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’
Jan 24, 2025 | AI, Marketing
Close your eyes.
Now think of the sound that happens when you open Netflix or HBO, the cello riff at the opening of Game of Thrones, the McDonalds ‘ba dada boop ba’ that ends every ad.
You can ‘hear’ them in your mind, they are an unambiguous reminder of what you are about to see and hear.
Think now of a song that meant something important to you when you were growing up. All you need are the opening bars of the music.
Can you feel the emotion that memory brings?
We humans are very tuned in to music (apologies for the poor pun). Somehow is sticks in our brain, and opens a door to our memories, emotions, and situations.
How would you like to have a sound that to your customers, wider networks, and those who have a casual acquaintance with your brand, brings your value proposition straight into their brain?
In the past that marketing luxury has been the territory of large companies with large marketing budgets. You had to pay songwriters, musicians, pay royalties, hire studios, session singers, or even celebrities.
All very expensive and time consuming.
Not now.
Now you can do it in a few hours at most with an AI tool (CHAT, Claude, Gemini, et al) that will write lyrics for you, and another tool to deliver you the sounds to order. Want your lyrics to be performed in the genre of country, pop, hip-hop, metal, whatever, tell the tool, and it will deliver. It will take some iterations, and prompting can be a challenge as music is much less specific than prompting using text., but you can get there.
There are several AI sound generators. Suno.ai is the tool of choice of a mate who has experimented with several, and which I found to be amazing, but there are others.
Want that sonic brand identifier?
It is now easily within your reach.
Jan 13, 2025 | AI
‘Tokenisation’ is a term bandied about by my AI literate colleagues, commonly at least 40 years my junior. Usually, the term is used in the context of ‘it takes X number of tokens to complete this job’ or similar.
In AI, tokenization is like breaking a sentence or text into smaller pieces (tokens) so that a computer can understand and based on statistics, predict what the next word (token) will be. The process takes a paragraph and chops it into words, parts of words, or even individual letters now called tokens. This then enables the system to find patterns and make predictions of the next part of the text using probabilities derived from the context represented by the previous tokens.
All AI platforms like ChatGPT, Perplexity, Claude, and myriads of tools that have emerged from the woodwork over the past 2 years, are trained to understand and generate tokens in this manner. They ‘learn’ by examining tons of text and figuring out how words and sentences relate to each other statistically. Tokenisation is the first step in this process.
When you give text to an AI tool, it:
- Breaks the text into ‘tokens’.
- Assigns a number to each token (a kind of code).
- Processes these numbers to understand statistically the patterns and relationships.
- Uses this understanding to answer questions, summarize, or generate text or in some cases, a graphic representation of the tokens.
There are different ways to break down text, depending on the instructions given to the model. It is also why the response to instructions can sometimes go crazy, as the machine does not always ‘hear’ what you thought you said. The placement of something as simple as a comma in the instructions can, and often will, alter the output.
This breaking down of text into ‘tokens’ is an essential step in the AI process. It is all about statistics and patterns, without any meaning as we understand it being given to the words themselves.
AI is a predictive machine that gives you the next most likely outcome given the instructions you have given the model. The way those instructions have been interpreted based on the way the tokens drive the patterns and relationships, delivers the outcome.
It is also how AI can work across languages, and why it consumes huge amounts of energy to run the billions of statistical calculations underlying the response it gives.
The above is a vast simplification of the process, but it ‘sort of’ satisfies an old marketer like me, trying to understand this new world that has suddenly arrived on my doorstep. It also explains the limitations of the models, as the ‘training’ is done on existing data. The system has no capability to leverage ‘knowledge,’ that human capability that enables completely disconnected facts and ideas to be put together in entirely new ways. I can only assume that this is where the current research is directed, building the ‘neural networks’ artificially, that we have as an outcome of millions of years of evolution.
Jan 6, 2025 | AI, Strategy
This time of year is filled with self-congratulatory posts, the ‘Ten best posts of the year’ types. All of them I see, use as the measure the number of views, shares, and other external measures to rank them.
I am going to be different.
The posts I put up come from two places.
Firstly, the experiences I see amongst my group of clients and similar, mainly but not exclusively, SME manufacturers. Some are service providers of various types, but all are SME’s. Sadly, none who can or would pay the consultant rates routinely scooped up by institutional consultants with large offices filled with eager MBA’s who have not experienced anything beyond a sophisticated student piss-up.
Secondly, from the frustrations I feel as I scan and negotiate the economic technical and commercial environment, being the antennae for those few clients who put up with my garrulous nature disguised as wisdom, and wide and deep commercial experience.
