Spoiler Alert ... 3D printing

Anyone who knows me, knows I've spent well over a decade keeping tabs on and occasionally being actively involved in 3D printing and printed electronics. My real interest, as it has always been, is the wider economic cycle of change of which 3D printing will be part of the next cycle.

To cut a long story short, 3D printing is about commoditisation of the means of manufacture in the same way that the Internet was about commoditisation of the means of mass communication and Cloud (a term I despise) is about commoditisation of a range of IT activities.

Anyway, I spent rather a dull afternoon in the company of a respected "future"-ologist who clearly has no idea what he is talking about. So, I thought I'd be a miserable old fart and tell everyone what 3D printing is actually going to do.

This is a SPOILER for the future.

1. Commoditisation of the manufacturing process will result in an explosion of new activities (higher order systems) as the means of manufacture become ubiquitous. This will create a time of wonder and new industries (see electricity led to radio, Hollywood, consumer electronics, computing etc) but what those new things are and what new industries form, well we don't know yet because they're uncertain (this is the one bit which you still have to wait and see). However, this won't stop endless pontification on the subject and book writing about the massive transformation underway and "Does Manufacturing Matter?"

2. The manufacturing industry will shift from a state of "peace" where relative competition exists and sustaining change tends to exceed disruptive change to a state of "war". It will become a fight for survival, where many past giants who have created inertia to change due to their past success fail to adapt and subsequently collapse. During this "war" disruptive change will exceed sustaining change and new entrants (not encumbered by past business models) will lead the charge. Among the new entrants will be our future giants.

3. Executives of former giants that are collapsing will start once again blaming culture (i.e. others) for their failure (lack of vision and action).

4. We will see a flood of capital from the past manufacturing industries to these new industries. Some economist somewhere will write a book on Schumpterian economics and 3D printing.

5. As the activity of manufacturing changes (from custom built factories to ubiquitous 3D printers) then practices in manufacturing will change. Practices often co-evolve with activities (e.g. architectural practices have shifted with computing infrastructure moving from product to utility). Someone will come up with a catchy name for this, like "DevOps" with cloud today.

6. The new practices will result in new forms of organisation as per electrical age (Fordism), Internet age (Web 2.0), Cloud (Next gen) and every other age. Some management guru will write a book on these new organisational structures probably calling them the "new Fords" or another equally lame term.

7. At the height of this change someone will write a book about how commoditisation of the manufacturing process (though they won't call it that as we will have created some daft term like "cloud" etc) will lead to mass unemployment etc. This book will probably overlook every other book which has been written about the same phenomenon (Hawkins and the electrical age) and how each time the author failed to anticipate the new activities (higher order systems) and related industries that will form e.g. electrical age led to radio, Hollywood etc etc. The author will of course fail to anticipate because the activities are uncertain (see point 1).

8. In a desperate attempt to save their bacon, past industries will promote the importance of physical DRM to prevent people stealing copyrighted ideas or making dangerous items. Security and the threat of people being able to manufacture things like guns will be used to explain why this change is dangerous for us all and must be stopped. Some lobbyist groups will persuade some Government somewhere that progress is bad.

9. Along with disruption of past giants many secondary industries will discover that their industries will be disrupted due to rapid reduction in barriers to entry. See Newspapers and the "Internet is good for us as it'll reduce our distribution and printing costs ... wait ... bloggers ... oh, no ... stop the Internet" moment. Someone will write a book on how 3D printing is killing our culture / industry / society etc.

10. Because of the reduced barriers to entry and the rise in competitors that were once former consumers (e.g. Amazon vs Infrastructure Providers, Bloggers vs Newspapers), someone will write a book on "Democratizing the means of manufacturing" or something like that. I wish they wouldn't.

11. The trickle of adoption to these new manufacturing techniques and practices will become a flood as the combined forces of efficiency (through commoditisation of the activity), increased agility in building higher order system (componentisation) and future sources of worth (Schumpeter) kick in. This will take everyone by "surprise" especially the analyst who expected the change to occur slowly in a linear like fashion (which it never does).

12. With the new techniques and practices there will be a growth in concepts of Agile Manufacturing followed by endless arguments over Agile vs Six Sigma equivalents. Eventually people will realise that one size doesn't fit all and both approaches have their place.

