Mar 7, 2022 | Change, retail, Strategy
The supermarket business model, like most others, is evolving as we watch. It is slower in Australia than elsewhere given the challenge of distance and the stranglehold of Coles and Woolies. Nevertheless, it is evolving, and we can learn from elsewhere.
Four years ago, with great fanfare, Tesco in the UK launched a discount supermarket chain they called ‘Jack’s’. It was intended to compete with discounters Aldi and Lidl, to be the British hammer blow on the invading German discount retailers.
At the time, it seemed to me that the game was already up, that the position the discounters had carved in the market would be impervious to the exhortations of then Tesco MD David Lewis, calling Britain to arms.
Prior to the launch of Jacks, there was considerable shuffling of deck chairs as other retailers, Sainsbury and Asda particularly adjusted to the discounters by M&A. Since then of course we have had the fiasco of Brexit, still evolving amongst the shattered supply chains. This has been graphically illustrated by the carnage at the port of Dover, and inability of British farmers to farm in the absence of eastern European labour.
Now Jacks is closing, its promises of stores in every major town never eventuating. Jacks only ever opened thirteen stores, six of which will be converted to Tesco, the other seven just closed.
At the time in a post I reminisced on the demise of discounters in Australia, saying ‘I suspect history will reveal that Tesco has made a huge blue’. At least they recognised the mistake relatively early and reversed course under a new MD.
Given Australia tends to follow the evolution of the British supermarket sector by a year or two, what can we anticipate domestically, particularly from the two current retail gorillas, Woolies and Coles?
- I would not expect either to make the mistake Tesco made and open a discounter. In the past, both have dabbled with discount retail brands, none of which have survived. Besides, they have both watched as Aldi has carved out a place without launching a discount rival, it is unlikely they will change direction now.
- The doubling down on home delivery will continue, as will the logistic arrangements that support home delivery, and the technology that enables it.
- Retail is fragmenting. Consumer behaviour is evolving rapidly, accelerated by Covid. There is an obvious trend towards on-line and specialist retail using multiple channels of distribution, attracting consumers from their large-scale competitors by offering other than ‘average’ products. Some retailers are designing their stores as an ‘experience’ as much as a place to shop. These stores are a brick in the brand building wall, and are in effect, another form of media as well as a retail outlet. Apple saw this first, opening stores progressively around the world. By the traditional retail measure of success of margin/sq foot, Apple is now the most successful retailer in the world. At the other end, we see small stores, even ‘pop-ups’ selling very specific and focussed ranges. In between, shopping malls have passed their peak, the massive floor space they occupy will need to be re-purposed, at least in part. The potential here is for locally focussed office and residential hubs with a mix of specialist stores and entertainment venues.
- Direct to consumer from the farm is increasingly possible and attractive. Farmers markets will continue to grow and nibble away at the supermarket share of produce, by delivering superior taste and quality. I love so called ‘summer fruit’, peaches, nectarines, and plums. Finding any in a supermarket that do not feel and taste like a cricket ball is impossible, as they are picked in bulk and green to survive the supermarket supply chain. They may look OK, but the taste is what really counts, and here they miss out badly to specialist stores.
- Harris Farm has considerable potential if they can resist the temptation to become more like a ‘chain’. Woolies had a go at high quality specialist food retailing with Thomas Dux, and at first got the recipe right. Sadly, success breeds intervention by the back office boys who never actually see a customers, which resulted in ‘Dux’ being sent to the naughty corner to die.
- Automation in big distribution centres will continue to drive costs out of the system. Ocado, the British online grocer is licencing their technology around the world. Coles did a deal with them back in 2019 to build two automated fulfilment centres, which will feed into their home delivery strategy and no doubt generate a lot of thinking for the standard supermarket Distribution Centre logistics chain.
- Aldi will continue to grow, more slowly than to date, as they expand store numbers in an already saturated market. Costco with currently thirteen locations around Australia have the potential to double in the next few years. Their differentiator is an entirely different business model, which is very hard to copy for any established retailer.