The published posts are the outcomes of the usually conflicting ideas, opinions, and reading of that landscape, that goes on in my brain. I write to sort it out, at least a bit.
The tsunami of AI generated ‘content’ combined with the continuing evolution of the algorithms means my meagre readership has eroded over the last year or so, going down by 30-50%, depending on your starting point.
Part of me wants to tear my hair out, what little is left, but the reality is that writing these posts is a selfish activity. I benefit from the exercise, and if that spreads to a few others, great, if not, too bad.
Therefore, my list is of the 10 posts that reflect the original thinking, research and wisdom of the years I bring, or try to bring to everything published, but which got almost no traction at all. In other words, the best of the 2024 that were also the most ignored.
In no particular order beyond the month in which they appeared.
- Is another government review an answer to our slide down the complexity rankings? https://wp.me/p5fjXq-3hd December. This is fairly recent, so perhaps there is time yet for it to get traction. Yeah…maybe not. We are a complacent bunch, and it seems no number of words, moaning, and harsh critique by a few will shake us out of that state. It needs a bloody good crisis!
- The large, uncalculated cost in your business. November. https://wp.me/p5fjXq-3ge I have never seen an adequate review of Opportunity cost in any strategic or planning document. Yet, it should be a significant factor in any resource allocation choice, as resources are finite. I guess it is too hard? Years ago I made an attempt when arguing for a long term commitment to brand advertising as an investment. I argued that rather than treating advertising as a short term variable expense in the P&L, it should be seen as an investment in future profitability. My analysis, based on the flimsy empirical evidence available at the time, opinion, and case studies clearly showed the long term benefit to profitability. While there were many arguable points, I was unaware of the key, deciding consideration. The MD was planning to retire early, and so was completely disinterested in the long term profit at the expense of the short term, upon which his bonus was calculated.
- Positioning: The secret weapon of aspiring market leaders. November. https://wp.me/p5fjXq-3g2 . Positioning is an old fashioned marketing idea, widely misunderstood by todays ‘marketers’. It is not just a catchy slogan, it is a strategic framework, a statement of how value is added, that drives resource allocation choices.
- The increasing value of intangibles. November. Again. (I must have been taking something in November) https://wp.me/p5fjXq-3gv The evolution of our economy from a base that requires hard, tangible assets to one that is based on services has a flip side. The value of an enterprise is now almost wholly dependent on intangibles. This is the value ascribed to your customer base and relationships, documented and managed processes, capacity to innovate, strength of the ‘management bench’ strategic position in a market, and many others. None of these appear in a balance sheet. Traditional accounting fails monumentally at reflecting the value of a business as a result.
- Institutional memory as the critical component of future success. September. https://wp.me/p5fjXq-3eV As life has sped up, become remote, is increasingly locked into screens and the tools accessed by screens, we are in great danger of losing the institutional memory that prevents us from repeating mistakes. When we lose the memory, we are more likely than ever to ensure that history repeats itself.
- Breaking up supermarkets: A really stupid idea. July. https://wp.me/p5fjXq-3ej ‘Colesworth’ has been on the receiving end of much negative, and in my view, totally unwarranted comment. They are regularly accused of ‘price gouging’ by uninformed commentators, politicians seeking an easy target, and simply those in the queue waiting to pay the increasing costs of a weekly shop. The negative commentary demonstrates conclusively the ignorance of those commenting on the drivers and dynamics of the supply chains that exist to serve supermarket customers. Almost as an aside, it should be understood that every Australian with a managed superannuation fund is a stakeholder in one, and mostly both, Coles and Woolworths. In other words, if you are unfortunate enough to be in a queue of 10 people waiting to pay the checkout bill, 9 of them are stakeholders in whichever ‘Colesworth’ store you are in.
- Strategy does not include execution. May. https://wp.me/p5fjXq-3dj Most management groups I have seen, and been a part of, undertake some sort of ‘Strategic planning’ exercise. In that process, 10% of the time is spent on strategy, the rest is spent on execution, or ‘budgeting’ as the usual shorthand. Not only does this grossly underestimate the challenges of genuine ‘strategy’ development, it conflates two profoundly different processes. It is like trying to mix oil and water, stir all you like, they will remain separate, and using them together makes both way less effective.
- Four strategic tasks for the owner of a successful SME. March. https://wp.me/p5fjXq-3cu Every business I deal with wants to scale for a whole range of reasons that all boil down to the simple truth that scale delivers options and further growth and profitability. Most fail. They might survive, but they survive as an SME that requires the owner to be in the weeds on a weekly, and usually daily basis. That is not success, that is buying yourself a job, that usually comes with stress, and less financial rewards than are achievable elsewhere.
