Aug 5, 2024 | Management, Operations
A phrase I am hearing a lot in conversation with my networks is: ‘this business model is capital light‘. It seems to most aspiring entrepreneurs this is preferable to ‘Capital heavy’, for the obvious reason that the upfront cash at start-up is less. However, while useful, it also is only one way of looking at a business model and its associated strengths and weaknesses.
Capital-intensive businesses have high fixed costs compared to variable costs, making them vulnerable to a slowdown, as they are very volume sensitive. Their breakeven point is higher than businesses less capital intensive. However, once they reach that break-even point, most of the rest is profit.
The obvious contrast is between an oil refinery or steel-making plant, to an accounting or law practice. The former needs considerable capital deployed before there is any consideration of the labour, management, and raw material required for conversion. The latter requires just offices and capable personnel.
In effect, Capital Intensity is a measure of how many dollars of capital are required to generate a dollar of sales?
Capital intensity requires that the assets be procured in order to be operational. This can be a mix of cash retained from earnings, or available from shareholders, loans, or ‘outsourcing’ manufacturing to a contractor who has, or will add, capacity for ‘rent’. An additional source is from suppliers so long as your debtor days are less than your creditor days, in which case, your creditors are in effect adding to the funding of your business.
Often you will see the term ROCE or Return On Capital Employed in financial reports. This is simply the ratio of profit to capital. If you generate $1 in profit for every dollar of capital, you will have a capital efficiency ratio of 1:1.
It is a useful macro measure of the efficiency of the capital used in the business, just as it is a valid calculation of the efficiency of a machine: Revenue/Capital cost of the machine.
Successful businesses use capital to generate revenue and profits, the more successful you are, the better you have used the capital deployed.
How much capital is required to generate your profits?
How to Calculate Capital Intensity
The capital intensity formula is:
Capital Intensity = Fixed Assets / Total Revenue
Example
Imagine a company has $100,000 in fixed assets and $1,000,000 in total revenue. The company’s capital intensity would be: $100,000 / $1,000,000 = 0.1
This means that the company needs 10 cents of capital to generate every dollar of revenue.
Increasingly, the capital required early in the life of a business is reducing as digital technology evolves, removing the capital requirement as a barrier to entry to many industry segments. This is leading to a transfer from capital intensive to ‘technology intensive’, which is in turn becoming increasingly complex and expensive as technology evolves at an accelerating rate, and the business cycles become shorter.
As the old saying goes, there is never a free lunch!
May 6, 2024 | Operations, Strategy
As we seek to move towards 3% of GDP as a measure of the R&D in the economy, we are assuming that simply increasing the percentage will increase the output, in some sort of linear manner.
Ranking as we do at 93 on the Harvard list, squeezed between Uganda on 92, and Pakistan at 94, we need to do something different.
We have not asked the question: what changes need to be made to the multi-jurisdictional, fragmented and short-term focused system we have currently.
In my view we should.
Before we throw more effort and money into the existing system, we should be questioning if the system is able to deliver the outcomes being sought in an optimised manner.
Assuming we elect to keep the existing system, (a given I suspect) we should start by asking challenging strategic questions about the technology domains we need to focus on, that contribute to the shape of the economy we envisage in a decade or two.
That is easy to say, sadly, it is extraordinarily hard to do. It is even harder for the answers that may emerge to get any traction, by way of public awareness and funding. Without exception, the questions we must ask will run against the readily available answers that reflect just the extrapolation of the status quo, perhaps with a few wrinkles.
Inevitably, multiplying the complexity of the challenges faced will present problems with no apparent answers, or they would have been answered before. That is why the cycle from science to commercialised product is so long, in most cases, 30 years or more.
Change needs a catalyst, which usually comes from unexpected angles.
Take the development of mRNA vaccines during Covid.
To most this was a rushed and half-baked process, as we all know that the pharma innovation cycle is at least a decade, from identification of a molecule of value, through product development and increasingly demanding levels of clinical trial. Here, it happened in 18 months.
Thing is mRNA vaccine development did not happen in 18 months.