13. As commoditisation of the manufacturing process spreads and the explosion in higher order systems and new industries accelerates there will be a corresponding explosion in un-modelled data. This is data which we don't know how to model yet but will eventually be modelled as we understand it more. Annoyingly, people will call it unstructured and probably create a term like "Big Data 2.0" ignoring the fact that the current Big Data revolution is about the fifth one we've been through in the last 200 yrs.

14. As hardware becomes more malleable like software, some bright spark will realise that the function of a device consists of digital and physical elements both of which can be described by code and hence a new language will form. In this new language you will describe the function of the thing you want and a compiler works out which bits should be code and which bits should be bits to be printed. They probably won't call it "SpimeScript" but they will come up with an equally daft name.

15. The open meme (e.g. open source, open hardware, open data, open APIs) will happily continue its symbiotic relationship with the Internet and grow rapidly in this space. Former product design companies will get fairly grumpy about this and there will be endless patent arguments. The patent system will become hopelessly outmatched for this world and will become as harmful for manufacturing as it has been in the software industry.

16. Google, Amazon and the like will swoop in with their normal two factor market and platforms plays to grab the developing ecosystems in this space. Many manufacturing, architectural and construction companies will find themselves now competing with the likes of Amazon backed by huge ecosystems of companies selling designs for direct printing (from that new watch to your new home). The results won't be pretty as usual.

17. Some Government official (probably pushed on by lobbyists from past industries) will start to talk about the needs for certification of designers, architects and the like on the grounds of "consumer benefit". Some standards body will jump on this as a potential new revenue stream. It will all go badly wrong.

18 ... oh, it's late. You get the gist. Just go back and replay every other industrial cycle of change.

A dangerous intervention ...

A few years ago, I warned about the dangers of Government intervention and creation of certified cloud providers. After reading the EC communication on Cloud Computing, my concerns are that we will start on this path.

First, some background :-

Cloud computing represents the evolution of a range of IT related activities from a product and product service model to one of commodity and utility provision. As such it has impact in terms of efficiency, rapid generation of higher order systems and new sources of value creation. In much the same way utility provision of electricity spurred on new activities such as radio, telephone, computing and new industries around this.

However, it's not just activities (what we do) that evolve but practices (how we do things). Hence architectural practices related to computing are co-evolving with the activity of computer infrastructure and we see the rise of what is known as "DevOps". This is all normal fare and these cycles of change repeat throughout history.

Each time we undergo such a change both consumers and vendors can have inertia to it. 

In the case of business consumers, some of this inertia is due to the changing architectural practice and the issue that legacy applications are not designed for the cloud. Hence there is often a desire on their part to have the new model operate like the old i.e. to have clouds which actually have the characteristics of more old fashioned data centres, a concept commonly dubbed as the "Enterprise Cloud". This inertia can be exploited to extend old business models.

In the case of vendors, much of their inertia is due to past success i.e. they become habituated to selling customers products and product rental models and are encumbered by their existing business. Which is why this period of change is often initiated by new unencumbered entrants (in the case of computing infrastructure this would be Amazon). The past giants often attempt to continue or extend their business models, believing the change is just a fad. History is not on their side and the result is disruption of the past models.

Today, we have all these issues with cloud - the new entrants providing utility services for computing, vendors and customers often suffering inertia and the attempt to extend past models.

EC communication on Cloud Computing

The EC communication recognises many of these changes and talks of the industrialization of IT. It notes the importance in forming competitive markets of utility providers with easy switching in order to avoid lock-in and other concerns consumers have. This is all reasonable.

The EC communication highlights its intention to help standards form in the industry in order to achieve these goals of competitive markets and choice for consumers. This is also reasonable if the approach is one of adoption of defacto standards (i.e. market chosen) and ensuring their provision both as open standards (i.e. royalty free) and through reference implementations in order to ensure semantic interoperability. These reference models (i.e. an expression of the standard as code) would need to be open sourced in order to ensure a competitive market which is free from constraints or control of specific vendors.

Already, in the infrastructure space, such candidate reference implementations exist with 850+ companies now involved in the Open Stack effort, an entirely open sourced IaaS which is at the heart of an industry movement towards creating competitive, service based markets. It's one of many such potential reference implementations - others including CloudStack, Eucalyptus and Open Nebula. In light of these developments, an EC approach of supporting any defacto provided as open standards with open source reference implementations should suffice in encouraging competitive markets.