- Revolution by Digital: a survival necessity. February. https://wp.me/p5fjXq-3bd In February the impact of AI was just being felt and seen for the first time by many. Few had done any more than play with the early version of ChatGPT, and most of them had come to the conclusion that AI was little more than another cog in the hype-cycle. Digital to most was still a vague term that led to added cost and confusion. A year later, and it is dawning on most that ‘Digital’ meaning the adoption of AI into their enterprises is a life and death choice.
- The two most important words in Strategy. January. https://wp.me/p5fjXq-3aY Libraries have been filled with well intentioned, academically sound analyses of strategy, along with a big lump of flimsy, self-serving stories of success. The latter group always fail to articulate the many hundreds of times their magic strategy potion had failed, only reflecting on the successes, and then they are often as much good luck as good management. In my world, there are two words that summarise a credible effort to build a strategy that will offer the guardrails and macro performance measures of a viable long term strategy. Imagination, and Possibilities. Application of these two drivers of human behaviour in concert will lead to strategic conclusions worth the paper they will end up being written on. Absence of either, and at best you have a budget.
That is my ten most unfairly ignored posts for the year.
I had a lot to choose from. Over 150 mostly ignored posts, all coming from my observations of the strategic, competitive, and regulatory constraints under which we, and most specifically my few clients operate.
None have been spawned, copied, or revamped from the tsunami of stuff spewing from AI generators. Every word is mine, and mine alone. The commentary on AI, of which there is a fair bit, is again mine. My comments reflect the importance and potential of the geometrically compounding impact of AI, and my frustration at the apparent lack of interest evident amongst the business sectors I seek to work with to improve performance by leveraging the potential of AI.
It has been a tough job picking the top ten ignored posts. This blog generates very little traction, although the feedback from those few who are regular readers is encouraging.
As a last observation, I add the first post I wrote after ChatGPT was launched on November 30, 2022. Published on December 19th 2022, just two weeks later, the post asked the first question everyone asks, ‘will it take my job‘? Progressively over the first few months of 2023, I added 20 addendums to the post as I stumbled across more and more tools, use cases and understood better the implications of AI. By then, there was general awareness, and hundreds of newsletters that did a better job of keeping track of this digital tsunami as it surges across our lives, so I called ‘time’ on the post. I have however come to the conclusion that AI will not take jobs, but individuals that use Ai will take the jobs of those who do not.
Dec 16, 2024 | AI, Leadership
The characteristics of leadership we expect from the local nonprofit or sporting club, to the largest businesses in the country, to the Prime Minister, are pretty much the same.
Trust.
We need to trust them. Trust is earned by the behaviour we observe, never just given. It is also incremental, built over time, but is also fragile, and can be brought down in a minute by one bad example. The test, if there is such a thing is whether we believe that the private conversations the ‘leader’ is having are the same as the public ones, and would they be prepared to say those private things on the 6 O’clock news. By this test, many in prominent so called ‘leadership’ roles in this country fail. Dismally.
Dependability.
This has many forms, from delivering on the big promises made, to turning up on time for an appointment with the local hairdresser. In any leadership role, no matter the size, when a real leader finds themselves from time to time unable to deliver, they do not walk away from the fact, they acknowledge the failure, learn from it, and move on. To many, this is the essence of leadership, to me, in it’s simplest form, it is just common courtesy painted on a wider canvas.
Competence.
Someone placed in a leadership role, who is an example of the Peter principal is corrosive to the rest of the organisation. Those being led must believe that the leader is someone they can follow, and learn from. That does not mean they never make a mistake, it does not mean they are never unsure of themselves, or exhibit human frailties, it just means that we believe that they have the wisdom, skills and experience to get the job done.
Humanity.
We are herd animals, we rely on those around us for safety, and security. We have evolved and prospered as a species because we are able to collaborate and care for one another and rely on our neighbours in times of stress and crisis. In short, we care about others. Someone in a leadership position who does not care about those being led, is not a leader, at best they are a manager, dispensable and easily replaced.
When an individual displays these four characteristics, followers just seem to appear.
Header by DALL-E, who cannot be made to spell correctly no matter how hard I try to get its digital brain cells to listen!!
NOTE: Before posting this, I saw I had written an almost identical post a few years ago. While the four parameters are the same, the way I expressed them is a bit different. So, rather than scrapping it, as i have done before when realising i am repeating myself, I elected to post it anyway. Repeating a good idea is rarely a bad thing.