The logic of what became mRNA was first articulated in 1956, and had been investigated continuously for the following 65 years. Suddenly the catalyst of Covid emerged, and the next decade or longer of development was compressed into the 18 months. This is simply because most of the work had been done, under the radar, and on a small scale, scientists knew it was extremely promising, they just lacked the catalyst and therefore the funds to prove it.
The question here was: can the expensive and technically very difficult production of mRNA be proved and scaled in 18 months? Clearly the answer was ‘yes’ and now we have mRNA as part of the pharma arsenal.
The PM has committed a billion dollars to developing a manufacturing plant in the Hunter that produces solar panels. On the surface, it is dumb, and has been condemned by many, including yours truly, and chair of the productivity Commission Danielle Wood.
However, what if we asked the mRNA question: Can the production of electricity from solar be re-engineered to use significantly advanced technology over what is currently available? If so, that may enable the plant to be a ‘next technology generation’ solar plant that sets a whole new standard.
The whole basis of the current argument that the investment can never be commercially viable because the Chinese have a stranglehold on the existing technology and cost structure is out the window. A new plant using new technology, delivering lower cost structures and capital productivity would make the current dominating technology redundant.
The intensity of intellectual effort required to ask and investigate these alternative questions is extreme.
The odds of one of them identifying an opportunity that is, with the benefit of hindsight, a ‘unicorn’ is tiny, so the political risk is significant. However, if we allow ourselves to be seduced by the fantasy of doing more of what has resulted in our current situation and expecting a better outcome, we will deserve the shellacking the investment will receive.
Two years ago I had a shot, and nominated three headline domains where we should be investing, and my views have not changed. Sitting under these three headlines are a host of opportunities for a focused R&D effort that should be considered by experts in the various fields, choices made, and long-term investment locked in.
Header is from the extensive StrategyAudit slide bank.
Sep 18, 2023 | Customers, Marketing, Operations
When you want to improve something, find a metric that drives the performance you want.
Pretty obvious, as most of us subscribe to the cliché that you get what you measure, while remembering Einstein’s observation that not all that matters can be measured.
Ultimately, what the customer thinks is crucial to success. Therefore, measuring the performance in meeting the customers’ expectations is always a good place to start measuring your performance.
Amongst my favoured measures is DIFOT.
Delivered In Full On Time.
That means not only the full order delivered on the day it is originally promised, with no errors of any sort, from quality of the product to the delivery time and accuracy of the ‘paperwork’.
DIFOT is a challenging measure, as it requires the collaboration and coordination of all the functional and operational tasks required to deliver in full on time.
As you fail to reach 100% DIFOT, as most do most of the time, at least at first, the failures are used as a source of improvement initiatives.
There is very little more important to the receipt of that next order than your performance on the previous ones. Never forget that, and measure DIFOT.
Hand in hand with DIFOT, you should also measure inventory cover.
The sibling.
You can improve DIFOT by simply increasing inventory when selling a physical product. Demand is inherently difficult to forecast, as it is the future, and entirely out of your hands. The challenge is to prevent your warehouses multiplying, and clogging the operational systems. The ideal situation is ‘make to order’, the ultimate shortening of the order to delivery cycle time.
The most common and very useful measure of inventory is ‘Days cover’. How many days of normal, average, forecast sales, whichever you prefer in your circumstances, do you have on hand to meet demand? This measure is extremely useful on a ‘by product’ basis, but when applied as an average across multiple lines with differing demand levels, can become a dangerous ‘comforter’.
Counter intuitively, the products that cause the most problems are the smaller volume ones, and new products. In both cases, demand is harder to forecast. The swings from out of stock to excess inventory can be erratic, particularly when a production line is geared to the larger volume runs of an established product as a driver of operational efficiency.
To achieve a 100% DIFOT while controlling physical inventory over an extended period is the most difficult operational challenge I have come across. As a result, it is amongst the most valuable to keep ‘front and centre’. The twin measures of DIFOT and ‘Days Cover’ are a vital element in addressing that ultimate challenge of customer service.
Aug 9, 2023 | Change, Operations, Strategy
Almost every SME I visit or work with needs to one degree or another to be moving down the path towards ‘digitisation’.
