There are two main areas I wish to discuss: -
- A highly predictable change in terms of “What” i.e. the commoditization of a pre-existing activity. For this I will use 3D printing.
- A highly predictable change in terms of “When” i.e. the impact of cloud computing in enabling an age of wonder and the development of intelligent agents.
I will avoid the general discussion on the genesis of the novel and new which is both unpredictable in terms of what and when. I tend to cheat with my predictions, using pre-existing trends.
What not When
I have had a long history with 3D printing, having written my first research report on the subject in 2001. I’m not going to concern myself with the mechanics of additive manufacturing techniques and the potential for hybrid printing of both physical and electronic structure, as there are now many works that cover this. I will instead concentrate on the consequences of this change.
First, 3D printing is part of a range of techniques that cover the commoditization of the manufacturing process itself i.e. factories are shifting from being custom built environments that consume large numbers of products to more digital environments that use increasingly commoditized methods to create objects. 3D printing is best thought of as part of the digital factory and in some cases this will be used in the home and in others in large scale manufacturing environments.
The impacts of 3D printing (and the related technologies such as printed electronics, hybrid printing) will be the same as the commoditization of any activity. Hence we should see a standard set of consequences that I first wrote about in 2006.
These include: -
- Commoditization 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 but what those new things are and what new industries form, well we don't know yet because they're uncertain.
- 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 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.
- We will see a flood of capital from the past manufacturing industries to these new industries.
- 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. The growth in new practices of more “Agile Manufacturing” will result in a yo-yo between more unstructured and structured techniques, a manufacturing equivalent of Agile vs Six Sigma.
- The new practices will result in new forms of organization as per electrical age (Fordism), Internet age (Web 2.0), Cloud (Next gen) and every other age.
- At the height of this change concerns will be raised how commoditization of the manufacturing process will lead to mass unemployment etc. This will overlook every other example of the same phenomenon (Hawkins and the electrical age) and how each time we fail to anticipate the new activities (higher order systems) and related industries that will form.
- In a desperate attempt to save existing business models, 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 items like guns will be used to explain why this change is dangerous for us all and must be stopped. Furthermore Government officials pushed on by lobbyists will start to talk about the needs for certification of designers, architects and the like on the grounds of "consumer benefit".
- 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.
- Because of the reduced barriers to entry there will be a rise in competitors that were once former consumers
- The trickle of adoption to these new manufacturing techniques and practices will become a flood as the combined forces of efficiency (through commoditization of the activity), increased agility in building higher order system (componentization) and future sources of worth (Schumpeter) kick in. This will take everyone in the industry by "surprise" due to the previous “peaceful” phases of competition.
- As commoditization of the manufacturing process spreads and the explosion in higher order systems and new industries accelerates there will be a corresponding explosion in un-modeled data. This is data which we don't know how to model yet but will eventually be modeled as we understand it more.
- As hardware becomes more malleable like software, it will be realised 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.
- 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. 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.
- Google, Amazon and other “players” are likely to adapt quickly to the change and attack 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.
The above “what” is highly predictable though the exact “when” depends upon the actions of individual actors and is hence unpredictable. However, we can assume the above changes will significantly hit the manufacturing industry between 2020-2030 based upon the original predictions in 2006.
In the last seven years, we have already seen the start of this process gather momentum including some of the dark arts such as concerns over printing dangerous items.
When not What
In this section I wish to cover a change that we know will happen (in terms of time) but just not what it will entail. This change relates to the commoditization of IT to components provided as utility services and how it will enable the rapid creation (nee Genesis) of higher order systems.
We know that our industry is going to experience a time of wonder but due to uncertainty we don’t know what those new higher order systems will be.
We can however make a reasonable guess by looking at the common components that are now provided as more ubiquitous and well-defined utility services and extrapolate what possible higher order systems can form. By reasonable guess, I mean we can confine our focus to a specific area but it should be noted that this time of wonder is highly uncertain and so we don’t actually know.
I’m going to focus on a piece of work I presented in 2005 called “Any Given Tuesday”. This work described a future with more intelligent software agents that understood both my network of things, my routine, my continual “exhaust” of data and my relationship between other networks. The work highlighted two scenarios: -
In the first scenario, I wake up at 6:45 am, spend 10 minutes trying to find my watch, leave the house at 7:15 am, drive like a madman to the station, spend 30 minutes waiting for a train due to cancellation, get to London bridge at 9:15 am, get soaked because it is raining, rush to work missing my coffee, arrive at work 9:35, discover my CFO has been trying to call but I've left my phone at home, realise I have football today but no boots as I threw them away last week, my partner calls to remind me it's Mother's day and my Sister's birthday tomorrow - both of which I've done nothing about.
