My friends David Witkowski and Martin Casado have talked about the adoption of technology in culture and society. The graph shows how long it’s taken for many technologies we take for granted to become common place.
While this graph is for the United States you can see similar technology adoption lifecycles for other countries if you travel a lot – you notice some technologies are even skipped. Wired land based telephone lines, for example – not something you’d expect to see. Most new households simply use their cell phones.
David wrote a great article about how over-regulation in California is forcing new tech and companies like Uber’s self-driving cars to move their business elsewhere such as Arizona – Read it here:
For many of us it’s the new technology of the day that defines us.
Diffusion of Innovations – economics of SDN NFV
Martin Casado spoke at the NetEvents Cloud Innovation Summit keynote on March 27th, 2014 about “How the Hypervisor Can Become a Horizontal Security Layer in the Data Center”.
- Alan Weissberger has a great blog post on Martin’s talk here: http://ht.ly/vJZZO
- YouTube has a video of Martin’s talk here:
Security will never be the same again. It’s a losing battle. 40% of SDN adopters paying money for SDN network virtualization are doing it for a security use case implementing micro-segments on a per app basis overcoming the traditional limits of vlans and hard wired firewall policies.
One of the main take-aways I liked from Martin’s talk was his “Technology Adoption Curve” showing the five steps for any new data center concept. This is what a typical CIO is now going through when learning about Virtualization, Cloud, SDN, and now NFV on their path to the SDDC.
- Science Fiction
- Let the crazies go first
- Help me understand
- Get me into production
When researching for this post I found that this is related to the economic theory “Diffusion of Innovations” and the “Logistics Function”.
I wonder – where are you now in this adoption curve? What category is your organization in:
- innovator – willing to take risks with financial resources help absorb failure
- early adopter – new technology will help them stay competitive
- early majority – above average social status yet lack opinion leadership
- late majority – typically skeptical about innovation
- laggard – aversion to change and focused on tradition
With successive groups of consumers adopting a new technology (shown in blue), its market share (yellow) will eventually reach the saturation level. In mathematics the S curve is known as the logistic function.
A logistic function or logistic curve is a common special case of the more general sigmoid function, with equation:
where e is Euler’s number (approximately equal to 2.71828). For values of x in the range of real numbers from −∞ to +∞, the S-curve shown above is obtained.
The logistic function can be used to illustrate the progress of the diffusion of an innovation through its life cycle. Historically, when new products are introduced there is an intense amount of research and development which leads to dramatic improvements in quality and reductions in cost. This leads to a period of rapid industry growth. Some of the more famous examples are: railroads, incandescent light bulbs, electrification, the Ford Model T, air travel and computers. Eventually, dramatic improvement and cost reduction opportunities are exhausted, the product or process are in widespread use with few remaining potential new customers, and markets become saturated.
Logistic analysis was used in papers by several researchers at the International Institute of Applied Systems Analysis (IIASA). These papers deal with the diffusion of various innovations, infrastructures and energy source substitutions and the role of work in the economy as well as with the long economic cycle. Long economic cycles were investigated by Robert Ayres (1989). Cesare Marchetti published on long economic cycles and on diffusion of innovations. Arnulf Grübler’s book (1990) gives a detailed account of the diffusion of infrastructures including canals, railroads, highways and airlines, showing that their diffusion followed logistic shaped curves.
Carlota Perez used a logistic curve to illustrate the long (Kondratiev) business cycle with the following labels: beginning of a technological era as irruption, the ascent as frenzy, the rapid build out as synergy and the completion as maturity.
Everett Rogers’ studies of technology diffusion have a direct application to the examination of Internet use. He describes the time-phased movement of adoption and adaptation in terms of an “S-curve,” which describes a slow initial rise over time, followed by a more rapid acceleration and finally a slowing toward steady state. S curves show the rate of adoption for six technologies in the US, beginning with telephone, followed by radio, television, cable television, VCR, Personal Computers and Internet. Telephone rises slowly. Radio, TV, VCR and Internet rise very steeply. TV seems to have risen fastest, and, like phones and radio, has achieved almost 100% diffusion. (Internet is unlikely to achieve this 100% saturation as rapidly since about half the remaining non-users in the US have declared themselves uninterested in joining the Internet.)