Today there is a big scare that bad people will run off with your intellectual property and make a ton of money with it. Another problem is that the Patent system is so slow and so expensive that the vast majority of innovators simply do not have access to patent protection – many people just keep their ideas secret. This happens in corporations where your ideas are used to advance the careers other people. Often the dominant strategy is to not innovate or keep your ideas secret.

The trend toward open sourcing and crowd sourcing is a real option in the Innovation Economy where Social Network are self regulating. In fact, these articles reference Wikipedia – a community source of definitions.

In practice, If I do dirty deals of Craig’s List, for example; people know where I live….or I get flagged. EBay, for example, produces relatively little to earn their 30B market cap except protect their social accountability system – the EBay feedback mechanism rewards high integrity and punished low integrity. The hallmark of the Web 2.0 is the user generated content as well as the user generated vetting of the content.

This is significant. The efficiency of any market is directly related to the efficiency of the vetting mechanism by rewarding high integrity and punishing low integrity; the FAA vets the airline industry, checks and balances vets democratic government, and the FICO score vets the consumer credit markets. Likewise, things go horribly wrong when the vetting mechanism fails; the accounting profession after Enron, and the sub prime mortgage crisis after loose lending practices, etc. The battlefields of business are littered with similar examples.

In an Innovation Economy, the secret sauce for the production of innovation is far more valuable than any single innovation itself.  The secret sauce provides a monopoly on dynamic repeatability rather than some static device. As such, patents can be open-sourced and innovation crowd sourced across a much wider domain of user applications.  Such conditions will change the type of innovations that are favored to reflect the broad and sweeping social priorities rather than innovations that are easy to patent, protect, and monopolize – and fear for one’s IP being stolen.    Bad people cannot steal your intellectual capital, your social capital, or your creative capital – it is yours, you own it and you have the social network to prove it.

Ownership is the key ingredient of entrepreneurship – everyone owns the innovation economy.

In fact, the objective of innovation economics is for people to take your ideas and make money with them – then give you some of it. Your income arises from collecting royalty payments on your ideas and participation of many ventures. If someone does not play fair, their access to intellectual property and the Percentile Search Engine can be curtailed just like access to credit can be curtailed in modern finance. Therefore, it is in everyone’s best interest to play fair; you may cheat, but only once.

Social Networks are largely self-regulating; no government, Industry, or management is needed. This is efficiency, scaleability, and multiplicity all in one!


If we combine the parallel transaction with the series transaction we have what now looks like a neural network. In practice, we know that strong networks of people freely exchanging ideas make organizations better, smarter, and more efficient. Networks are where knowledge and wisdom is literally stored. A network is fault tolerant, if one person leaves, the network survives. For a relatively small input into a network, we can produce a large output of new knowledge – we have a learning organization.

However, in society, these interactions are largely accidental; people meet at Church, Starbucks, and Social Events or by word of Mouth. Other times, these interactions are concentrated inside a single community of very similar people such as a technical conference, group meeting, or lunch buddies and are often not well diversified.

Suppose the interactions among people were not random, instead, they could be designed by the entrepreneur to produce a unique outcome. The Innovation Bank will combine people of complementary knowledge assets in a calculated manner in order to arrive at specific business approaches and applications.

A special case of the above business method and resulting social network is called the Multiplier Effect. A financial bank enjoys a multiplier effect with the ability to lend the 10 times more money than they hold in reserve. Money changing hands has a multiplier effect on an economy. Again, financial analogies hold.

Suppose that a company owns composite material technology for use on aircraft. Since they specialize in airplanes, they have no intention of pursuing other applications such as recreational equipment, energy production, or health care products.

Suppose that the company could deposit this asset in a bank and collect interest. The Search Engine can scan the business landscape to find companies with a knowledge deficit in the area of your technology and make loans of your technology. As the originator, you have the option to see what those other companies invent and you hold the right to use their new ideas in your aircraft application.

With an innovation Bank, you can reduce your Research and Development costs and create additional revenue in a tangential innovation market. With reduced cost and risk of innovation, you are likely to specialize more and more in innovation as your enterprise. In the event of a cyclic downturn in the business of an originator, instead of “laying off” knowledge assets, people can work in tangential industries where they will continue developing – literally putting “Knowledge in the Bank” – to be called back when market conditions improve. A mobile knowledge asset increases in value becoming smarter and more productive over time.


So now, what are the entrepreneurs going to do with this percentile search engine?

Entrepreneurs wander the earth looking for valuable things that are being used at a low level of productivity and they move those assets to a higher level of productivity and then pocket the difference, called profit.

Think pet rock, condo conversions, sand, corn, etc.,…it goes on forever.

The entrepreneur needs to have a clear view of what the asset is, the lower level of productivity, and the higher level of productivity of the asset. These three elements are the focus of all business plans. Then they set things in motion and give life to the market system.

When we look at financial banks we see the classic entrepreneurial activity. In the simplest form, banks do little more than find people who have a surplus of money and they match them with people who have a deficit of money.  Bankers have a clear view of the asset, the lower level of productivity and the higher level of productivity for the asset.

