This blog is all about innovation systems. It retains the initial focus on the international architecture of industrial clustering, industry definitions and the patterns of industry level 'business' models. However, my interests are also shifting to the next level of macro questions. How do these architectures operate within and shape the global economy? In what ways is technology and innovation the transformation driver of macro-economics?
The term dis-intermediation gets banded around alot in this early cyber revolution period but what does it mean and how can you show it.
So Wikipedia has the following rather limited definition of intermediation.
Intermediation involves the "matching" of lenders with savings to borrowers who need money by an agent or third party, such as a bank.[1]
If this matching is successful, the lender obtains a positive rate of return, the borrower receives a return for risk taking and entrepreneurship and the banker receives a return for making the successful match.[1] If the borrower's speculative play with the funds provided by the bank does not pay off, the bank can face significant losses on its loan portfolio,[1]and if the bank fails its depositors can lose some of their money if the deposits are not insured by a third party.
In fact with vision, and vision is needed here we need to expand the concept of intermediation to just about any scenario you can think of where there is an actor interposed between step 1 and step 3. So ingrained in us are conventional concepts of human work - most scenarios will not even look like intermediation - they only become so when digital technologies offer new possibilities.
So let us illustrate the concept.
Figure 1.
This gives us a basic template to see what happens when we change the dynamics of the economy.
At the highest level we can observe what happens to entire 'industry complexes' when a digital substitute marketplace is created.
Figure 2.
Pre-2000 there was a substantial industry constructed around music - agents, labels, studios, physical media manufacturing (records, tapes and then CDs) and then the retailers.
However, along came napster and later iTunes and what have we got left.
Fig 3.
What we see here is that Apple iTunes has dis-intermediated the music industry and re-intermediated music as well. It now offers a direct route for artists and traditional music industry operations must go through it to get to the customers. This process has dramatically shrunk the tradition commercial music complex.
Now we can apply this to any example. For example a worker driving a truck. Pre-2000 this idea that the driver is an intermediation point would be treated as complete nonsense - now not so much.
Fig 4.
Fig 5.
We can now move to a scenario when mining companies can dis-intermediate this value chain.
This may look dramatic and that is the point. This logic of dis-intermediation and re-intermediation is intrinsic to digital technologies and we had better start designing data around this concept to understand it better.
Just some musings today of future costs rather than benefits.
So as a follower of innovation studies and also a collector of serious attempts to look into the future it seems to me that one of the serious flaws in the way we bean count is to only focus on growth. It always seems that studies overshoot the future partly for lack of technical advance but partly because they undervalue the economics of the system. These dimensions are inextrricably link - make enough technical advance and the economics improve - however perhaps the upfront costs of that technical advance are too high to begin with.
It seems to me that in understanding this conundrum our national accounts have categories which are next to useless in the modern economy.
That blog immediately triggered so many tangential thoughts. Assimov's comments in the Foundation trilogy that as the Galactic Empire slowly collapsed it could not longer maintain its technologies.
Another was a throw away comment in the current U.S. 'great wall' debate about the cost of maintaining the wall. http://www.cnbc.com/2015/10/09/this-is-what-trumps-border-wall-could-cost-us.html includes an estimate of $750m - per annum for maintenance. If the wall cost $12b even without accounting for inflation you are paying for the equivalent of a new wall every 16 years.
Out of sheer curiosity I looked up the accounts of the local public transport body and it was hard to discern what their actual final maintenance costs are.
But let's just assume that gradually over time not only are our societies accumulating more infrastructure but that as technology is more fully embedded the costs rise.
How to read the image. As we rarely discard technologies entirely or when we do, we replace them with ever more complicated ones. So we add to the techno-system and rarely take away. If you read the chart vertically you can read it that past structures are past onto future generations. Roads build pre-1950 are largely still in use today as entities and locations although they have been upgraded in quality significantly. Therefore the pre-1950s column goes vertically upwards. In the pre-millennial period we started introduced significantly new and varied technologies and we currently stand on the cusp of IOT of things. The graph tries to take account of some efficiencies and productivity improvements from gains from embedded technology - but there will still be more of it.
So over time the costs of maintenance rise - but it is difficult to determine whether this is proportionate or disproportionate to the rest of the economy. We know that in the USA it is failing. In Europe where taxes are higher infrastructure maintenance is better.
Of course early on councils and governments will embed sensors on everything from water mains to roads - but here is the question - what will break first the sensor or the pipe. If it is the pipe how quickly will cash strapped councils replace the sensor.
With the current obsession with new technology - we only study the system around the production of the new technology - not the technology system itself. Oh and BTW costs are only one element - you actually have to have a techno-system that values education for the skills necessary to maintain the societal infrastructure.
Any regular or irregular reader of this blog will realise that one of the goals of this blog is to explore non traditional concepts and language for describing the economy and the relationship with technology. The dominant language at present is 'innovation' and the academic discipline is 'innovation studies. This is I believe to greater or lesser extent fostering confusion about the topic. Technology remains in my view a problematic entity in society and economics. Treating it like land, labour or capital I believe is not helpful because technology conditions and transforms the others. It is not simply a production variable nor something meaningful to count as X% of firms launched new products last year.