- The demise of proprietary brands in Australian FMCG has probably reached its lowest point. Coles and Woolies have ransacked the profitability of their supply base, who have responded with little or no investment in genuine innovation, ultimately the only source of real growth. I suspect that some smaller brands may start to reappear as Coles and Woolies seek to differentiate themselves from each other, Aldi, and the alternative distribution channels slowly emerging.
- The big retailers will, or should, start to experiment with some of the technology proving successful in the US and China. The obvious place for such an experiment is in some of the CBD locations they both have. Shoppers looking for a quick shop for dinner as they run for the train home, might value the sort of service offered by Amazon Go and others.
- Managing inventory for suppliers will become even more difficult. Retailers are continuing to reduce their order quantities while increasing the order frequency and placing rigid delivery times on suppliers. This volatility is making supplier demand planning progressively more challenging, while getting paid in a reasonable time means they are funding the retailers. I suspect there will be technical solutions to demand planning evolving that involve AI, interacting in real time with store traffic, weather, and events to deliver a demand number by location. It may be that the DC starts to pack retail shelves, which are delivered on a roll in roll out basis to stores, removing the in-store labour and reducing back store footprint size. At Dairy Farmers 30 years ago, we experimented with this idea for fresh milk, and while it was promising, it did not catch on. Just 30 years too early?
- The physical movement through the supply chains is an increasing problem for supermarkets. Traffic density, and fewer drivers available as the old guard retires, unreplaced by a new driver cohort willing to accept the rigors of driving semis in heavy traffic for 12 hours a day. Combined with the challenge of demand planning, this will increase the number of product out of stock at the retail face, encouraging consumers to alternatives.
No business model remains unchallenged, and can remain unchanged in the face of evolving competitive circumstances. The supermarket business model is no different, although proving to be more resilient than I had thought it would be a decade ago. The core assumption of the business model however remains unchanged. They control a choke point in the supply chain, and take a margin that reflects their power on both sides of that choke point.
Mar 2, 2022 | Change, Leadership
For a change effort to succeed, it must solve a problem people care about.
The first challenge I have seen in many years of looking, is to find the few who care enough to get off their arses, and then make sure those few care about the same things for the same reasons.
Start small and focussed.
The status quo is a powerful antagonist, one that resists change with a power that is almost always underrated by those advocating for the change. There is a very real difference between the apparent agreement to change, and taking the actions that will lead to the changes seemingly agreed becoming a new status quo.
Being misled is a common occurrence. ‘I thought we had agreed‘ a common cry, followed up by a litany of excuses why the agreed changes were not able to be executed at this time.
The most common mistake the change-makers make, is to try and leap from the grievance to the solution in one step. It seems so obvious to them. Instead, small steps work much better. It is like changing a habit in your own life, going ‘cold turkey’ is much harder than making a series of small changes, none of which are too difficult, moving progressively towards the objective of a changed habit.
Once the change has been achieved, there must be some sort of foundation to prevent what I call ‘change recidivation’. That tendency to declare success, only to find later that there was slippage back to the old ways.
The metaphor I use is of a stretched elastic band. Once the pressure comes off, the tendency is for the band to revert to its former shape. You must ensure that when you think the change is successful, that it really is embedded, absolutely nailed down, not just waiting for the chance to revert when you are not looking.
The corollary of course is that in an environment where constant change is necessary just to keep up with what is happening around you, a stop/start approach will not be enough to stay competitive. The leadership challenge is to enable change to be the status quo, always happening on autopilot, rather than being that stop/start exercise undertaken as a separate project.
Feb 28, 2022 | Leadership, Management, Strategy
History is littered with examples that convincingly make the case that a battle on two fronts can never be won.
Our business literature is similarly littered with examples of business failure brought on by the competing demands of too many markets calling on a common set of resources. The metaphor of war is routinely used in business literature, I have used it myself many times. Phrases like ‘the high ground’, ‘resource mobilisation and concentration’, ‘overwhelming force” and so on.
How odd then to find myself saying that success absolutely relies on being effective on two fronts at the same time.
Those fronts are not different enemies, or geographic locations, distribution channels, customer groups, or any of the other regularly used differentiators, but they can be all of them.
The two fronts are ‘attack’ and ‘defence’.
The disciplines used to assemble and deploy scarce resources to take advantage of opportunities, look for new products, and outflank the opposition whilst defending your home ground are common to all situations.