Another part of communication discusses the need for voluntary certification and the EC's intention to enable this. If a competitive market of multiple providers forms then as with other utility industries such an assurance / compliance industry should be expected to form. The objection with the communication is that given the development of the market there is no need for intervention of the EC with certification. The danger is the EC risks "blessing" the certification programs it involves itself with.

Such an act can have negative consequences because certification is fundamentally about approval of certain characteristics however the market has not yet come to terms with what characteristics are essential and many business consumers in the market are suffering inertia to change. In these circumstances, certification could be manipulated to "bless" past business models i.e. to create a preference for "Enterprise Clouds" and thereby play upon the inertia that some companies have.  For example, a focus on SLAs can be used to strengthen the case for "Enterprise Clouds" over "Commodity Clouds" despite the latter being the more evolved state that industry will head towards.

The effect of this can be detrimental to industry, as companies adopt services that they wish to believe represent the future and are "blessed" by the EC through supported certifications but then discover the services represent a continuation of old models which take advantage of their inertia to change i.e. the quick fix to adopting cloud is simply to rebadge your existing enterprise hosting service as "Cloud".

A counter argument to this, is that though there is a risk, the trade off to this is encouraging adoption however it assumes that the EC is more capable of deciding what certification is required than the market. Given a situation where there is already significant market efforts to make interoperable systems and competitive markets (such as Open Stack and its 850+ member companies) then this seems premature.

I would agree with the EC effort to support standards, where those standards are designed to encourage a free (as in from constraints) and competitive market and hence based upon defacto (i.e. market chosen), open standard and open source reference models.

I would not agree with the EC effort to support certification programs as these would naturally form in a competitive market and the EC runs the risk of interfering with the process before the market has chosen and the EC cannot be sure that such interference will be beneficial and not manipulated.

The Standards Jungle ...

The EC has released a communication on cloud computing

I've had a brief read, I'm in the middle of other work but I'll note that the general comments about the importance for future industry, competitiveness, good historical comparison (industrialisation of IT, comparison to utility) etc are all fairly standard fare. Though there's nothing particularly interesting it's good for them to repeat it. 

There's also the usual wobbles on cloud reducing cost, alas Jevons' paradox ... any reductions will be temporary as we will end up doing more.

However, regarding the Fragmentation of the digital single market and the Standards Jungle, I'll make a couple of observations.

In the value chain associated with cloud, one of the components is obviously enough the Internet i.e. availability of this commoditised means of mass communication has enabled commoditisation of discrete IT activities towards utility services (e.g. IaaS). Now, the Internet is as much a social as a technology phenomenon inherited from the hacker ethos - anonymous, decentralised, egalitarian, interactive, neutral to end user etc. 

The Internet's existence also allowed for the easy formation of communities such as as various open technology communities (e.g. open source) which themselves have inherited the hacker traits. There's a symbiotic relationship here between the Internet enabling the communities and the communities in effect sabotaging mechanisms to control the Internet (either corporate or Gov) through the technology they build.

Today, open technology is huge business and most of this is unaccounted (see the clothesline paradox). For example the economic contribution of Apache is enormous but not normally reported - O'Reilly has a fantastic report on this.

So, onto this symbiotic relationship between the Internet and the open technology communities, environments which by their very origins are anonymous, decentralised and neutral which have generated huge economic value including spurring the whole cloud industry most of which also depends upon open technology - we want to apply more centralised legislative frameworks with concerns over areas such as security (in principle due to anonymity)? 

Hmmm, this feels like it could be a repeat of how the radio spectrum was divided up due to security concerns for the benefit of a few companies but in the process managed to destroy a much wider ecosystem. However, this time the economic value at risk is huge. I'd be naturally cautious with any such measure.

So, unsurprisingly, I have concerns over areas such as the certified cloud providers / standards approach.  I'd want to look closely at the details of this. i.e. could this end up being a rehash of the OSI vs TCP/IP debacle? 

Overall : my view on this is 50/50. In some parts it is probably uncessary and if badly handled then potentially downright dangerous. I'll write something more on this when I've had the chance to read it properly.

Something I'll be coming back to ...

