Cash flow as the lifeblood is only half a metaphor.

Cash flow as the lifeblood is only half a metaphor.

 

 

Cash flow is often described as the lifeblood of a business.

While it is correct, it leaves a lot on the table.

If cash flow is the lifeblood, you also need a heart to pump it around the body. The leaner and more efficient the body in which the heart resides, the easier it is to pump, reducing the stress on the mechanism, reducing risk.

Similarly, to be effective blood requires oxygen to be attracted and distributed through the system.

Oxygen is what keeps everything working, it is the source of the power required to run the system, without which the system rapidly grinds to a halt.

In a business context, the oxygen is the input of information, the lungs and heart are the analysis and leveraging of that information, and the culture of the organisation is the body that holds it all together.

You go to the doctor to get a physical, where do you go to get a ‘commercial’?

An accountant will give you part of the picture, based on the books.

A ‘lean’ expert might offer many insights into the operational processes, particularly in a factory, and at the same time offer cultural insights.

A ‘6 sigma’ expert will deliver an arithmetic analysis of the efficiency of each part of a process.

A marketing expert (if you can find a bullshit-free one) will give you opinions based often on questionable and partial information, and usually biased towards their particular view of the role of marketing.

A sales expert will opine that everything else will be OK if you just get more leads for them to convert, and here is how!!

The point is that each will give you a picture of your business as they see it based on their experience, training, predisposition, domain knowledge, and their own assessment of WIFM.

Finding someone who ties all that together, and offers a complete, unbiased, and expert picture is a challenge.

 

 

 

 

Have Covid and AI been extreme Darwinian catalysts to change?

Have Covid and AI been extreme Darwinian catalysts to change?

 

 

Covid was a Darwinian catalyst, at least in my view.

A decade of slow change was supercharged into 6 months as businesses, institutions, and individuals, struggled with the need to change rapidly, and radically. It also unleashed an unprecedented innovation cycle in medical science that will have long term impacts on drug discovery.

In November 2022, another Darwinian catalyst struck. Open AI launched ChatGPT into the wild, setting off a chain reaction that surpassed the impact of Covid, which has since become endemic, and we have largely stopped worrying.

We have yet to understand the longer-term impacts of AI on social dislocation, personal security, and the ways in which the largess can be fairly spread across the community.

The trends in both cases were all there for those who looked closely enough with an open mind to see.

Pre-Covid it was clear that there were too many cafes, and we were generally over-shopped. Home delivery was increasing, as was remote work. The installation of ‘smart’ devices in factories and homes was normal, and product differentiation based on digital features was everywhere. Yet, it was slow going.

We had a binary mindset, the cake was a given size, and any change to the way it was sliced up meant there were winners and losers. Nobody wanted to be the latter.

Suddenly, in two whacks behind the ear, the cake has changed size and shape radically. The pre-Covid/AI status quo that included many points of friction and often unseen waste, previously sacrosanct, have been swept away.

All this costs money, so the cake has changed ingredients as well as shape and size. The suppliers of those ingredients have morphed into a few monster corporations that will continue to change the shape of our cake with little or no public oversight. Governance has become whatever it takes to make more money, as the power of regulators is substantially diminished.

This level of uncertainty has made us very jumpy, unwilling to trust, and wary of the future impact on our finances, security and familial connections. It has also made possible development of products and services inconceivable previously.

If you are a glass half full type, the opportunities are endless. If you are the other sort, find a comfortable place to hide, if there are any left.

 

How would Darwin see human evolution post covid & AI?

 

Header: Is a photo of Ghandi leading the ‘Salt march’ in 1930 which was the catalyst to the recognition that British rule over India needed to end.  

 

 

 

Will Generative AI replace people?

Will Generative AI replace people?

 

The astonishing ability of the new AI tools to increase productivity relies on being able to ‘learn’ by mining pools of data, then detecting and projecting responses based on statistical outcomes of that mining.

The next step, Generative AI, Generative Artificial Intelligence, is the point at which the artificial systems can reason, much as we do. This happens by making ‘neurological’ connections between apparently disconnected data, depth of domain knowledge and experience, breadth of more general knowledge that provides a ‘thinking canvas’ and context. These add up to instinctive responses we sometimes describe as pure ‘gut feel’.

