In a regulatory and geopolitical sense, we are spinning out of control.
- The rate of development of systems that enable humans to expand the reach and depth of the intelligence we evolved to have will be extended at a rate that is further accelerated by the huge reduction in cost that appears probable as a result of this Chinese breakthrough. We had better all start learning Mandarin.
As the old Chinese saying goes ‘We live in interesting times’