I'm just finishing my latest research and I thought I'd share a graph with you as I'm going to be using it from time to time.

The graph is a comparison of a reasonable sample of companies across two axis - the level of strategic play vs the use of open as a means of competing against, outmanoeuvring others.

The bubbles size represent the % of two populations - those that consider themselves Traditional and those that consider themselves more Web 2.0.

Basically, companies break down into four groups :-

• Players : companies which think strategically about IT and are willing to use open as a means of competing. (STRATEGY + ACTION)

• Thinkers : companies which think strategically about IT but don't tend to use open as a means of competing. (STRATEGY + DECISION NOT TO ACT)

• Believers : companies which don't think strategically about IT but do use open as a means of competing. (NO STRATEGY + ACTION)

• Chancers : companies which neither think strategically about IT nor tend to use open as a means of competing. (NO STRATEGY + NO ACTION)

There's a whole underlying model (all to do with evolution) of why these groups exist and the impact of them, their success etc. However, I'm not going to go through this now.

I just wanted to say that being in the Chancers or the Believers group doesn't seem to be very healthy. Which is why I've recently been posting about "What's my IT Strategy" and "Open by Default ... No Thanks"

You see, there is method in my madness and there are reasons why I raise these questions.

Open by Default ... No Thanks

Despite being involved in the open source community for over a decade, I am not a fan of open by default. My preferred route for deciding whether to deploy an open technology approach as in open sourcing a project or providing it as open hardware or open data or via an open API is :-

1. Map out the value chain of a revenue stream within the organization. The value chain should contain all the systems (activities, practice and data) needed to create the high level product or service.
2. Apply evolution to the value chain. For example, determine whether the activities are in a state of genesis or more commodity. Care should be taken to ask whether it is widespread and well defined in the industry and not how any specific company considers this activity (as the company maybe suffering from inertia to change). Where a difference exists this should be marked and an inertia barrier added. 
3. Apply forcing functions to the map for where open technology already exists and is driving a system to a more evolved state. 
4. Mark barriers of entry (whether regulatory or requiring high amounts of financial, physical or human capital) and impacts on supplier and buyer strengths.
   
5. Determine your intent (from efficiency to standards game to recruitment) and use this map to determine whether to open something or not.

Wow, this sounds like a lot of work just to answer a simple question of whether to open something or not? Actually, it isn't. Mapping out the value chain of an organisation should take a few hours at most.

The point of the map is it gives you some situational awareness. It can be used to anticipate changes and competitors action. It also forces you to think about what you're trying to achieve with an open technology approach like open source, how you want to manipulate the market, what opportunity exists, what strategy are you following?

What I don't like about "Open by Default" is it often rapidly becomes "Open without Thinking" and alas this degenerates into "Open without Value" i.e. it's the act of thinking about how to manipulate a market which is more likely to mean a business will value it and put resources, effort and focus into an open technology effort.

If it turns out that you can't perceive any value whatsoever in the project then by all means throw it out there with the hundreds of thousands of other open "meh" projects. Someone might find it useful, it might have some form of beneficial effect you hadn't realised or it might help you hire that skilled engineer / data scientist. But at least, you've thought about it.

Thinking about something generally translates into "we value this". Open technology approaches are powerful tactical weapons in the competition between companies and are far too valuable to be simply ignored or launched without thinking.

Unstructured vs Structured

There are many terms I dislike from the misuse of the term innovation to the whole computer utility vs cloud debate. Another example of this is the whole unstructured vs structured data argument.

The terms unstructured vs structured implies there is a difference in the data sets i.e. unstructured data is by its very nature unstructured and unlike structured data. The term implies this is a permanent state of affairs, a set of data which has no structure and therefore cannot be modeled.

However, our entire history of scientific endeavour can be broken down into discovery of data we didn't understand, creation of models to explain the data and finally data we now understand. In other words we constantly move from unstructured to structured via the creation of a model.

Hence I prefer the term un-modeled data vs modeled data. Inherently this implies there is not a difference in the data sets just simply in our ability to model. It implies that there will be a movement from one to another.

What is your view? Am I the only person who dislikes this framing of unstructured vs structured?

The Real Company syndrome

Ten years ago, I went on the Canon Corporate Executive development program at INSEAD and other institutions.

