Jun 28, 2024 | Leadership
Performance is always enhanced when there is skin in the game.
I only work with SME’s, for the very simple reason that those in charge have skin in the game. The process of creating the environment where significant improvement to financial operational and strategic performance can be achieved requires change, and change is hard. When you own the business, and you decide that change is necessary to achieve the goals, you can drive those changes, and most people will follow. In a large business, most of the senior management still get paid, even when the train goes off the rails. They may lose a bonus here and there, but usually not, as they set the rules themselves.
It is a situation I dislike.
In the case of marketing, the lack of accountability for outcomes is more pronounced than in other functions. There is a mystique, a black box, and marketers have convinced themselves, and others that success is about long-term brand building, therefore they cannot be held accountable for results today.
Nonsense.
Marketing should be accountable for margins, absolute and percentages, today and tomorrow. Then they have some skin in the game and will act accordingly.
The upside of the greater accountability is that those in the corner office will take them more seriously than they have in the past.
The turnover of senior marketing personnel is faster than any other function. CEO’s are usually accountants, lawyers or engineers, and they quickly get sick of marketers talking in cliches, making vague promises, then delivering creative excuses when the outcomes fail to materialise.
Accept accountably for revenue and margins, and that uncertainty goes away.
As Steve Jobs put it, you need to ‘own the results‘.
Header credit: NZ Herald State of origin 2,.2024
Jun 24, 2024 | AI, Change
We’re all familiar with the standard XY graph. It shows us a point on 2 dimensions.
AI does a similar thing except that it has millions, and more recently, trillions, of dimensions.
Those dimensions are defined by the words we write into the instructions, built upon the base of raw data to which the machine has access.
The output from AI is a function of the data that the particular AI tool has been ‘trained’ on and accesses to respond to the instructions given.
Every letter, word, and sentence, generated is a probability estimate given what has been said previously in the database of what the next word, sentence, paragraph, chapter, and so on, will be.
Generative pre-training of digital models goes back into the 1990’s. Usually it was just called ‘machine learning’, which plays down the ability of machines to identify patterns in data and generate further data-points that fit those patterns. The revolution came with the word ‘transformer’, the T in ChatGPT. This came from the seminal AI paper written inside Google in 2017 called ‘Attention is all you need’.
The simple way to think about a transformer, is to imagine a digital version of a neural network similar to the one that drives our brains. We make connections, based on the combination of what we see, hear, and read, with our own domain knowledge history and attitudes acting as guardrails. A machine simulates that by its access to all the data it has been ‘trained on’, and applies the instructions we give it to then assemble from the data the best answer to the question asked.
The very first paper on AI was written by Alan Turing in 1950 was entitled ‘Computing machinery and intelligence’. He speculated on the possibility of creating machines that think, introducing the concept of what is now known as the ‘Turing Test.’
The original idea that drove the development of the transformer model by Google was a desire to build a superior search capability. When that was achieved, suddenly the other capabilities became evident.
Google then started thinking about the ramifications of releasing the tool, and hesitated, while Microsoft who had been also investing heavily through OpenAI, which started as a non-profit, beat them to a release date, forcing Google to follow quickly, stumbling along the way.
Since the release of ChatGPT3 on November 20, 2022, AI has become an avalanche of tools rapidly expanding to change the way we think about work, education, and the future.
Header cartoon credit: Tom Gauld in New Scientist.
Jun 19, 2024 | Change, Governance, Leadership
Many years ago, I worked for Dairy Farmers Ltd. It was a large dairy co-operative operating in the dying days of milk regulation in NSW. The business had two divisions, reporting at EBIT. The first and biggest by a very large margin was the regulated milk business.
All milk produced in NSW at that time was by regulation vested in a statutory authority, which then ‘sold’ the milk to processors to be processed and distributed as fresh milk. It was a highly regulated and price-controlled industry from the cow to the consumers fridge.
Milk in excess of the requirements for fresh milk was termed ‘manufacturing’ milk. The farmers were paid directly by processors at a market rate.
At the time, the price paid by the diary corporation for fresh milk was roughly 2.2 times the price the co-operative paid for manufacturing milk by the second division, the Dairy Foods division that produced all dairy products beyond fresh milk.
Manufacturing milk was unregulated in any way beyond food safety.
The commercial imperative for the dairy farmers was clear, albeit not viable long term.
After 8 years of struggle, the Dairy Foods division had recovered from being a commercial basket case, one step from the corporate mortician to a significant and profitable player in the national market. The culture that supported that huge improvement was highly competitive, productivity focused, and financially disciplined. By contrast the milk division was a cost-plus business operating as a regulated monopoly, and so had become fat and lazy.
A newly arrived Managing Director decided to merge the two divisions. His reason, supported by a report by a highly paid consultant, was that the commercial culture of the dairy foods division was needed to be patched onto the milk division, facing the reality of deregulation at some point.
As a newly appointed GM of the dairy foods division after those 8 long years of struggle, I resisted this change as strongly as I knew how. I argued that culture could not be ‘copied and pasted’ from one organisation to another, even those working under a common ownership and centralised head office structure that allocated capital. It seemed to me that the much larger still regulated business would reject the completely different culture of the smaller unit, which would in turn erode the competitive culture of the dairy foods division they were trying to spread.
That is what happened, resulting in Dairy farmers becoming another sovereign corporate casualty.
- Processes that ordered, allocated and paid for milk for the regulated fresh market dominated the cash flow of the merged divisions. The Dairy Foods division cash flow processes and management became lost in the quagmire of the regulated cash flow of the much larger former milk division. Focus and discipline went out the window.