Resources are limited, opportunities to use them are not.
How many successful football teams have you seen that cannot both attack and defend? The really good ones swing from one to the other, and back again seamlessly, without a loss of position or momentum. Each player knowing their role in any given situation, understanding how that role contributes to the overall outcome of the play in progress, and ultimately to the score at the end of the game.
The best I have seen at this in recent times is the Melbourne Storm rugby league team. Irrespective of personnel on the field, every player knows his role in both attack and defence, and swings seamlessly between them in concert with every other player on the field.
It is the same in commercial life.
The imperative to grow also means that the home base, the source of the cash today, is effectively defended even as it evolves to deliver cash tomorrow.
I am constantly reminded of Charles Darwin’s observation that ‘it is not the strongest of the species that survives, nor the most intelligent, it is the one most adaptable to change’
How good is your organisation in this tug of war operating on two fronts?
Feb 25, 2022 | Analytics, Operations
To improve performance, the key challenge is to identify the drivers of outcomes in real time, and enable the changes to be made that will improve the performance.
The ‘Box score’ is a term that has been hijacked from the recording of individual sporting performances in team sports by a few accountants seeking to capture real time operational data. The term originated with Baseball, but all team sports have a system that in some way records individual performances which when taken together are the source of team performance.
In a commercial operational context, the collection of metrics plays the same role, capturing the real performance of a part of a process, adding through to the totals for the whole ‘team’. It is a more accurate and responsive way of tracking the costs incurred in an operational situation, specifically a manufacturing process, than the favoured standard costing system.
Typically, standard cost systems while better than nothing, fail to reflect the actual costs incurred by a process. They are ‘lazy’, displaying the averages of past calculations, and as we know, averages hide all sorts of misdemeanours, errors, and potentially valuable outliers.
Sometimes these systems also have a component added to the cost of each unit of production that is noted as: ‘overhead absorption’. This just makes the inaccuracy and inflexibility of the standard costing system even more inaccurate and misleading, resulting in poor data upon which to make decisions.
Accounting has only two functions: the first is reporting to outside stakeholders. That has become a formulaic process with a template and rules about how things will be treated, this is to ensure that you are always able to compare apples with apples across industries.
The second function is to provide the information necessary to improve the quality of management decisions. The two are not connected except at the base level, the originating data.
This is where the ‘box score’ approach adds huge value: it captures the actual cost of a process.
A well thought out standard cost of goods sold (COGS) calculation typically includes calculations for the cost of packaging, materials used in manufacturing, and the labour cost consumed by the process. The calculation assumes standards for all three, and then throws out variances from the standard to be investigated. Standards would typically be updated regularly to accommodate variances that appear intractable. Changes such as labour rates, machine throughput, and price changes in materials, should be included in updated standards, but often they are not, and when they are, it is after the fact, and as averages.
A ‘box score’ by contrast captures the actual cost in real time, or close to it, so that more informed management decisions can be made.
30 years ago, I did an experiment in a factory I was running, the objective of which was to identify the exact cost of the products running through a line. To collect the data, a host of people needed to stand around with clipboards, stopwatches, and calculators. At the time it was called Activity Based Costing, ABC. The result was good, but the improvements resulting from the information gathered did not generate a return on the investment necessary.
These days with the digital tools available to collect data, there is little excuse not to invest the small amount required to measure the real throughput and resources allocated to get the better information for informed decisions. The options to collect real time data are numerous and cheap, and in modern machinery, just part of the control mechanisms. These devices can collect data and dump it into anything from Excel to advanced SCADA systems, which enable the data to be analysed, investigated and the outcomes recorded and leveraged for improvement.
Managing operations using the actual costs captured and reflected in a ‘Box Score’ manner enables more accurate and immediate decisions to be taken at the point of causation. It is no different to a cricket captain taking a bowler off because the batsman is belting him out of the park. When you can see what is happening in real time, you can do something about it.
Header: courtesy Wikipedia. The scorecard in the header is the scorecard of day 1 of the 1994 ashes test in Brisbane. It progressively captures the days play as it happened: a ‘Box score’
Feb 23, 2022 | Analytics, Governance
The old adage that you can find data to support any proposition, almost no matter how wild, has never been as prevalent as it is today.