There is however, a middle point.

‘Deep mind’ is a research unit now owned by Google. Their models evolved as AlphaGo and subsequently AlphaZero. These models cracked the barrier that seemed uncrackable, the ‘4-minute mile’ of computing. By beating the best humans at the complex game of Go, it demonstrated the ability of an algorithm to replicate in some form, the neural networks we have in our brains. In short, it can learn from its own experience, not reliant on outside data.

Crossing this Rubicon opens whole new territories to be explored.

It is in effect a ‘rolling probability’ calculation, each step using an estimation of the outcome of the previous calculation to deliver an adjusted outcome, in an ongoing process.

This is how we learn: from our experience.

As a kid I remember my younger cousin crawling towards a campfire surrounded by rocks. The immediate response of most was to grab him to prevent him getting burnt. However, my aunt stopped us, pointing out he would not be badly hurt by the mildly heated rocks surrounding the fire. However, when he touched a heated rock, it would create a memory-response loop that connected the fire to a modest hurt, thus ensuring he would automatically adjust his behaviour, and not go near another fire.

That incident stuck in my memory, and it reflects the way these AI tools are evolving rapidly towards ‘thinking’.

The dystopian view is that such developments over a few decades will see the machines take over. I prefer to think that we humans will find a way, as we always have, to overcome such threats. I guess my great grandchildren might know the right answer.

The header was created with help from DALL-E in about 3 minutes using a short series of prompts.

E&OE: A few hours after posting this post, I stumbled across this post on Medium that might bring forward the passing of the Turing test by a machine back into my lifetime. It records the evolution and current state of Googles 1.5 Pro tool, claiming it is to Current ChatGPT4 what a Model T is to a Ferrari.

The pace of change is astonishing, logarithmic, which makes it hard to comprehend by normal people..

 

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4 hurdles to successful ‘digitisation’

4 hurdles to successful ‘digitisation’

Often, I hear the term ‘Digital Strategy’ used as if it were an end result, some discrete set of activities to be completed.

To my mind, this is a misuse of the term.

As it is usually used, ‘Digital’ is all about the devices, the technology, whereas the value in digital is elsewhere. It is in the ability to get things done, differently, more quickly, efficiently, and in a distributed manner by those best able to complete the activity with the minimum of organisational friction.

It is about the business models enabled, the understanding of customers, ability to visualise the unseen, and communicate it clearly. It is not about the RFID tags, VR, and all the other enablers of digital, it is the outcomes that count.

Your strategy may be enabled by digital, but you do not need a digital strategy any more than you need a telephone strategy. They are both just tools to be leveraged.

Management of these changes is confronting, there is not a lot of precedent to go by. This is particularly the case now following the explosion of AI onto the scene. There is a lot of advice around, often delivered by those with a stake in selling you another product or service. However, it seems to me that there are a few simple parameters worth considering.

Functional Silo thinking is poison. The communication enabled by digital is inherently cross functional, better reflecting the way customers and suppliers see us and want to interact. Functional silos have little to do with optimised outcomes anymore. They have outlived their purpose and value.

One step at a time. While the pace of change is getting faster, and the pressure to keep up increasing, we all know what happens when we try and run down a hill really fast, we end up arse over tit. Matching the speed of change to the pace that your enterprise can absorb the change is pretty sensible. Of course, if you are the slowest in the competing pack, it may be better to get out while you can.

Digital is a team game. Hand balling digital responsibility to the IT people is a mistake. You will end up getting what they think you need, which is rarely what you really need. The real challenge is engagement of people not really focussed on digital. The primary example is in the space of marketing automation. Suddenly it exploded, way beyond the capabilities and experience of most marketing people, who are nevertheless now investing more in tech than the IT people. It is essential that the right capabilities are built in the right places. Finally, everyone affected, which is everyone, needs to be in on the secret, with all the options, challenges, and opportunities transparent. The unknown is the father of all sorts of ugly children.

Think long term. Digital transformations are not just about which software you will install to automate a process. Is more about what the business may look like in 5, 10 years, and what steps do you need to take over that time to reman relevant. Technology, much of which may not yet be available, will play a vital role in that evolution, but they remain tools of the evolution, rather than the main game.

Header credit: My thanks to Tom Gauld in New Scientist.