Dec 20, 2023 | Analytics, Marketing
This is an indulgence, but who cares, it is that time of the year.
I do not spend too much time worrying about numbers, this blog is my personal ‘journal’ of the stuff I am thinking about. If others get some benefit from that great, if not, nobody cares.
However, contrary to the above, there are some lessons for me in the numbers, and learning from the past, and improving is what it is all about.
The obvious skew in numbers that arises from posts early in the year having more time to gather readers than those posted later, has been ignored. Most posts see the vast majority of views in the first week or so, so timing should not be a huge influencer. However, there are a few exceptions to that rule.
Number 8 on the list is a post on the business model of supermarkets written in 2014. This has been in the top 10, usually the top 3 every year since. Number 7 is a thought starter on the budgeting process, that annually added job everyone except accountants hate, which was posted in January 2020. Every other post on the list is from 2023.
There are a few common characteristics of the top posts.
- Most promise a silver bullet of some sort in the headline. This may attract readers, but sadly, does not make the meat of the post any better. I can only hope that having been attracted, some might take some value out of the post.
- They are generally shorter than the average. This may reflect the focus and promise of the headline, or alternatively, I just did a better editing job.
- This characteristic is both a surprise and a worry to me. Apart from the two posts from previous years, and number 10 on the list, all have as a header a ‘Dilbert’ cartoon. Perhaps the presence of Dilbert is a strong motivator to readership? There was no intent here, and that correlation (or is it causation?) came as a complete surprise to me.
- Almost half the readers come from the subscription list, which is not big, about 35% from LinkedIn, and the balance from search engines, mostly from Google, but a surprising number from random engines. Readers come 70% from Australia, next biggest is the US, followed by (presumably) taxi drivers in Mumbai looking to emigrate, and a few from places I have to consult an Atlas (remember those) to find.
- Linkedin attracts a varying number on the platform, from a few to in some cases many thousands. The ‘views’ which misleadingly just counts the number of feeds a post has been shown in, bearing no relationship to being read, varies between a few, and many thousands. I only take account of the number of comments and reposts as an indicator of value, with a lesser value on ‘likes’. Linkedin discourages links leading off the platform by sticking offenders in ‘Linkedin gaol’, meaning they squeeze the algorithm so fewer people on the platform have the chance to see it. Suffice to say, I expect my gaol sentence to be ‘life’.
- As I run my eye down the full list, there is an increasing number of posts from previous years, some delivering very regular cadence of readership, years after publication. This is gratifying, and indicates that unlike a newspaper, a useful blog post is not just tomorrow’s fish wrapper. One that does continue to amuse is ‘Public Sector Flatulence’ published in 2013. It can go months without any readers, then suddenly, and suspiciously coincidental to some politicians brain-fart, it generates a bunch of views, and the odd comment.
For those interested, the list from top to number 10 is:
The simple choice marketers must make.
Plans never reflect what happens, so why bother?
The single key to great success.
Enduring culture change demands action.
The easiest and most effective way to build carbon emission compliance.
How to maximise the return from your investment in sales personnel.
5 Key factors to consider when planning your budgeting process.
3 essential pieces of the supermarket business model.
Equity or loans: The entrepreneurs funding dilemma.
The two key building blocks of strategy.
Thanks to all my readers, have a safe and merry Christmas, or whatever it is you celebrate (a valued friend is a Hindu, and Hindu’s traditionally marry on the last Sunday of the month. Guess what he and his wife of 30 years are celebrating)
Note: Given the number of links in the post, Linkedin will send me to their gaol for life, ensuring as few as possible casual lookers get to see the posts. So, please encourage those who might be interested to subscribe on the StrategyAudit site. That way they can continue to have the chance of seeing the outcomes of my addled musings.
Header courtesy of Dilbert, and Scott Adams, again. It just seemed right.
Aug 21, 2023 | Analytics, Management
Volume, flow, and capacity utilisation are drivers of each other, a symbiotic relationship articulated by Wrights Law.
A product with significant volume that is easy to schedule through a factory, and because of those volumes, has ‘well-oiled’ and efficient operational processes, generally delivers profit.