They pay a lower interest to the depositor than they do to the borrower and pocket the difference. In addition, they enjoy a multiplier effect that allows them to lend the same money many times effectively creating money from a promise to pay, or debt.

It is in the best interest of the bank to find rich people who will not need their money for a while, and poor people that have the best likelihood of paying the money back in time. This is to minimize the risk that the depositor will pull out their deposits and the risk that the borrower will not pay back the loan. The problem is that some assumptions need to be made, some of which may no longer be valid:

The bank assumes that the borrower has the knowledge required to execute the business plan that they are financing. Unfortunately, the credit score does not predict knowledge on future ventures.  For this reason, new ventures are not easy to finance.

The financial bank makes the assumption that the entrepreneur has the knowledge to execute a business plan that they seek money to fund.

On the other hand, the Innovation Bank makes the assumption that the entrepreneur has the money available to execute the business and is searching for the knowledge to do so.  This service will be required in the innovation economy since no single person can live long enough to possess as much knowledge as is required to manage the complexity of problems that face the World. We will need to mind meld.

The Innovation Bank simply matches most worthy knowledge surplus with most worthy knowledge deficit and a market is born.

The challenge for the innovation Bank is to match the most correct knowledge surplus to the most correct knowledge deficit. This is accomplished with the computer enabled knowledge inventory. A search can be conducted of the supply and demand for knowledge assets. The Percentile Search Engine will calculate the probability that the specific business objective will be successful.

The business plan for the entrepreneur is very simple but the implications are vast.


The Percentile Search Engine is a way of using a computer to make predictions about all types of combinations of knowledge Assets.

Conceptually, the percentile search engine is where all of the equations that we use to analyze financial assets are now applied to knowledge assets. The main characteristic is that the Percentile Search Engine returns probabilities – that is, what’s the probability of success for any number of scenarios.

For example; an entrepreneur may want to know if her team has enough knowledge to execute a business plan. Maybe the team has too much knowledge and they should try something more valuable. Maybe the team does not have enough knowledge and they should find someone else, take training, or try something simpler. The Percentile Search Engine can look into the community and identify the supply and demand of a knowledge asset. If it is unavailable or too expensive, the Percentile Search Engine will even tell them what training they need to increase their probability of success.

The entrepreneur may also want to determine what competitors have a dangerously high probability of competing with her new business. The Search Engine will allow competitors to scan each other’s knowledge inventory to determine how long it would take for their secret sauce copied. They can take then choose to take evasive action, compete, or cooperate. If a key person retires, the entrepreneur would simulate the knowledge that is lost and reassign people strategically. All of these scenarios can be examines prior to spending money. They can be made during the project cycle, or after the project is completed. Lessons learned can be used to adjust the algorithm perfecting it over time.

While companies such as Disney and Boeing both use Engineers, each would have proprietary combinations of knowledge that represents their “secret sauce” of success. These recipes can be adjusted and improved to reflect the wisdom of an organization.

Over time, these algorithms will far more valuable then the Patents and Trade Secrets created by them – this will allow technologies to be open sourced much more profitably and shared across more industries.

Literally thousands of new business plans will emerge from this important new paradigm. Knowledge will become tangible outside of the organizational construct of the corporation. Knowledge combinations will become the new corporate structure. The rate of change of knowledge with respect to time is the key metric and fundamental building block of the innovation economy.


Now we look for a similar situation for Knowledge Markets.

In the cuurent times, the hiring manager is the person to know if you want to get a job. The manager would read your resume and compare it with “bell curve” in their brain about what has worked or not worked in their past. This was a great system for the industrial economy, but it falls far short in the innovation economy.

The world is evolving so fast with new technology, new disciplines, and global cultures that what worked in the past may not work in the future. Innovation favors different combinations of knowledge where the Industrial economy favored similar knowledge. A hiring manager may not accumulate sufficient experience in a lifetime to make a proper assessment in the complexities of a diverse, global, and technical future market.

If we look in society, there are many vetting mechanism in place. Social networks are by far among the most exciting and important new technology that can serve this purpose. Social networks must now evolve to become a local vetting mechanism for knowledge assets.

Just like the reporting agencies in the credit system, Social Networks can serve an extremely valuable function in permitting human knowledge to emulate a financial instrument by acting as the “Recording Agencies” who have verified the asset in terms of quality and quantity. The knolwedge Inventory acts as the independent variables that are used to calculate the probability of market success. The difference is that the credit score measures mostly negative events while the new system will seek only positive events and can be designed to give the participants much greater influence on how they appear to the market.

One thing is missing. The credit score uses the FICO equation; Innovation Economics will use something called the Percentile Search Engine.


We have defined the currency, the factors of production, and the inventory of the Innovation Economy; we destroyed the old resume system and turned it into a computer language that makes knowledge appear like money in the eyes of the entrepreneur.

Now, we need a system that keeps the game free and fair. For example; EBay does little more than protect the feedback system, Craigslist uses community flagging, Linkedin keeps track of comments and contacts, etc. All markets must have a vetting mechanism in order to operate efficiently. Entrepreneurs do not invest in places without a good legal system and where property rights are not protected. When vetting fails, investors leave – It is that important.