- The board of the business, was made up of farmers with 2 exceptions, the chairman and MD. The rest of the board were dairy farmers who unanimously rejected the notion of deregulation. It was clearly in their short-term financial interests to retain the existing regulated system. There was simply no formal recognition that the regulated system was an economic basket case. Privately, several of the board members did recognise that fact, but the power of the status quo prevailed formally.
- Major customers, the supermarket retailers were able to bring significant pressure onto trading terms given the previously completely separated divisions were now one. This pressure seemed to me to be a catalyst that brought forward the date of deregulation. The retailers started to bring fresh milk across the border from deregulated Victoria, and discounting in NSW in defiance of the state regulations, citing Section 92 of the Australian constitution, which bans constraints on interstate trade.
- The financial discipline beyond managing cash flow exercised by the former Dairy Foods division was lost as the reporting was merged. It was further complicated as Dairy Farmers set about ‘merging’ (Co-Operative speak for taking over) other Co-ops in NSW, QLD and SA. These co-ops were all different, but all were afflicted by lack of commercial and competitive focus on customers and consumers.
All of these point to the fact that culture is organic, and like all organic systems requires time, investment, alignment across the broad stakeholder population, and nurturing.
What should have happened but did not.
- There was no attention paid to the differing cultures that existed. Little useful thought was given to the practical challenges of merging them. The merger came via announcement, and a revision of the organisation chart. The two were simply incompatible. While a sensible review would have highlighted that fact, it was ignored.
- There was no integration plan that ranged from the strategic to the tactical and operational. Again, it was driven by the revised organisation chart, with little effort made to successfully articulate the reasons for the merger to anyone, including senior management.
- Any attempt to articulate a ‘vision’ for the merged entity was missing in action. The justification was all about the imagined financial benefits that would flow, and the risk mitigation coming from the probable deregulation of the fresh milk business at some future point. Both were reasonable expectations, but there was no thought about how to turn reasonable expectations into cash. Somehow, by some unknown osmotic process, it was supposed to just happen.
- There were no objectives for the integration that reflected the strengths of both, the holes that needed filling, and the resources necessary to achieve the restructured strategic objectives.
- There were no financial or operational objectives beyond budgets generated by spreadsheet aiming at an EBIT that was by decree, rather than by any disciplined process. The budgets of the two separate divisions were just merged, with the mythical improvement index applied.
- There was always going to be considerable resistance from both sides of the merger. Almost universally, (most certainly by me) the merger was seen as a retrograde step, ignoring the very different challenges faced by the two entities.
The great irony I see from the perspective of 30 years, is that Bega Co-operative virtually broke on the back of cheese factory expansion that had run significantly over budget, was saved by a cash injection by Dairy Farmers. Bega has since evolved into a major producer of branded packaged goods to supermarkets. Dairy Farmers has disappeared as a commercial entity.
The lesson: Cultural change is complex, messy, and potentially terminal in the absence of skilled leadership, complete transparency, and what at the time would seem to be significant over-communication.
Header cartoon credit: www.Gapingvoid.com
Jun 17, 2024 | Change, Strategy
80% of Googles revenue comes from advertising. The obvious question is how the explosion of AI after the release of ChatGPT will impact on that revenue, and virtual monopoly of search that delivers it.
Rather than typing in a query and getting pages and pages of options for an answer, headed by 5 or six links that have paid to be at the top of the first page, AI will give you an ‘exact’ single answer.
At least you hope it will be the right answer.
If it is a simple black and white question, like what is the capital of Australia, you can be pretty sure it will be right, but if you want a detailed explanation of the science of climate change, it will be insufficient, and potentially misleading.
However, in a world of instant gratification, the first answer that appears right will be accepted, and as the late Daniel Kahneman demonstrated, we like the quick, ‘fast’ response in favour of the considered ‘slow’ answer.
Google has responded to this existential threat to its profitability with a tool called ‘AI Overviews’, currently in beta. It summarises search results and presents them as a single answer to the query.
‘Overviews’ It operates on the principle of “satisficing,” or providing quick, decent answers rather than a range of options.
Presumably, the ‘toll-booth’ will still be at the point of click through, while advertisers will be given the option to be on the ‘satisficing’ menu, for a price. Not a lot of change from current, frankly.
However, the tectonic forces driving the adoption of Ai will have impacts across the face of business, government and our personal lives, few of which are easily forecastable.
Darwin’s dictum that it is not the biggest or fastest that survive, but the most adaptable to change will really be tested in the coming decade.
Jun 14, 2024 | Communication, Governance
You cannot expect the right answer to come from the wrong question.
Too often we spend inordinate amounts of time trying to answer those questions before we understand the context or the ‘frame’ from which the answer will come.
Before anything else, to ensure the best answer possible, consider all the ‘frames’ through which the situation in front of you could be seen. Hypothesise what alternatives to the immediately obvious could be possible that might drive the situation you are examining.
Several months ago, early on a summer Saturday evening, I was walking my dog. As I passed the church at the end of my street, I saw a vague acquaintance crying.
There were a few other people milling around, so I just made an assumption without realising that is what I had done, and offered to help if I could. Her response was that she was Ok, crying for joy, her first grandchild had just been baptised.
Clearly the question that popped into my head led to an entirely to the wrong conclusion that her crying was from distress.
The frame through which I observed the woman crying led to making an automatic, but incorrect conclusion.
How often in our commercial lives do we ask questions which just assume the presence of some factor, when in fact that assumption is wrong?
The lesson here is make sure you have the context right before you start coming up with answers.
Header credit: Tom Gauld at www.tomgauld.com