Years ago, I did a product profitability exercise on a range of products that were marketed by the company for which I worked at the time, Dairy Farmers Ltd. The parameters I used were based on the gross contribution to fixed overhead after promotional costs. These I calculated from the standard costing model being used at the time. Also weighted into the calculations were the complexity of the operational scheduling imposed by the products, and the ratio of gross contribution to the calculated capacity of the individual production lines, including downtime measures like machine availability.
The most profitable product in the range in both dollars and percentage was 300gm sour cream in cartons. It was a product that had significant and easily forecast volumes, so raw material procurement was simplified, predictable, the operational processes were ‘well-oiled’, and we had some pricing power in the supermarkets. There was very little wasted capacity or product failure in the manufacturing processes. Wrights law at work, and after a bit of thought, it made absolute sense that it would be the most profitable.
The second most profitable product in the range in percentage terms was a surprise to everyone, including me. A relatively small volume product, ‘Buttermilk’ in 600ml cartons. At the time there was no competitive product, so we had considerable pricing power, the volumes were highly predictable albeit modest, the ingredients simple and always available, and we could run the product immediately after sour cream with just a change in carton size which we could do ‘on the run’, the first few cartons acting as the ‘clean-up’ after the sour cream. There was effectively no downtime, no ‘start-up waste’ product, no added labour, few inventory costs, and no promotional costs. The capacity utilisation of buttermilk was virtually 100% of the capacity allocated by the arithmetic that combined volumes required and theoretical throughput rate and delivered margin.
Sadly for Dairy Farmers profitability, the supermarkets realised there was a profit pool they were not accessing. They introduced house brand products manufactured by a competitor who had idle capacity and took a marginal cost approach to the price at which they were prepared to sell the product to use that capacity. The volumes of both sour cream and buttermilk products fell quite quickly, while the operational costs per unit increased markedly.
Wright’s Law works in reverse as well.
The header is of Theodore Paul Wright 1895 – 1970
Aug 7, 2023 | Analytics, Leadership
We all need to become ‘knowledge workers’ say the pundits, who generally fail to define just what that term means, and how we achieve it.
Most would simply apply some added practical training and education, and bingo, knowledge, but I suspect it is more complicated than that.
Knowledge is way more than just education and training. It is also the wisdom of experience, domain familiarity, networks of people who can be called upon, and a capacity to make connections in non-obvious ways. It is intangible, as individuals, we have no physical stocks of knowledge, although we do now have relatively unlimited access to its sources.
The value of knowledge is also very hard to define, if not impossible, and it is not of much value when it stays in one place. Its value is highly contextual. It is of little obvious use having an expert in genetics when you are struggling with a problem of commercial governance. However, when you dig deep enough, you often find there are lessons to be learnt from other domains that can be applied, and in the process of digging, you learn.
The real value of knowledge is when it flows from one to another, and on to many, then, magically, it grows, evolves, and is put to uses not previously considered, creating even more value.
Therefore, the definition of a knowledge worker should be more like ‘Builds, shares, and leverages data for use beyond their domain’.
Improvements and alternatives encouraged.
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.
May 17, 2023 | Analytics, Management
The ‘Long tail’ is a graphic recognition of the Pareto principle, the 80/20 rule. It holds true in every situation I have ever seen. Rarely exactly 80/20, but always somewhere in the region.
We tend to accept it as a reflection of revenue and profit: ‘20% of our customers generate 80% of our revenue’.
Often, we manage our businesses, particularly the sales effort, as if this is the only place the principle works.
It applies equally to transaction costs, long term potential, management attention, geography, product class, customer type, and many other useful to know indicators.
Take for example, those customers that in 5 years’ time will be amongst your most profitable. Chances are, they are currently hiding somewhere in your long tail, denied the focus and assistance they might value that will assist them to grow in importance, simply because they are not seen. I call them ‘Strategically Important Customers.’ Unimportant now by most measures, but critically important in the long term.
Ignore these customers at your peril.
So, how do you find them?
- They meet the parameters of your ‘ideal customer.’
- They have a problem to which you have or are developing the ideal solution.
- Your share of their ‘wallet‘ is low when they meet other ‘ideal customer’ parameters.
Conversely, set your sales team to dig them out of your competitor’s long tail, deliver value to them, and convert.
An equally important task is to identify those customers who cost more to service than their current or potential profitability. The best thing you can do is send them to your competitor, so they can be saddled with the usually hidden transaction costs and low margins.
