Sep 21, 2026 | Management, Strategy
The world is divided in many ways, but every way that divides also compresses down to a strategic choice most do not consider.
Are you operating in a world dominated by a Gaussian distribution, or a power distribution?
We are all familiar with the normal curve, which is a gaussian distribution. Many, if not most things across the commercial, natural, and institutional worlds we live in operate on a normal curve. Human height, manufacturing variation, travel time to work, cricket scores, heads thrown in a game of two-up. All are plottable in a normal curve, and the larger the sample, the more ‘normal’ the curve becomes. It is the statistical basis of every political poll you have ever seen.
Italian mathematician Vilfredo Pareto noted the wildly differing income levels amongst Italians. This pattern did not comply with the normal curve leading to the insight that reversion to the mean did not apply at a micro level. The differences in income of individuals, 80% of which accrued to 20% of Italians, led to the 80/20 ‘Pareto rule’.
Wherever you look, you see the pareto rule at work. A closer examination often also reveals a power distribution playing a key role.
Cricket is a game where the scoring is constrained by the maximum of 6 runs. Hit the ball over the boundary on the full, and it is six runs. Whether the ball clears the boundary by an inch, or by 100 meters, the maximum runs scored is six. However, if you were to perform a power distribution of the batsmen who had hit a six in test matches, the 80/20 rule prevails. Of the 1,828 sixes scored by Australians in test matches over the last 25 years, the top five batsmen scored 79.6% of them, the other 448 batsmen combined scored the other 21.4%.
By contrast, Rugby league is not constrained by a maximum. The score in Saturday evenings semi-final game between Cronulla and Easts was 46 to 10. The commentators were discussing the chances of Easts breaking 50 in the last few minutes of the game, as there is no limit applied to scoring beyond the time of the final whistle ending the game.
These differing perspectives lead to the question referred to in the header: Are you in a commercial context that is constrained by a reversion to the mean, or are you competing in a ‘pareto-like’ context?
The obvious follow up question is ‘does that optimise the commercial outcome’
The domain you are in drives the nature of the strategic choices made.
A domain dominated by a power curve business model is one where many bets are laid, knowing most will fail, but the few that work will deliver a disproportionate share of the total value delivered by all bets. The challenge is that those that will deliver the disproportionate outcomes are unknowable when the bets are laid. Typically venture capital works in this domain.
To continue the cricket analogy, coaches might look for the characteristics that made Gilchrist, Smith, and Co the outliers amongst the long tail of cricketers who score none or few sixes in their careers, and coach them to hit those sixes. Most will get out even more quickly than they normally would if trained for defence, but perhaps one or two might join the elite group in the 20% club.
In the bell curve or gaussian analysis, incrementalism is the driving force. Coaching the average test bowlers to turn their average test scores from 6 or 7 into the teens over time will optimise their capacity to contribute to the total reliably.
Long term success depends on both approaches being applied judiciously, as trade-offs must be made.
Scott Boland has a bowling strike rate of 39 balls per wicket of Australian test bowlers over the last 25 years, and a batting average of 9. He struggles to find a place in the test team other than in the absence of Hazelwood, Stark or Cummins, despite having the best balls/wicket ratio. (let’s not debate the obvious impact that his balls/wicket ratio is heavily influenced by his astonishing 7 for 55 in the 2021 boxing day test)
As someone running a business, you must also make these trade-offs between incrementalism and ‘hitting for the fence’ in the ways that best suit the circumstances of the business and its competitive context.
Note: explanation of header graph.
- The top 5 scorers of the 1,828 sixes hit over a 25-year period, Gilchrist 5.5%, Hayden 4.5%, Ponting 4.0%, Warner 3.8%, and Smith 3.7%, together account for 79.6% of all sixes hit by all 453 Australian test batsmen over the last 25 years.
- 276 players hit no sixes, the average being 3.9 sixes each.
- Gilly, is 8 standard deviations from the mean, making him, as we knew, a freak!
Sep 11, 2026 | retail, Strategy
Coles and Woolworths annual reports are boring, self-serving documents, unless you are an engaged shareholder. However, behind the fluff there are hints of the rules suppliers must understand if they are to prosper.
Aldi being a private company is not required to release the level of detail of their public rivals, but by observation, while still well behind the two gorillas, the race is now a three horse race. Aldi uses a different business model tacked onto the same universal drivers of Supermarket retail that drives Woolies and Coles.
Australian supermarkets are not free markets. They are tightly controlled ecosystems, choreographed by Coles and Woolworths. Suppliers are not selling to consumers, they are they are selling to gatekeepers who own access to consumers and therefore set the rules of the game. A supplier must play by their rules, or choose not to play, and there is no middle ground.
