By now, the reader should understand that things are created (genesis) which are uncertain, rare, constantly changing and hence chaotic by nature. These things diffuse through society through various constantly improving iterations (evolution) driven by competition (consumer and supply). Ultimately they become a more common, well-defined and standardized (i.e. linear) commodity.
This process of evolution impacts activities (things we do), practices (how we do things) and data (through models of understanding).
Where those things can become components of higher order systems (e.g. nuts and bolts with machines) then as they evolve (become more linear) they accelerate the genesis of those higher order systems through componentization. This extends our value chains. Hence evolution is associated with increasing efficiency (of what is evolving) and increasing rates of speed and agility in creation of higher order systems. Genesis begets evolution begets commodity components begets higher order genesis ad nauseum.
The process is a continuous cycle that we commonly describe as “progress”.
The new higher order systems are sources of future wealth and hence we see flows of capital from the past to the new (creative destruction). However, the process is not smooth because practices tend to co-evolve with activities and hence we see inertia to change due to legacy constraints.
Equally suppliers have inertia due to past success, so the later stages of evolution (in particular the switch from product to utility) are associated with new entrants.
However, the change is inevitable as consumers are in constant competition and the benefits of efficiency, increased agility in building higher order systems and new sources of wealth turn a trickle into a flood. All companies have to adapt just to stand still relative to an evolving and surrounding environment (Red Queen).
This pace of change will often catch out suppliers as they are lulled by consumer inertia to the change and the previous more peaceful, slow moving stage of relative competition. Hence we can describe the transition of competition around an activity as one of relative peace to one of war to one of wonder and creation of new higher order marvels.
The peace state can be characterized as one of incumbent giants with relative competition where sustaining change exceeds disruptive change. The war state is one of new entrants, a fight for survival and where disruptive change exceeds sustaining.
However the progress from peace to war is not unexpected and there is no reason (from culture to inertia) for why the past giants cannot be prepared. Disruption, unlike the case of unexpected changes in the market, is entirely preventable but rarely is prevented.
Of course, the change reduces barriers to entry and allows for new things that can impact value chains in unexpected ways (from gas lamps to light bulbs, from naturally harvested ice to ice making machines). Hence some indirect disruption is unpredictable and the innovator’s dilemma runs rampant.
This cycle of changing states (wonder, peace, war) created by the interaction of inertia and the economic pressures of evolution (efficiency, agility and new sources of wealth) which is itself driven by competition (user and supply) and the need to adapt to competition (Red Queen), appear at both a local and macro economic scale.
The macro economic scale we tend to call Ages as in Industrial Age, Mechanical Age, Internet Age. Each has a time of Wonder, Peace and War.
In certain cases that which is evolving can accelerate the entire process for all things by improving communication e.g. postage stamp, telephone, printing press, the Internet. In all cases, the drive towards more evolved and higher order systems consumes greater quantities of energy (though our waste vastly outweighs this).
Beyond creating inertia, the co-evolution of practice with activities will result in new organizational forms from Fordism (the age of electricity) to Web 2.0 (the age of the Internet). In all cases, these new organizational forms are more adapted to this changing world of higher order systems and are more effective at managing the flow of change from chaotic to linear.
Each age can be associated with the evolution of organisations themselves.
However, our systems are far from perfect. Our tendency to one size fits all (one of the solutions of Ashby’s Law of Requisite Variety) tends to create a yoyo between extremes. Whether project management (agile vs six sigma) to marketing (push vs pull) to structure (networked vs hierarchical). A better balance can be found through embracing both and as organization evolve we tend towards this balance.
Our confusion over this simple pattern stems mainly from terminology and our inability to see it. We use the word innovation to mean genesis, a feature differentiation of a product or even utility provision of a pre-existing model. Our use of the word hides the obvious pattern of evolution in a fog of “Everything’s an Innovation”.
The same problem extends to other parts of our language. The process of evolution (often called commoditization) is different from the process by which an idea gains economic value by implementation into a tradable thing (i.e. idea or concept turned into something real). Alas, the process that represents a conversion of social (idea) to financial (tradable thing) capital is called commodification and whilst it is entirely different from the process of evolution, the terms of commodification and commoditization are often used to mean the same thing. It’s a bit like using the word chalk to mean cheese.
Hence in a world where obvious patterns are clouded by the misuse of terms, where companies often compete without any means of understanding the landscape that they exist within, we often believe they things are a lot more random than they are.
Strategy often becomes one of “do what others are doing” and vague hand waving notions. We grasp at concepts like inertia and disruptive innovation as though this explains all - “We couldn’t help ourselves it was an unexpected change, we were caught by the Innovator’s dilemma”.
In some cases you are, in many cases you are not. You could have survived.
And so the cycle continues, new activities that appear evolve creating new inertia barriers (due to success) and a new war results from the inevitable march of competition. The same lessons are repeated, new forms of organization appear and we marvel at the changes.
The plethora of new activities created also results in new forms of data we have yet to understand, it is unmodelled or unstructured (if you insist). We stare in amazement at our progress as though somehow this time of wonder was any more wondrous than any previous time of wonder. The cycle continues.