My principle concern is that there is a great deal of muddled language where technology and innovation are almost used interchangeably. Further, technology has been subsumed within economic growth studies and impact but surely it does more that grow the economy it bends its shape.
Technology is more than just one thing - it is many things simultaneously. It is our creation and therefore it can be studied like we do with nature - biology and ecology, as a single organism, with DNA - heritage and history. It can be studied in 'food webs' in relation to economic structure - supply chains and so forth. It can be studied within the ecosystem of other technologies of greater and lesser scale, scope and dimensionality. Back here http://econscapes.blogspot.ca/2013/08/macro-innovation-1-introduction.html I explored the idea that technology should be seen as an ecosystem that is interdependent and modifies the 'environment' ie. the linkages between other systems around it. That is one image of technology - but at the macroeconomic level it is not simple enough.
The idea of 'general purpose technologies" exists but has never really taken off, and there is Keven Kelly - technium which hasn't caught on either.
It is interesting that at this moment when 'technology and economics are now almost synonymous there may just be the start of a movement to go back to rethink technology.
Beyond Innovation: Technology, Institution, and Change as Categories for Social Analysis. By Thomas Kaiserfeld. New York: Palgrave Macmillan, 2015. Pp. 174. $67.50.Technology and Culture, Volume 57, Number 1, January 2016, pp. 244-245 Reviewed by Benoit Godin.
So onto this blog.
The latest concept has been playing in my head for a long time but received some impetus with the first measured gravity waves.
So here is another way to conceptise technology - as 'mass' in economic space time.
Space Time
I found this great youtube video of the space time concept. https://www.youtube.com/watch?v=MTY1Kje0yLgDan Burns explains his space-time warping demo at a PTSOS workshop at Los Gatos High School, on March 10, 2012.>
So what is Economic Space Time
Imagine if could measure all the dimensions that are important for understanding the dynamics of economies. Economies are not singularities that move through time - always essentially the same. What is made (incl services - everything), where it is made and how it is made changes radically across time - this we could call economic space time.
Naturally to understand economic space time we need to measure tot just income, but how people make their money, the production systems etc etc ... In short we would be able to then approximate the underlying 'technology' of the economy at particular points in time. But could we simplify this by looking at the 'waves' generated by new technologies.
Economic Space Time circa 1960
Put your mind back to the 1960s the US manufacturing economy was at its zenith - thousands of people were employed in factories. The big companies - resources and manufacturing employed many thousands of employees. I actually went looking for the numbers but they are hard to determine. If I can calculate some I will put them on this blog.
Economic Space Time circa 2016
So what about today. The top companies ( http://fortune.com/fortune500 ) are Walmart, Exxon Mobile, Chevron, Berkshire Hathaway and then Apple.
If we pick on Apple as the first company that makes products - yes I know petroleum is a product but not in the same way.
Apple has nearly 100,000 employees and an un-numbered 000s in its elongated supply chain which is a part of the modern economy. We also don't know how many people do contract work for Apple.
To make the point about supply chains even stronger, General Motors is no 6 on the list. Is has just more than twice the number of employees than Apple.
Amazon one of the born digital companies has 154000 employees.
JP Morgan Chase Institute recently released a fascinating report on income volatility and other information using big data analytics of JP Morgan Chase bank accounts. The most interesting reading relates to the platform economy participation.
Although 1 percent of adults earned income from the Online Platform Economy in a given month, more than 4 percent participated over the three-year period.
The Online Platform Economy was a secondary source of income, and participants did not increase their reliance on platform earnings over time. Labor platform participants were active 56% of the time. While active, platform earnings equated to 33% of total income
So at this point you are thinking - 1/3 of the income for 1 percent of adults, that not much in the scheme of things is it. And that was the view of The Economist
Such reforms, though, would be relevant to only a tiny fraction of the workforce. JPM’s data suggest that most ondemand workers use apps to supplement their income, rather than as a replacement for a fulltime job. On average, labour platforms provided only one third of ondemand workers’ incomes. And their participation was often sporadic; almost half of those who start working on a labour platform stop within a month. Earnings from Uber and the like are strongly correlated with negative shocks to incomes from other sources (capital platforms are used much more consistently). That suggests people use apps to smooth bumps in their earnings, which are frequent: more than half of JPM’s customers have seen their incomes swing by at least 30% in a month. Volatility in pay is largely responsible. Perhaps conventional jobs are not so great after all.
But just a moment
Just how significant is one percent of the labour force? Well.... As I have been reading through the report by JP Morgan Chase Institute I realise I need to read it much more closely as it refers to 'adults'. That is is a very much larger pool of people than conventional statistics of workforce.
For comparison in Canada 1.6 percent of employment by industry is in agriculture. A further 1.6 are employed in Mining. As a percentage of adult population that may drop a bit and we get closer to the 1 percent.
So when you hear only 1 percent are employed in the 'gig' or 'task' just keep in mind that number is bigger than you think.
So what is the point: 'technology waves'
When the steam engine was invented, enabling power and the factory system it changed the economy - not just grew output and productivity.
Today with the growing digitalisation it is obvious the economy is change shape again. This is not new it is in the papers everyday.
The point is no single way of understanding those changes not single language is powerful enough to capture the scale scope and significance of change and we should give up trying. Lets be heterodox is our rich descriptions of change.