The profit and Loss statement is, or can be, a remarkably efficient way of capturing the information required to focus resources in the most optimised manner, dictated by your strategy. A P&L by customer, product, geography, market, and any other driver can be generated using readily available and relatively simple tools. The challenge is in overcoming the institutional definitions of how the data for the statements is collected, collated, and presented.
For example, what is an overhead, and how is it allocated?
In a factory, is the cost of supervisory staff allocated to individual product lines based on the actual costs, some rough ‘standard’ cost, or not allocated at all? Are those costs seen as overhead? Is the total overhead spread across total production by some magical formula devised by the accountants, or treated as a cost centre and managed proactively? What about those directly on the production line? Are their costs allocated in proportion to production volumes, customer offtake, or some mythical ‘absorption’ rate?
Take the time to ‘slice and dice’ your Profit and Loss statement. After having tackled the greater challenge of having the costs as they are actually incurred reflected in the customer P&L statement, you will be in a great position to take decisions that will have a significant impact on your overall profitability.
Feb 1, 2023 | Analytics, Governance, Strategy
Mark Zuckerburg has a lot to answer for, disrupting as he has the lives of my children. However, he is also very smart and rich, so being annoying must have something going for it.
When pitching the $5 billion Facebook float in 2012, Zuckerburg wrote to prospective shareholders via the prospectus, a letter that outlined his vision of what Facebook had become, and would continue to be.
This is to my mind the crucial paragraph, buried in the body of the letter.
“The Hacker Way is an approach to building that involves continuous improvement and iteration. Hackers believe that something can always be better, and that nothing is ever complete. They just have to go fix it — often in the face of people who say it’s impossible or are content with the status quo”
It now seems he has taken that perspective of his obsession to the world of virtual reality. He has invested billions of shareholder funds in his personal vision, triggering a loss of billions from the market value of Facebook, now Meta. He does not seem to care, but many other shareholders do. They must be getting very annoyed about now, the value of their shares dropping 70% from its peak 15 months ago.
At some point, businesses must develop stable, repeatable processes that just gets the mundane stuff done.
Facebook did that with remarkable efficiency for a long time, creating a river of cash. However, ‘hacking’ has taken hold.
Hacking to improve mundane processes should be part of the culture, so long as the experimentation is part of a managed process. The alternative to that discipline is chaos.
Mixing the cultures that accommodate the disciplined repeatable processes that get the bills paid, and the sometimes chaotic, creative environment of “hacking” is a function of the leadership of the enterprise.
Management needs to be “Loose” to accommodate the creativity and experimentation necessary for process improvement, while being “tight” to enable the learning that comes from experimentation to be incorporated into standard procedures when they prove to be an improvement.
Loose/tight management, is the environment in which “Hacking” Kaizen, or whatever you choose to call it thrives.
‘The Zuk’ has imposed his single minded obsession with hacking on the culturally poisonous monolith he created, because he can. If his VR vision becomes a reality, Meta share price will not only recover, but break all records. I do not expect that at any time soon, particularly if as rumoured, Apple comes out with their version. Meta now faces a governance challenge that could be a real game-changer.
Addendum February 4, 2023.
This article from the Statista website details the progression of losses Meta has booked on Zuks metaverse bet. $US13.7 Billion in 2022, on an increasing trend. While the share price has dropped dramatically, if you look at the PE ratios before and after the drop, it seems to me that the price is settling back to where an old fashioned investor, one who expected a return from dividends rather than capital growth on the basis of a never ending share price increase, might expect it to be. The same comment can be applied to many other digital pletform stock price drops over the last year or so. Fundamentals kicking in??
Addendum 2 February 5, 2023.
They are coming thick and fast!. I read this ‘Wired’ article by the brilliant Cory Doctorow this morning. It explicitly defines the life cycle of social platforms, something we all ‘sort of’ knew but dismissed in favour of the value for early adopters, progressively locking in users, at the same time they squeezed the algorithms to generate ad revenue. Doctorow calls it ‘Enshittification’, a lovely word. Towards the end of the article is a quote from a very young Zuckerberg ”I don’t know why tney trust me, Dumb fucks’. Here is the news Zuk, we don’t!!