Few supplier hopefuls who do not understand the hidden rules of engagement until too late escape with their capital intact. However, this does not stop them trying, as the allure of all that volume is powerful. Tactically the rules have evolved over time, exclusively in favour of the retailers, but the foundations remain the same as they have been for decades.
Shelf space isn’t earned. It’s rented.
Retailers are not merchants there to provide easy access to consumers. They are retail real estate agents monetising every square centimetre of space. If your product doesn’t deliver a stronger return per centimetre than the one next to it, it will be replaced by an alternative.
You get a limited window of time to prove your worth. There is no elasticity in supermarket aisles, so it is generally one SKU in, one out.
You’re not just competing with other suppliers, you are also competing for shelf space with the retailer’s own label. Increasingly these are pushing out proprietary brands as the retailers can dictate prices and terms to the supplier, capturing at least part of the proprietary margin.
Buyer thought-bubbles are not R&D.
Your account manager returns from a meeting with a buyer and says, “They’re keen on a new lime and chilli variant in a smaller pack.”
Sounds like an opportunity, but most often it is a mirage.
Buyers like to speculate. They float ideas. They riff off competitor activity. Suppliers, chasing hope, redeploy R&D and tie up production resources on a buyers thought bubble. By the time the product is ready, it has consumed resources, created opportunity costs, and the buyer has had another thought bubble. Generally speaking, ‘buyer innovation’ is a total oxymoron.
Suppliers under-write logistics costs.
Retailers want frequent deliveries in smaller volumes, as it saves them money. Suppliers want the opposite for the same reason.
Suppliers however, do not get to choose. Miss a time slot, get fined. Deliver too often, lose margin. Fail to meet targets, risk delisting.
Driver shortages, fuel price volatility, traffic congestion, and demanding delivery windows, all combine to drive the costs to suppliers up. Meanwhile, the retailers book margin increases labelled in the annual reports labelled as ‘logistics efficiency’ or some other metaphor for pushing costs off their P&L, onto those of suppliers.
Exactly the same comment can be made about many costs incurred in the retailers domain. Suppliers fund category management costs, hold ‘safety’ stock to cover demand planning shortcomings, shelf management, promotional ticketing and stock display, and more. Retailers have squeezed out costs, but have been more successful in moving them to their suppliers
Their tech stack is your problem.
Everyone wants digital transformation. Few want to pay for it.
Most supermarket systems are legacy beasts—clunky, siloed, and allergic to integration. You’ll be asked to plug into their portals, match their EDI specs, and sync to their promotional calendars.
When it fails, and it often does, suppliers cover the costs.
Cash is always king, and suppliers are last in line.
Retailers pay their bills slowly. Always have. Meanwhile, you’re expected to pay your suppliers fast. That gap in timing is stretching working capital requirements of all FMCG suppliers. As interest rates rise, that pressure just increases.
SKUs tend to breed, chewing up supplier margins.
To chase growth, suppliers add SKUs, channel or retailer specific variants, seasonal specials and promotional darlings pushed by buyers.
Each one adds operational complexity, forecasting risk, warehouse clutter, and production cost. The volume gains are often marginal, but the margin losses are not.
SKU creep is a slow-moving death, and while it is tough to delete your own products, doing so makes listing a new one easier, and beyond changeover costs like excess packaging, does not increase the costs of complexity.
When your brand leaves the shelf, private label steps in.
Retailers are brand agnostic. They want control, exclusivity, and margin.
If your brand underperforms, it’s replaced. The space doesn’t sit idle, it is quickly filled by something cheaper, more compliant, and often owned by the retailer themselves.
To survive, you need more than a barcode. You need a story consumers understand and are prepared to actively choose, and you need the funds to get the message out. Working with buyers is a two edged sword, you need them backing you, while you need to make them look smart for backing you.
Forecasting is now a guessing game.
Retailers want tight service levels, lower order quantities, and increased frequency. These expectations contradict each other.
You can’t run efficient production with small, unpredictable orders. You can’t plan logistics around moving targets.
Every delivery window missed is a cost. Every forecast error is a stockout or a write-off.
Digital is your hedge, not your saviour.
Everyone talks about Direct to customer, E-commerce, digital platforms, marketplaces, and other descriptions. Yes, they matter. But they don’t pay today’s wages. Building digital capability takes time, capital, and clarity, and most second tier suppliers are burning all three just to stay afloat.
Digital is a long game. If you don’t survive the short game, you’ll never get to play it.