The cycle has occurred numerous times over the last three hundred years. Alas “the one thing we learn from history is that we never learn from history”. In the hope that we learn this time, I’ve drawn the cycle in figure 31 and I’ve taken the liberty of removing the axis of value chain and drawing it as cycle. Each time we move through the cycle, value chains extend.
Figure 31 – A Frequently Repeated Cycle.
So, let us bring ourselves to our modern day.
Driven by consumer and supply competition, the activity of computing infrastructure has evolved from products to more of a utility. It is so widespread and so well defined it can now support the volume operations needed.
New entrants not encumbered by pre-existing business models (such as Amazon) have initiated this change and a resultant state of war has developed in an environment that was once governed by relatively peaceful competition between incumbent product giants (Dell, HP, IBM).
We see an explosion in the genesis of novel higher orders systems created on these utility services, a flow of capital into the new higher order systems and we marvel at the speed and agility of creation. Endless books are written on creative destruction, componentization and change.
As expected, practices have co-evolved with the activities. We talk of distributed systems, design for failure and chaos engines (or monkeys if you like). An entire movement known as “devops” has developed around these changes.
Consumers of the past models of provision (i.e. computing products such as servers) have also shown inertia to change. Citing all the typical risks and the issue of the legacy estates, they want all the benefits of agility, efficiency and new sources of wealth but without the cost of transition due to re-architecture. They want the new world but provided in an old way. They want the old dressed up as the new. They talk of enterprise clouds that are more rental services than utility.
Many of these consumers are oblivious to the issue that those benefits (efficiency, agility, wealth) are also pressures for adaption which will force them to change as competitors do. It’s not a question of “If”, it never has been. It’s a question of “When”.
Their suppliers encumbered by past business models race to provide this “old” world dressed up as new. They, suffering from their own inertia, are unaware that the trickle to the new world will become a flood at a pace they are not expecting. They watch Amazon thinking it will tail off, that it’s really only for new start-ups and green field sites. This is wishful thinking.
Along with changing practices and movements such as “DevOps”, new forms of organization appear. New structures, new ways of operating diffuse and evolve. Tomorrow’s Fordism has been with us for many years and it’s spreading.
As expected, for any student of history, we have also seen an explosion (as in genesis) of new data. Whilst the scramble to provide “big data” systems focuses on the issues of volume, it is the un-modelled nature of the data that is key. It wasn’t simply the volume of natural history data or the explosion in the number of books through printing presses that changed our world; it was the models of understanding that altered us.
This data will become modeled and we will progress in understanding but not without arguments of the Structured vs Unstructured or Dewey Decimal vs Cutter type beforehand. We blissfully ignore that all data starts as unstructured and it is through modeling that the structure is found.
It’s like our assumptions of innovation. It’s never the innovation of something that changes the world; it’s commodity provision as good enough components (e.g. nut and bolts, electricity, computing).
It’s not the volume of data that matters; it’s our model of understanding.
So, cloud is all about utility provision of pre-existing activities to commodity components, explosions in the creation of higher order systems, new sources of wealth, new practices, new forms of organisations and disruption of past models stuck behind inertia barriers and indirect disruption through changing value networks and lowering barriers to entry? Yes.
This was all perfectly clear in 1966 when Douglas Parkhill wrote the book the “Challenge of the Computer Utility”. It was only a question of when.
This was all perfectly clear in 1966 when Douglas Parkhill wrote the book the “Challenge of the Computer Utility”. It was only a question of when.
By 2005, the weak signals of “when” were screaming loud. The “when” was NOW!
None of this should come as a surprise.
The CEOs of the past giants should have leaned over their shoulders and pulled down from their bookcases their “What to do when Computing Infrastructure is ready to be a utility” playbooks. These playbooks should have been crafted and refined over the decade beforehand when the weak signals shouted “getting closer”.
By the time Amazon launched, the past Giants should have prepared to launch at a massive scale. Culture is gameable and should have been gamed. Inertia is manageable and should have been managed.
By 2010, Amazon should have been crushed. The past giants should have dominated the market. They had all the advantages they needed. But that’s not what happened. Those past giants hadn’t mapped this change.
They were not prepared for the expected.
Many will suffer the same fate as previous companies who have failed to prepare for the expected from Blockbuster to Kodak. But before the normal round of excuses begin, the inevitable rush to safety of executives behind the “innovator’s dilemma” and claims of unexpected changes, let me blunt.
Those companies failed because their executives failed. Not culture, not inertia, not unexpected changes but instead a total failure of strategy. They were simply not up to the job or as Gandalf might say “fool of a Took”.
As I said in the beginning, this work is not about gaining advantage but about surviving and mostly that’s surviving the expected. The cycle continues today, as it has in the past and as it will tomorrow.
So on the assumption that you’re not one of those facing oblivion through some gross failure of past executive play, let us turn to the new forms of organization and practice that you’ll need to deal with today.
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Post 14 of 200
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