I remember it well because on the first day, in the first meeting we examined the question of the impact of the internet and what Canon's involvement should be - which was the overall theme of the course.

In a group of executives, there was a massive majority opinion which was very strongly voiced that it was just a channel and Canon shouldn't get directly involved. Then there was me, a single voice (ok, I was CEO of a subsidiary) up against this solid wall of opinion of SVPs, VPs from all over the globe.

Fortunately I've never been shy of a fight. Opinions changed by the end of the six month course but that first meeting always stuck in my mind because of one phrase.

The phrase I heard at that meeting was how this or that company wasn't a "real" company. In that meeting it was how Amazon wasn't a real company unlike Kodak.

Today of course, no-one would dream of saying that Amazon wasn't a real company but I keep on hearing that phrase. In the cloud space it was "but are there any examples of 'real' companies using cloud' etc.

I'd say how about Netflix and the response would be "no, 'real' companies not these tech companies'. Ensue argument over what defines a company, how all media companies are tech companies etc etc.

Where does this awful term 'real' company come from? Is it simply an artefact of inertia and a mechanism for manifesting denial over change?

What's my IT strategy?

I was asked this question recently about a company's IT strategy. Which bit was actually strategy? This is fairly easy to work out.

1. Take a company's IT strategy.

2. Now remove any and all references to a choice of a specific vendor as these are purchasing decisions e.g. we will use SAP to ...

3. Now remove any and all references to implementation details e.g. we will build a private cloud to ...

4. Now remove any and all references to operational details e.g. we'll improve our SLA's and reporting times to ...

5. Now remove any and all references to tactical choices e.g. we will invest in big data, BYOT (bring your own technology) and open source 

What is left, is the IT strategy. This should give you an idea of where the company is heading and what is governing those purchasing, implementation, operational and tactical choices.

Open Source and the Cloud

"It's important to understand that open source in this utility computing world is not a tactic, it's not a strategy, it's the only practical way of creating and competing in a marketplace"

OSCON, 2007

I've been asked why the OCI principles has the phrase "and at least one such implementation must be licensed in its entirety under an Open Source Initiative (OSI) approved license"

First, it's important to understand that in a utility world, any standard must be running code for reasons of semantic interoperability. In order to create a competitive market rather than a captured market this has to be open source. You can find more on my discussion of competitive markets and open source in various of my talks and posts between '06-'08. However, you'll find the basics in the OSCON 07 presentation.

By implementations this can refer to multiple providers offering the same code base or multiple providers offering different code bases. However, as long as all the implementations are "full, faithful, independent and interoperable implementations" with the open source implementation then you have a free market. The open source implementation in effect acts as the reference model.


For example, multiple Cloud Foundry providers means multiple implementations and there already exists an open source implementation in Cloud Foundry itself. Of course, providers could set up with modified versions of Cloud Foundry (e.g. operational improvements) and as long as they are full, faithful and interoperable implementations they would meet the OCI principle.


You cannot avoid the need for an open source reference model in the OCI principles. But that's because you cannot avoid the need for an open source reference model in a competitive utility computing market.


Competitive markets and Open Source are intertwined. Always have been. It's what we tried to do with Zimki all those years ago.

Dante's Quadruple circle of hell - The Expense System

I have a fervent dislike of expense systems. It's not that I have particular dislike of an expense process but it's the systems themselves that always get me.

First, a good example (as in one I like) of an expense process.

The company gives me a company credit card which the company owns. There's a limit on the card. I spend as is required on a principle of trust. The company accountants receive the bill. If anything looks odd they come and ask me.

This is my favourite expense process, it's blissfully happy. It works on trust as in the company trusts me and gives me this right. It's hassle free and occasionally the accounts team might ask what this or that item was for. It works on an exceptions basis.

The few times I have experienced this process, I've been delighted.

Second, a bad example (as in one I hate) of an expense process.

The company gives me a company credit which I own (i.e. it's my money). I spend as is required, in other words I dip into my own pocket and spend on company stuff.  Ok, it's called a company credit card but it's actually my money.

Then after spending my money, I have to fill in forms to claim my money back. There are rules, usually lots of them and often discussions about whether this item is valid or not and of course I have to have receipts.