Final thoughts: Know the rules, or get buried by them.
Australian FMCG suppliers are not competing in a market. They’re performing in a theatre, with a script written by someone else, who is also the referee.
The shelf is a battleground. The margin is thin. The risks are hidden, and the penalties for ignorance are brutal.
To win, you need more than a good product, retail leverage, and consumer visibility. You also need a map of the minefield and the nerve to cross it.
Aug 31, 2026 | Branding, Customers, Strategy
Marketers, particularly those that emerged after the sudden take-over of marketing by digital platforms, love fireworks.
They talk about big creative ideas, reach, frequency, ideal customers and their profiles, attention and campaigns that become part of popular culture. Meadow Lea had all of that.
It also had a folding table, a loaf of sliced white bread and a woman who knew the product intimately.
That ordinary little table may have mattered just as much as all the hoopla.
In a market full of near-identical products, recognition earns familiarity, then the product feels like an old friend. This reduces mental effort and perceived risk.
Trust comes later.
Advertising can make a promise. Only performance can prove it.
Digital technology has made it easier than ever to start a business. A template, a payment gateway a social media advertising account, and a contract manufacturer can put you into the market by lunchtime.
It has also made it easier than ever to look exactly like everyone else.
Low barriers to entry enabled by digital tools and extended and readily available supply chains creates the opportunity for low-cost product imitation. The ‘noise’ generated by the presence of imitators drowns out anything but highly creative and distinctive brand building effort. This requires consistency, discipline, and a sequence of promise, proof, repetition, and memory to be delivered to consumers.
Advertising makes the promise. The product and the people provide the proof. Repetition turns that proof into an expectation, and the expectation when met consistently becomes trust.
Meadow Lea offers one of Australia’s great examples.
In 1975 I was a newly minted product manager at what later became Meadow Lea Foods. Mojo created the great “You oughta be congratulated” ads that turbo charged Meadow Lea’s market share from single figures in a highly contested and commodified market to around 23% of volume, and a greater share of value and profit.
That long running campaign did more than advertise a brand of margarine. It spoke directly to mothers at a time when more women were entering paid work while still carrying most of the domestic load. Rather than reminding them of another obligation, Meadow Lea congratulated them for what they already did.
The advertising gave the brand real meaning to those in charge of the purchase decision. National distribution made it easy to buy, and product quality kept the promise.
Then the program of supermarket demonstrations made the promise personal.
We selected and trained a small team of demonstrators in each state and kept them working in stores for 40 weeks of the year. They did not simply hand out pieces of bread, or dry biscuit with a smear of margarine on them. They answered questions, explained the product, listened to shoppers, and offered an immediate, risk-free trial.
Nobody entered a supermarket craving a square of white bread covered in margarine. That was only the conversation starter, a small piece of empathy delivered by somebody who understood the challenges being faced in a busy and fractured life that seemed to be changing daily.
The advertising said the brand understood its buyers. The demonstrator behaved as though it did. The first bite turned an abstract promise into evidence, by delivering the pat on the back the advertising promised.
Each demonstration closed a small part of the gap between what Meadow Lea said and what shoppers believed.
Most contemporary marketing teams would call the program difficult to scale. Many finance teams would call it labour intensive, tough to manage, open to shenanigans, and to the sales teams that carried the responsibility of organising the logistics, it was another task to be completed.
All were right, but they also missed the point.
The program worked because we repeated it. Week after week. Store after store. Conversation after conversation.
Someone had to recruit the demonstrators, train them, roster them, supply them and maintain the standard. Nobody won an advertising award for any of that. It was however a key to the work of building the foundations of the Meadow Lea brand.
Many businesses now reverse the sequence. They spend heavily making a promise, then leave the proof to an overloaded receptionist, an unanswered email, a poorly informed salesperson, or a late delivery.
Nothing destroys expensive advertising faster than cheap execution.
A brand operates like a trust account. Marketing opens it, but every customer experience either makes a deposit or a withdrawal.
One supermarket sample did not build Meadow Lea. Thousands of consistent conversations helped do it.
The jingle earned attention, the product tasting, evidence that the brand did what it said, earned belief.
Attention can make you famous.
Repeated proof or performance, and empathy with the key buyers builds trust, which creates a resilient brand.
Jul 20, 2026 | Analytics, Operations, Strategy
If a job that took eight hours now takes one, most managers will call that a productivity gain.
They are right up to a point.
Economists usually measure labour productivity as output per hour worked. If we produce the same output in one hour instead of eight, productivity has risen whether we use the remaining seven hours to win another customer, dissect the accounts, or head for the beach.
