Introduction – A Quick History Lesson

Let’s take the short and hopefully not revisionist view of post-World War II US Growth. Capitalism was on the rise. US security saw its longest period of domestic peace with social unrest. For the first time in world history, the global population doubled in a lifetime. To keep up, quantity became more important than quality. Fast and cheap became the new craze for food, clothes, and other staples.

The landscape changed as well. The 1950s immediate post-World War II style explosion paused appliances, furnishing, flooring, and facades that followed mass production from factories. This made it easier for general contractors to build in suburbs to support the 4.2-person and .7-dog nuclear-family household. Thus, the construction of well-thought-out integrated-system buildings took a back seat. In their place, we had rapid urban construction needs due increasing population growth of the new rapid build-out siloed house.

So What?

This residential building model continued into the realm of data and computers. The initial computer and library science-driven efforts to create robust, integrated solutions to build knowledge systems took a back seat to reduce costs. Also, automating rote tasks such as filing, approvals, and workflow, led to the implementation of Management Information Systems (MIS). Data centers were popping up everywhere and quickly told they were going too fast. Subsequently, the stick (instead of the carrot) was put in place by the CFO/Accountants to utilize the cost center model for computing centers (e.g. charge per computing time use). 

The Brooks Act, which forced the US federal government to consider competency, qualifications, and experience rather than price, provided the momentum to move IT as a Service to IT as a cost center. IT Marketing took over as well, as data designed to build knowledge took a back seat to efficiency solutions brought on by Moore’s law and its amazing capability to automate and lower costs. Data Centers and MIS took over as capitalism’s backbone. Knowledge solutions in experiments would remain in research for a long time as computing power, algorithms, and data to support was in the long tail.

This Is How It Has Been In Buildings And Computing Ever Since. But, Times Are Changing…

US population growth has slowed. Without immigration to the US, organic growth shrunk as well. More attractive factors are needed to spur new construction market growth as real estate has become more compact and costly. To top it all off, Moore’s Law has been challenged for the first time in 60 years and seems to be decreasing.

Currently, the population growth in the U.S. slowing down. The country has taken a slower pace on the development of sprawling city centers, late 90s McMansions, and expensive-to-commute-to and provide-energy-for-prison-looking corporate centers. This has caused a shift to LEED-certified new or refurbished buildings that have modern or rustic styles. Call it irony, nostalgia, Pleasantville 2.0, or simply the last era to have design and architecture as its core. It is clear in the new urban landscape, that integrating eco, energy, water, air, structural, and vocational systems into structures and urban planning is making its comeback.

Changes In Industry And Its Effect on Knowledge Solutions

Industries similarly challenged Moore’s Law. For example, MIS efficiencies are now turning on themselves. Also, with additional computing power, the movement and storage of data are at the point of supporting knowledge-based questions, and knowledge solutions have a chance to become mainstream again.

Amazon played with this concept first in the public sphere with the early 2000s personalized search engines. Though Amazon questioned if they could financially survive the dot-bomb, with their first business data center shifts to a Service Center model Amazon was able to create Amazon Web Services (AWS) and was first to market with the easiest “pay $10 for a couple of hours of high performance computing”. They saw this opportunity and capitalized on the market needs, and now capitalism is experimenting with more advanced sensors and smartphones. For example, such sensors and beacons could send ‘just-in-time’ coupons because they know you are in the clothes aisle. Currently, there are 5 top players in Artificial Niche Intelligence of Personal Assistance solutions: Apple’s Siri, Microsoft’s Cortana, Google Now, IBM Watson, and Amazon Alexa.

But Here’s The Thing…

The question is, will it take 1-2 years or 5-10 years for the capitalist ecosystem that IT has built as a MIS Cost Center to shift to Knowledge solutions? If MIS can solve the security and network bottlenecks, then the shift will happen sooner. Due to the US geographic size, the US broadband network build-out is way behind other countries. If Wireless 5G can speed that up, we could gain some talent back on the knowledge side. If security can adopt a self-healing and impact-reducing approach instead of a risk avoidance and contingency approach with expensive standards, then the security impact could decrease(currently the cost of being hacked is still too expensive).

Security is the biggest risk though. It continues to be, every time IT has a new efficiency advancement. For example, the cloud brought ants, quantum computing brings the thread to easy 128-bit cracking, and the internet has brought anonymity and easy social engineering. Sure, knowledge solutions will be an awesome new wave. However, it will bring a greater threat because of how the baddies use it. Just like how more cars means more congestion.


Oddly, Transportation went through a similar, but shorter cycle post World War II. Highway expansion projects were almost complete. Also, the one-car per adult model was adopted during the baby boom growth. However, that changed as the infrastructure was built on a high dependency on external unstable markets (aka foreign oil). It quickly shifted to cheap and unsafe. At least, until the late 80s accident to fatality rate shot up. Consequently, cars from the late 90s became more safe and economical. 

The railroad/train industry increased safety greatly through its integration of sensors throughout its network. So much so, that areas without it are seen as barbarically outdated. Transportation has a chance to lead the way in domesticating knowledge solutions with intelligent transportation solutions. These solutions address hundreds of applications to help with congestion, safety, adjusting speed zones, car-to-car communications, environment, increasing transit services efficiencies and cost/passenger, collision avoidance, asset management, emergency response, and weather road network response.

A Return to Knowledge Solutions

Back to knowledge solutions, it’s clear to folks in LA, DC, NYC, Chicago, or anyone at 5:15P in an urban center, that the transportation solution today is nowhere near where it needs to be. Smart City concepts are still taking their time after 20 years. The data, approach to sensors, algorithms, and rules to make the systems smarter, social adjustments to rules, and capital investments in assets to adjust to rules, will all take a generation. Same with knowledge solutions in other industries. 

Watson winning Jeopardy was a great proof of concept. It was also a coming out announcement that early phases of knowledge solutions are scaling. How long until we can stabilize will depend on our capability to shift our time, investment, and foresight. This helps us understand what data we have, can exploit, can get more of, and can get better quality. Then use the technologies frameworks coming out to our advantage – and hopefully well before the baddies.