For some, this means considering how the sudden appearance of LLM trained AI will impact on their competitive position, for others, it is still how to write a simple excel macro, and move bookkeeping from Mavis in the corner to a cloud package.
Just what does ‘digitisation’ mean?
For most of my clients it means automating some or all of the existing processes driven by bits of unconnected software and spreadsheets, liberally connected by people handing things over.
It is usually a real mess, and the evidence of incomplete solutions, misinformation, and shattered hopes lie everywhere.
The world is digitising at an accelerating rate, so keeping up is not only a competitive imperative, it is a strategic challenge. To survive you must evolve at least the same rate, just to keep up.
On of my former clients is a printing business, an SME with deep capabilities in all things ‘printing’ that enabled the company to be very successful, in the past. Their capabilities are terrific, highly competitive, if we were still in 1999.
If I use them as a metaphor for most I work with, there is a consistent pattern.
They do not see digitisation as an investment in the future, rather it is seen as an expense. This means that the challenges are not considered to be strategic. There is no consideration of the application of digital to their product offerings, beyond the digital printing machines, services beyond those that made them successful 20 years ago, and their business models, beyond what is demanded by the two biggest customers, who between them deliver well over 35% of revenue.
They have not considered digitisation of operational processes, beyond a 20 year old ERP system, which has not been updated in any meaningful way for a decade, and they still only use a portion of the capability. The reason for this is simply a lack of internal capability and awareness, and the lack of cash to invest for the long term.
They have not modified their organisational and operational culture. No digitisation effort can succeed without the support of an operating culture that encourages ongoing change. Organisational processes can be modified by decree, but they will not stick. It takes everyone in the boat to be pulling in the same direction, in unison, to make the forward progress proposed by the digitisation nirvana. This takes leadership, and a willingness to be both vulnerable internally, and a strong ability to absorb the stuff from outside. You need to ‘get out of the building’ not to smell the roses, but to see the lie of the land, and understand where the opportunities and challenges are hiding.
The recognition of the critical necessity of change is where you get given one point out of a possible 10. The other 9 are reserved for taking action. A daunting prospect for most.
Following are the 5 steps necessary to become ‘match fit’.
- Map the existing operational processes so you know what you are changing. The starting point!
- Map and change the mindset of the people, so everyone understands the extent of the challenge to the business, and to them personally. This will prove very tough for some, so expect push-back.
- Take small and incremental steps along a path that all understand leads to a digital future, which means that a lot of collaborative planning has been done. Look for some low hanging fruit where early wins are likely.
- Ensure that there are the necessary opportunities for all stakeholders, but particularly employees to grow and change with you. Those that choose not to, also choose to work elsewhere. There are no free rides.
- Ensure the resources of time and money are allocated uncompromisingly to the long-term outcomes. It is just too easy to put aside something that is important but not urgent for something that may seem to be urgent, but is not important to the transformational effort.
Most need outside help to get this done. Usually that help in the early stages is not found amongst software vendors who have a dog in the fight. It is amongst those who have ‘been there, done that’. It will also be a resource hungry beast, but assuming you feed it, and you have the right mix of project management and technical capabilities, the investment will generate returns quickly, just not tomorrow.
Header cartoon credit: Tom Gauld
Jul 12, 2023 | Analytics, Marketing, Operations
Anyone who reads my stuff on any sort of regular basis will know I have been deeply engaged with the potential impact of AI on all of us, since I stumbled across ChatGPT in early December last year. Of particular interest is the apparent potential for efficiency gains, particularly amongst the SME manufacturers I serve.
On one hand, I have been excited by the potential of AI to generate efficiency and expand the operational scale of SME’s. On the other, scared shitless at the potential for bad actors to sneak into our collective pockets and steal everything.
I need to write to think.
It forces me to sort out the stuff swimming around between my ears, as when I can articulate it sufficiently to write about it in some coherent manner, it leads to some level of understanding.
So, here is my list of the good stuff, followed by the bad, as it relates to the core of my business: strategy and marketing, starting with SME’s and the written word.