The beach does not cancel the efficiency gain, it simply exposes the limits of the measure.
The conventional measures tells us how efficiently we produced what it can already see. It tells us very little about what happened to the released capacity, whether the output improved, or whether technology enabled valuable work that nobody previously attempted.
It is a stopwatch with a blindfold.
This matters as businesses adopt AI. Most discussion starts with replacement: write the report faster, answer the email sooner, produce the first draft without paying someone to stare at a blank screen.
Useful, certainly but not transformative.
If AI cuts eight hours of work to one and the business fills the other seven with more of the same work, the gain will eventually appear in output, margin or capacity. If the business simply adds seven hours of meetings, the technology has delivered potential while management has squandered it.
That is not a measurement failure alone. It is a management failure with excuses.
The larger opportunity comes when AI extends what a business can do.
Most SMEs sit on piles of data they barely use. The accounting system contains patterns in customer profitability, purchasing, margin leakage and payment behaviour. The CRM contains clues about lead quality, objections, lost sales, response times and repeat purchases.
Managers have always suspected gold lies in those records, but lacked the time, skills or patience to dig it out.
AI changes the economics of the digging.
A business can now examine why apparently similar customers generate wildly different margins. It can compare the language used by prospects who bought with the language used by those who disappeared. It can identify which products create revenue but consume so much handling, discounting and after-sales attention that they destroy profit.
None of this necessarily replaces an existing task. Often, nobody did the task in the first place.
That makes “hours saved” a miserably small way to assess the value.
The better questions concern decisions improved, waste prevented, risks spotted and identified opportunities leveraged.
My commercial history includes a significant time driving sales and profitability of dairy products.
Take yoghurt for example. The supermarkets report a yoghurt market. That broad category helps retailers size the category shelf space, then allocate space to product groups, brands and individual products. It creates a ‘category map’ products and preparation of management reports. It conceals much of the behaviour that drives the sale to the time poor, budget limited, harassed by kids shopping consumer.
Shoppers choose between fruited and plain, low-fat and full-fat, pot-set and stirred, indulgence and health, adult and children’s formats, single serves and family tubs. Then they behave inconsistently, driven by the behaviours at home that result in consumption. Shoppers have never read the segmentation presentation, and do not care about it at all. The same persons trolley can contain Greek yoghurt for breakfast, a sweet pouch for a child, a set in pot natural yogurt for a fussy daughter, and a premium dessert for Saturday night, and be different on every visit to the supermarket.
Traditional analysis could reveal these patterns, given enough clean data, statistical skill and time. AI does not invent the possibility. It lowers the cost and effort required to pursue it, then allows a manager to question the data repeatedly rather than wait three weeks for another report.
They can uncover submarkets hidden inside the convenient fiction called “the market”. It can improve assortment, pricing, promotion and product development. The value comes not from producing the old market report faster, but from seeing choices the old report blurred out.
Then comes the hardest category: genuine innovation. Not the pack design change, or the ‘new improved’ standard product, genuine, category generating new products.
Every important general-purpose technology eventually enables products, services and business models that people could not sensibly describe at the beginning. We struggle to measure these gains because measurement follows observable activity. It cannot count a commercial possibility before somebody discovers it.
Nor do conventional accounts handle quality and unpriced value in anything but hypothetical terms. A better diagnosis, a more useful forecast, improved process, or a tailored customer answer may create considerable value without creating a measurable additional unit of output. We do not need to throw out existing productivity measures. They answer an important question and allow comparisons over time.
Businesses need a second dashboard.
Alongside output per hour, managers should track the use of released capacity, the valuable work newly performed, improvements in product quality and management choices, improved cycle and takt times, and new revenue or margin that technology made possible.
That is the productivity challenge in businesses.
AI will save time. This is an opportunity also available to competitors and especially new market entrants, unencumbered by past choices and technology. The sustainable advantage will go to the businesses that know what to do with the no added cost capacity that better use of time can deliver.
As an interim GM 20 years ago I was contracted to a manufacturing business that while marginally profitable, was struggling with capacity. Analysis revealed what everyone knew at some level, that a key step in the manufacturing process was acting as a bottleneck, strangling capacity. A number of relatively simple process changes that required no capital and no personnel changes enabled the key step to operate an extra 6 hours a day, effectively nearly doubling capacity. That resulted in shorter customer lead times, dramatic increases in DIFOT, abolition of outside warehouse costs, and very happy customers increasing orders at the expense of competitors. The changes took a couple of months to work their way through the financial system, but when it did, the impact on profitability was substantial. However, it was only with hindsight and deep digging into the numbers, that the changes in productivity numbers could be tracked.