I usually have to fill in a horrendously detailed system, upload scanned images of receipts, comply with the rules, deal with any discussion - which all takes up my time. Along with this, there is often any number of other authorisation systems which have to be complied with in order to get back my money which I've in effect lent the company. Of course any late charges are my responsibility and there's no question of interest being paid.

The many times I have experienced this process, I've hated it.

In fact, I normally start to respond at a subconscious level by avoiding any expense. I start to realise that things I would normally do, I avoid. It's the equivalent of being invited to a pub by a friend, them asking you to pay for the drinks but they'll pay back later and when it comes to later they ask for itemised receipts and start questioning. The chances of me being available next time I'm invited drops quickly to zero.

I do find however some people love it because of some other benefit like they gain air miles on the card or some other point scheme. As someone who has taken a thousand flights in their life - the last thing I ever want is air miles.

So why am I mentioning this?

Well expenses for me can often be a time of increasing expletives, frustration and the thumping of a keyboard. But, it turns out my uncle enjoys the experience and even has an expense afternoon. A part of his week he sets aside for doing expenses routinely.

However, he does feel a bit guilty about this because he feels it's not proper work.  Well I agreed with him. In my experience filling out expense systems is not proper work, it's in fact hell and as such should count for quadruple time.

But I'm curious, do other people feel guilty about using work time to fill out expense systems? Why?

I don't like Hayek vs Keynes

I'm pro Hayek, pro Keynes and very much Anti Friedman. I see an awful lot of discussion which is Hayek vs Keynes and I don't quite understand it. Certainly, these two great thinkers had disagreements and their approaches (one top down, the other more bottom up) were different but their models are not mutually exclusive. It's the mix of Hayek, Keynes and Schumpeter which has always made economic sense to me.

To explain why I feel this way, I'll use four graphs. The first two examine the process of evolution as opposed to diffusion, the third is an examination of value chain vs state of evolution and the last is one the cycle itself.

As activities commoditise they can enable higher order systems to appear e.g. electricity begets radio, computing, Hollywood whereas nuts and bolts beget machines which in turn beget generators etc. These higher order system are where new value is generated and hence we see a flow of capital from past industries (which are commoditising) to new industries (which are being created).

The process of evolution is not however smooth as companies build inertia to change (due to past success), which is why when an activity commoditises it's often associated with new entrants into the market and disruption of existing players.

Figure 1 - Evolution & Diffusion

Figure 2 - The Process of Evolution

Figure 3 - Evolution vs Value Chain

The above can be simplified to a cycle of commoditisation enabling the genesis of new activities (which we often call innovation but there's problems with that specific term). The shift from product to commodity and utility services and the associated inertia barriers to change mark a phase change in an industrial ecosystem. We go from a relatively peaceful state of competition with sustaining change exceeding disruptive to a fight for survival, with new entrants and disruptive change exceeding sustaining. We literally go from peace to war.

Of course, the explosion of new higher order systems (due to componentisation effects) create a rapid growth of new industries (genesis) and a time of wonder and amazement. This cycle of wonder, peace, war repeats throughout history both in specific industries and at the macro economic scale through Kondratiev waves or what we more commonly called ages.

The age of electricity started not with the genesis of electricity provision (which can be traced back to  Parthian times) but with Westinghouse & Tesla and utility provision of modern day electricity supply. This disrupted past industries (war), created an explosion of wondrous new activities built upon this component supply (growth) and eventually the new giants of industry settled down (peace). I've created a simplified map of this onto figure 4 to show the cycle (ignoring the value chain).

Figure 4 - Cycle of Change.

So, now to Schumpeter, Hayek and Keynes. The overall cycle describes concepts in Schumpeter's work on business cycles. During the growth and peace cycles, the application of Hayek's policies seem the most logical - limiting excessive growth in credit and the impact of central bank policies such as low interest rates which encourage speculation, lower savings and bubbles etc.

However during the war phase (where much of past industry is suffering inertia often compounded by the demands of financial community) then direct investment in new industries and the stimulation of demand - a Keynesian approach - seems a more effective way of balancing this market change.

But this is no different to the issue of managing activities which due to changing characteristics vary from agile development (in the genesis phase where they are more chaotic) to six sigma (in the commodity phase where they are more linear). There is no one size fits all policy and instead you need to use the right policies for the right stage of evolution.