The good things AI can do for you.
- Summarising large blocks of copy, even when it seems very messy.
- Brainstorming; ideas, subject lines, complementary ideas, headlines.
- Editing and grammar. (I have been using the editing and ‘speak’ functionality of word for years, it is essential to me, and is AI that we now just treat as part of the furniture)
- Assembling descriptions and fact sheets
- Looking for logical holes in an argument
- Repurposing copy from one platform to another
- Research
- Outline and first draft.
- Translation and transcription
The stuff AI is no good at doing.
- Humour
- Reflecting current news and events
- Factual reliability. (Sometimes, it just makes stuff up)
- Finding a good metaphor
- Being creative. The great irony with creativity is that AI opens a whole new set of what is possible with visual tools, which can then combine with verbal cloning tools to completely alter apparent reality.
- Looking ahead
- Breaking complexity down to ‘first principles’
- Pouring another glass when faced by a blank page and a deadline.
Then there is all the other stuff AI will do, and evolve to do in the very near future, that is not writing. Graphic design, integrating currently separate digital systems (API’s on powerful steroids) identifying trends and holes in huge masses of data. The impact on medical technology is already profound. When the human genome was first successfully mapped in 2000, the cost of that first success was in the tens of billions of dollars. Now you can send away a sample and have it returned with your genome map for a few dollars overnight.
The key it seems, is to be very good at explaining to the tool what it is you want, in the detail a 5-year-old will understand. As the header cartoon illustrates, being human while driving this stuff will rapidly become the differentiator.
Header credit: GapingVoid.com.
Jun 30, 2023 | Change, Lean, Operations
Several years ago I became aware of ‘Wrights law‘. In the 1930’s, Theordore Wright an aero engineer proposed that: ‘For every cumulative doubling of units produced, costs will fall by a constant percentage’. This insight came from observing the performance of his own factories building aircraft during the thirties and over the course of the war.
While I do not have the numbers, intuitively after 50 years of observation, it holds very true.
That truth seems to hold over any manufacturing I have seen and read about, unlike its much better known sibling Moore’s Law. Gordon Moore observed the increase in the number of transistors that can be stuffed onto a silicon chip in a given period of time, and predicted that a doubling of numbers would hold consistently over the long term.
Therein lies the significant difference that manufacturers have come to rely on.
Moore’s law refers to technology improvements over time.
Wright’s law refers to the manufacturing cost reductions that come with scale.
I would suggest that the cumulative impact of the combination has had a potent effect on manufacturing costs of everything from the manufacture of simple widgets to solar panels, to the cost of human genome mapping. Wrights Law applies as scale builds, and technology provides a catalyst to a tipping point that radically alters the growth curve, after which the graph finds a new normal in the relationship between volume and cost.
Australia for lack of leadership, foresight and capital has shied away from the investment required to light that catalytic fire many times in the past.
A primary example is solar panels. We have known for a hundred years that solar energy could be harnessed. As a kid I used to burn leaves, paper, ants, and occasionally myself, with a magnifying glass. However, it took researchers at the UNSW to invent PERC (Passivated Emitter and Real Cell) technology in 1983 to kick off Australia being the international leader in Solar cell technology. Funding and the foresight to commercialise could not be assembled here, so the technology was used to develop the manufacturing industry in China, where Wright’s law has facilitated the growth of a dominating share of the world market for wafers, cells, and completed solar modules.
Forecasting manufacturing costs is at the core of every successful manufacturer. While in the early stages of commercialisation there will be a host of variables you need to be able to model, understanding the relationship between your cost base and scale will remove a significant weight from your shoulders when planning capital requirements.
Australia again finds itself on the cusp of being an international leader in Quantum computing, biotechnology, Hydrogen sourced energy, and rare earth extraction and value addition. Let’s not allow ourselves to be distracted this time, we may not get another chance.
Successful economies all have one thing in common: they manufacture stuff others want to buy. Australia’s history is littered with great ideas, and technical innovations that are commercialised elsewhere for lack of foresight, leadership and capital. We would be desperately stupid to let it happen again!