Overall: I'm wet, late, had no coffee, I've annoyed my CFO, I'll miss out on football and I've still got to work out what to do about Mother's day and my sister. I'm hardly in the best mindset for work.
In the second scenario, I wake up fifteen minutes earlier at 6.30 am, pick up my watch and phone that are on the kitchen table, leave the house at 6.50 grabbing an umbrella from beside the door, arrive at the train station at 7:10 am and catch the 7:15 am, arrive at Canon Street at 8:20 am, pick up pre-ordered football boots from the sports store, grab a coffee, walk to work putting up my umbrella when it starts to rain, arrive at work 9:15 am, tell my CFO the reports been done and when my partner calls explain that I've sent my Mother flowers and my sister has a new ipod which will be delivered tomorrow as her last one broke.
Overall: On time, dry, plus coffee, I'll be able to play football, mother and sister's presents are sorted and reports done. I'm in the right mindset for work.
Ok, so what happened between the two scenarios? Did I become Mr. Organized or learn the twenty-seven secrets of successful people? No, it's all done with technology and asking a few simple questions.
First, everything is tagged, everything is online and everything is a network. My network of things knows it's a Tuesday, how long it takes me to get ready and what things I need for work. It knows where those things are and the weather forecast. It can interrogate the train stations network to get times and cancellation information and it knows where I need to be. It knows I play football on Tuesday and that I threw my boots away. It knows I like to drink coffee and that its Mothers day tomorrow and that I bought flowers last year. It can ask my Mother's network what sort of flowers she has and whether anyone is buying her flowers? It knows it's my Sister's birthday tomorrow, it can ask her network for suggestions. It now knows she broke her ipod (remember this was written in 2005), that she hasn't replaced it and what her favourite songs are and where she will be tomorrow. My network knows my CFO was in a meeting where they discussed a new way of analyzing value from users.
My network of things can now, find a shop with the boots I need and pre-order, find a coffee shop and calculate a route to work to pick up both. Calculate time for journeys and dynamically deal with cancellations. Sort out ipod and flowers. Analyze the CFO meeting and determine most probable research to be collated and who to contact.
All it now needs to do is ask me some basic questions: -
- Do I want to buy some new boots for £35 so I can play football tomorrow?
- Do I want to send my Mother flowers for Mother's day?
- My Sister's ipod is broken, do I want to buy her a new one for her birthday?
- The CFO is after an examination of user spending patterns vs latency on the site, do you want me to prepare an initial analysis with the latest research on the subject?
Then it needs to calculate my journey and wake me up when I need to be woken up. This is what I called augmented intelligence and it likely to be provided through intelligent software agents that ask the questions and take care of the details. The agents will depend upon commoditized means of providing computing infrastructure, large-scale data analytic systems, extensive and modeled search and voice analysis, ubiquitous sensors and networks. Back in 2005, the capabilities were already there but it was economically unfeasible, the recent round of commoditization in IT is bringing many of these into reach.
In 2005, we could be sure that IT would enter an age of wonder (after the war) and intelligent software agents was a reasonable guess as to one of the higher order systems that were created. Today, we have MindMeld, Google Now, SIRI and EVI.
The Cycle of Change
The above demonstrates how examination in terms of evolution is not only useful for creating maps and competing with others but also for providing some level of forecasting over the future. Alas, such forecasting is limited to “What” just not “When” or “When” just not “What”. However, the use of weak signals and componentization can help narrow down the uncertainty to likely areas of probability.
We can already see what the impact of 3D printing will be (probably sometime around 2020-2030) and how a time of wonder will occur in IT over the next five years (probably involving some form of intelligent software agents).
Those newly created activities in the time of wonder will themselves evolve and eventually become a commodity initiating a new cycle of change in that industry. So, we can use these cycles to predict probable areas of interest well in advance.
However, the cycles of changes themselves are not linear but impacted by commoditization of the various means of communication. Whilst the evolution from Archimedes screw to standard nuts and bolt (brought on by Maudslay’s screw cutting lathe) took 2,000 years, the Parthian battery to utility provision of electricity was 1,400 years, the evolution of the first phone to telephony itself being a commodity was over one hundred years and computing infrastructure took a mere sixty years.
Whilst it is doubtful that we have become more “innovative” as a species (i.e. our ability to create the novel and new has accelerated), the speed at which things commoditize and the next cycle starts certainly appears to be accelerating. The printing press, postage stamps, telephony and the Internet have all accelerated the general rate of evolution of all other activities by increasing communication and participation.
So it is probably reasonable to say that along with being able to predict “What” not “When” or “When” not “What”, the one other thing that evolution teaches us is the cycle of change is likely to become more rapid.
Hopefully by now the reader is fully aware that things aren't quite as random as people make out and the importance of understanding evolution and mapping in competition. If so, well, I've done my job.
The END
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Post 27 on Management and Strategy series.