The foregoing examines the productivity challenge of an individual business.
In the recent budget, and following discussions, the Treasurer has loudly and consistently pointed to the ‘productivity package’ contained in the budget papers.
The challenge in delivering on the promise, and having the electorate understand the complexity of the productivity challenge faced by the Australian economy is immense. It is easy to pick at the edges and observe ‘nothing to see here’ because the policy documents are shallow, predictably lacking in any real and measurable project timelines and checkpoints, and the press releases are as useless as the claims of a carnival hawker. It is however a start.
Jun 2, 2026 | Leadership, Management, Marketing, Strategy
A ‘heuristic’ is a ‘rule of thumb’ that takes the place of conscious calculation in the interests of speed and reduction of cognitive load in our brain. Cognitive overload creates the ‘friction’ in our brains resulting in indecision and anxiety. Heuristics, or ‘mental models’ bring the cognitive load down to a level we can deal with efficiently.
It is a function of evolutionary psychology.
To survive, you had to make a choice quickly about that rustle in the grass. Ignore it too often and you could end up as tiger shit.
Remember, we are all survivors of those who ran in order to not take the chance with the rustle being a tiger.
We all use these mental models daily, usually unconsciously.
In 2009 Chesley ‘Sully’ Sullenberger ‘landed’ the Airbus A320 he was piloting in the Hudson River after a flock of birds shut down both his engines on take-off from La Guardia airport.
He ‘knew’ without doing the calculations that he would not make it back to La Guardia, or the alternative airport of Teterboro in New Jersey.
His only option was the river, or a crash landing in populated areas of New York, and he had seconds to make the choice.
Subsequent investigations eventually confirmed his choice.
Sully applied unconsciously, a heuristic, a framework that was a result of his extensive flying experience, and knowledge of the gliding performance of the Airbus A320.
No data, no standard operating procedure that was useable, he acted and saved the life of every person on the plane as a result.
We all have a set of heuristics in our heads. The cumulative result of our experiences with life, and the context in which we have lived. We can either understand and leverage them to the advantage of ourselves and those around us, or we can fail to recognise their presence and power.
In your business, you are applying heuristics every day.
Choices that seem automatic: which customer to serve, who to hire, sales conversion, leadership choices, all are made with the assistance of heuristics. They are an essential and integral part of our management, but are only valuable when they are built from valid experience and regular testing and review.
You need to update your heuristics with regular feedback in the manner of an ‘after action review’ type analysis. What worked and what did not, where to lay the chips next time around, where to double down, and where to run.
When left untended, heuristics can evolve in suboptimal ways. Don’t leave yours untended, they may save you.
Feb 23, 2026 | Governance, Strategy
The political energy wars in Australia will flare again with the ascendancy of the right of the Liberal party, surging of One Nation, and relative gutlessness of the government.
The ‘debate’ will be about residential energy costs.
It is too easy for faux ‘Current affairs’ programs and politicians to find someone with 3 small kids not able to pay the electricity bill. That story gets splashed around as the core of the ‘national conversation’.
What is rarely given any oxygen is the impact of energy costs on industry. From the local coffee shop, bakery, and warehouse to energy intensive industries like smelting commodity ores, and cement.
When energy becomes too expensive, unstable or unreliable, businesses close, or relocate, and lift prices.
The principals of these businesses rarely get heard, unless they are a really major business like an aluminium smelter. As a result, the ‘debate’ will be about the wrong thing.
We should be talking about ‘energy sovereignty’.
Throw away the slogans, and work towards making energy one of the inputs to our way of life that we actually control. Why be a price taker at the whim of others, and a flailing and ineffective domestic policy vacuum.
Renewables are now cheaper than fossil fuel generated power, but the fight remains about the environment and retail prices, not cost and sovereignty.
Cheap power is rapidly becoming the strategic necessity of the 21st century. It shapes both national and geopolitical outcomes. Those who control power generation will end up controlling the economy. Foundational to control of power generation is the control of the essential elements in the power supply chain: lithium, graphite and other science fiction sounding minerals.
China is not only generating the cheapest power, but they also control the supply of these minerals from the extracted commodity to the final input to manufactured products.
Our focus on the retail price of energy is way too narrow.
We should be focussed on the strategic importance of the whole supply chain, and where in that chain strategic power can be exercised.
Currently Australia has none, but we have the potential to be a major global player.
That means bi partisan agreement on significant long-term investment with a long-term ROI measured by the standard of living of our grandchildren.
Is there any chance of all of that happening?
Header courtesy Tom Gauld at New Scientist.