We have the sight of politicians on the one hand telling us the science is wrong as it reflects the looming catastrophe of climate change, while at the same time lauding science in the way the world has responded to the covid pandemic with new vaccines in record time.
The contradiction is extreme, however, there is always data to ‘prove’ whatever point is required.
Following are some of the common ways data is manipulated to mislead, misinform, and bamboozle the unwary.
- Confusing correlation with causation. This is very common, and I have written about it on several occasions. Just because the graphs of ice cream sales and shark attacks mirror each other, does not mean one caused the other.
- The Cobra effect. This refers to the unintentional negative consequences that arise from an incentive designed to deliver a benefit. The name comes from an effort by the British Raj to reduce the number of cobras, and associated deaths that occurred in Delhi, by offering a bounty on each dead cobra. Entrepreneurial Indians started to breed them for the bounty. The identical situation applied when the French wanted to reduce the rat population of the French Indochina. They stuck a bounty on rats’ tails, which resulted in enterprising Vietnamese catching the rats for their tails and then releasing them to breed further.
- Cherry Picking. Finding results, no matter how obscure, that support your position, and excluding any data that might point out the error. This is the favourite political ploy, having a great run currently.
- Sampling bias. Relying on data that is drawn from an unrepresentative sample from which to draw conclusions. It is often challenging to select a sample that delivers reliable conclusions, and often much too easy to select one which delivers a predetermined outcome. Again, a favoured political strategy.
- Misunderstanding probability. Often called the gamblers fallacy, this leads you to conclude that after a run of five heads in a two-up game, the next throw must be tails. Each throw is a discreet 50/50 probability, no matter what the previous throws have been. Poker machine venues rely on the players increasing belief that the ‘next one’ will be the ‘jackpot’ after a run a ‘bad ones’ for their profits.
- The Hawthorne effect. The name comes from a series of experiments in the 1920’s in the Hawthorne Works factory in the US producing electrical relays. Lighting levels were altered minimally to observe the impact on worker productivity, and concluded that they improved when lighting was increased, but later dropped. The effect of the lighting was later disproved, when psychologists recognised that people’s behaviour changes when they are, or believe they are, being observed. This can be a nasty trap for the inexperienced researcher conducting qualitative research.
- Gerrymandering. Normally this refers to the alteration of geographic boundaries, usually in the context of electoral boundaries. It can equally be used to describe the boundaries set around which source data can be included in any sample. ‘Fitting’ the data to deliver the desired outcome. The term originated from the manipulation of electoral boundaries in Boston in 1812 when the then Governor Elbridge Gerry signed a bill that created a highly partisan district in Boston that resembled the mythical salamander. The national party held government in QLD for 32 years until 1989 as a result of a massive gerrymander in their favour, perhaps better remembered as a ‘Bjelkemander’
- Publication bias. Interesting or somehow sensational research is more likely to be published and shared than more mundane studies. In this day of social media, this becomes compounded by the ‘echo chamber’ of social platforms.
- Simpson’s paradox. This describes the situation where a trend evident in several data sets is eliminated or reversed when the data is combined. An example might be the current debate about university admissions favouring males over females. If you take subsets of the data for different faculties, this may be true, but combine the faculties, and the numbers will be virtually even, perhaps even favouring females. This was demonstrated in a study of admissions to UC Berkely in 1973 and is a regular feature of misleading political commentary.
- McNamara Fallacy. This comes about when reliance is placed on data only in extraordinarily complex situations, ignoring the ‘big picture’, and assuming rationality will prevail. The name comes from reference to Robert McNamara, US Secretary of Defence under Presidents Kennedy and Johnson who used data to unintentionally lead the US into the disaster that was Vietnam, later acknowledging his mistake.
Using data to is an essential ingredient in making your case, as they convey rationality and truth. When listening to a case being made to you, be very careful as numbers have the uncanny ability to lie. To protect yourself, ask at least some of these eleven questions.
Header illustration credit: Smithsonian. The drawing is of the electoral district created by Massachusetts Governor Elbridge Gerry in 1812 to ‘steal’ an election.