This is why I don't get the whole Hayek vs Keynes debate - which noticeably is a very US based discussion and occurs to a much lesser extent in Europe. The debate is as simplistic as the whole Agile vs Six Sigma, SQL vs NoSQL, Push vs Pull, Hierarchical vs Networked debates of one size fits all.

The answer always seems to be both are right, you just need to know when to use each. So, I'm pro Keynes and Pro Hayek as there is both a time to steer markets and a time to set them free. Furthermore, since markets evolve at different rates then you need to use both approaches at the micro level i.e. one market you let run free whilst in another you can be busily investing and stimulating in at the same time.

Does this make me Pro Friedman? Absolutely not. I'm Anti Friedman and I have little time for the Big Dogma of Monetarist theory / Neoliberals which has been created in his image. I do understand the political reasoning of supply side fiddling with QE because it helps maintain the illusion of house and stock prices (through cheap foreign capital) but continues the stagnation of our real internal industry and society. It is not worth it.

We need to direct our industries to overcome their inertia and that requires direct investment along with stimulation of demand. I find scant evidence that the financial community can resolve this in a timely fashion as they have inertia of their own. Instead, China's huge investments (at this moment in time) in internet technology, renewable energies and manufacturing technologies such as 3D printing & printed electronics suggests an alternative way. They seem to know how to play this game and they're aiming to grab the future.

We should have buried the monetarist dogma long ago and started actually playing the game. The whole Keynes vs Hayek debate feels like just another artificial campaign to maintain the status quo and all the suffering that comes from it (social inequality, lack of true mobility etc). I, for one, don't like it.

On Predictions

There are three basic forms of predictions that I make, which given this recent podcast I thought I'd better make clear.

First, there are predictions I make regarding the overall process of evolution and the cycle of change. These are based upon causation, correlation and past testing and I'm confident enough in this to describe the model as a weak hypothesis.

Second, there are predictions I make regarding specific industry actors. These are based upon my opinion and naturally any outcomes depends upon the strategy of the actor, the impact of others and economic events. These predictions are therefore inherently uncertain. I'm not confident in these at all as they are purely conjecture that I consider likely.

Lastly, there are predictions I make regarding my on going exercise of prediction testing. Here I'm deliberately aiming for a 50% prediction rate of the headline predictions which are based upon a hundred plus components. This is purely an experiment I'm running to see if I can improve some general models I have. Overall, this experiment is simply an idea at the moment which I'm refining.

For reference, the general scale I use is as follows** -

Idea = anything you think of. It's an idea. No Confidence.

Conjecture = idea + some initial supporting data (upto a hundred or so data points) demonstrating merit. Extremely Low Confidence

Reasoned Hypothesis = idea + initial data + correlation (through a couple of experimental observations) + initial models of causation. Low Confidence

Weak Hypothesis = idea + data (a few hundred to a thousand or so data points) + correlation (supported by a couple of experimental observations) + causation + verification (either independent confirmations or a couple of prediction tests). Weak Confidence

Strong Hypothesis = Weak Hypothesis + large volume of confirming experimental data (tens of thousands of data points) + correlation supported by significant independent experimental observation (in the order of hundreds of) + verification (peer review and and hundreds of prediction tests).  Reasonable Confidence

Theory = Strong Hypothesis + significant volume of data (hundreds of thousands of data points) + independent verification of experiments (in the order of many thousands of) + widespread acceptance by scientific community + large volume of prediction tests (many thousands of). High Confidence

Universally Accepted Theory (law* in all but name) = Theory + so much data (many millions of data points) + so much independent verification (hundreds of thousands of independent experimental observations and predictions tests) that it has become universally accepted within the community, we've almost stopped asking the question and will be genuinely surprised if someone shows it to be wrong. Extremely High Confidence

* In the normal sense a scientific law is simply a description of observed phenomenon whereas theory is the explanation of those observed phenomenon e.g. Newton's Law of Gravity is not the same as the Theory of Gravity. However, I don't know an appropriate word to describe a universally accepted theory, the temptation is to call it a 'law' except that creates all sorts of other confusion. So, I'll simply note that there are categories of theory which have become universally accepted. 

** I refined this list on the 17 August 2013 to give some examples of volume of data that I'd expect to see.