In the Innovation Economy, the knowledge market is analogous to the credit market.

In the old days, the banker was the person to know if you wanted to be successful in town. If you needed to borrow money to start a business or buy a house, the banker would review your work history and financial records as well as your reputation in the community where you both live. If you were deemed an acceptable risk, the banker would lend you money from the deposits of local companies and individuals.

Then an engineer named Bill Fair and mathematician Earl Isaac created the first behavior scoring system to predict credit risk. They formed the Fair Isaac Corporation FICO and their invention came to be known as the FICO credit score. With the credit score, the local banker is almost irrelevant; now a Saudi Billionaire can lend money to a young couple in Boise to buy their first home – and neither of them are aware of the other. The credit score is responsible for the creation of a lot of wealth because it made many more entrepreneurs who invested borrowed money in business. The credit score even allows you to recover if you hit hard times – you just pay more a little interest until you prove yourself solvent again.

The credit score isolates about 22 or so measurements of financial activity and puts them on a bell curve relative to everyone else. These include how much debt you have, how much your assets are worth, your income, etc. These ratings are run through the FICO Equation and out pops your credit score. Anyone can now predict the likelihood that you will default on your obligation.

All of the data that feed FICO are collected from public records, your employer, and the people who you borrow money from – all of these organizations have a vested interest in a system of correct credit scores.

It is interesting that you and I do not compete for our credit score because it is not a ranking system. The old saying “No credit is worse than bad credit”, although inaccurate, is cited often because with bad credit, you are visible to the system and it can adjust to find a suitable interest rate. With no credit, you are simply invisible.

We lose some privacy with FICO, but we accept these terms well because they provides us with tremendous benefit to finance a business, automobile, or a home without needing to save cash. Likewise, we lose some privacy engaging each other on the Internet and in our community, however, the benefit of Social Networks far exceed many perceived privacy issues.

My personal complaint with credit scores is that they track largely negative events and seem to predict failure. What if we had a system that tracks success and used that data topredict varying degrees of success.

In the next section, we will identify the institutions that exist in society and how Social Networks can act to duplicate the benefits of the credit score without the downsides….watch


In American society there is a persistent ideology of winners and losers; there can only be one winner and the rest are losers. We rank things in a very linear way; 1st, 2nd, 3rd, etc. Sports analogies dominate many business expressions; low ball, hail mary pass, ball’s in your court, etc. Our culture is to protect one’s position at all cost, shield away all attackers and decimate our competition. This way of thinking was effective in the industrial economy but today with the emergence of social networks it keeps us from understanding how knowledge actually exists in a community – it lives on a bell curve.

The Bell Curve
The Bell Curve

If I examine a group of people on the streets of Seattle in the area of mathematics – I would get a bell curve. If I examined engineering school students in mathematics, I would still get a bell curve. If I examined engineering professors, I would still get a bell curve.

In the Innovation Economy, there are no winners or losers, only different markets. There is a perfectly legitimate market for a Ferrari and there is a perfectly legitimate market for a KIA – in fact the market for KIAs is bigger than the market for Ferrari, so the idea that we compete with each other may no longer be appropriate. In fact, according to game theory priciples, it may not actually be the best strategy to be number one in a single talent – rather, being slightly above average in many diverse talents, on average, pays more for the majority of people engaged in innovation economics.

This is important. All of the tools, methods, and equations in the world of banking, finance, and insurance use interpretations related to this type curve when they try to figure out the value of an asset in the particular market. This is very important for making knowledge look and behave like money. Again, there are no winners or losers, only different markets.

We will need to come up with a way to sample and normalize knowledge in a community. In some ways we already do: Ebay uses a rating system, we rate comments on blogs, best answers to questions, Google placement, number of contacts, college GPA, credit score, etc. So rating are everywhere – there is nothing new here.

Here is what we need to do to make knowledge tangible in a community: when a local community of practice meets, everyone needs define the knowledge that the community shares, then everyone needs to find their place on the right bell curve. Each specialty and proficiency level is a different market. For example, a photography community there may be some competition for who can operate a camera better – but there is competition anyway. The competition disappears when one photographer is also a musician and nature enthusiast while another is also a baseball player and likes political contests. They would each own a unique market; still life and action respectively – and they can now cooperate instead of compete.

In fact, rather than fighting for first place by beating up your competitors, the best strategy in a market may be to have an average level of expertise in as many subjects as possible rather than being the best at one or two obscure areas. It depends on the market – it always has and it always will.

An entrepreneur will not make a bet without odds. We are giving the entrepreneur the information that they need to create wealth. Again, There are no winners or losers, only different markets.


Suppose we used the Dewey Decimal System to write a resume. A person could be described as a series of numbers instead of words and computers can search the numbers as they do key words today.

For example: 302, 307, 330, 607, 17, 500, 519

This person has experience in social interactions, communities, economics, educational research, ethics, natural sciences, statistical analysis

While memories of high school librarians may make us cringe, the computer loves numbers and classifications in this format. This will be important especially where knowledge is very specific. However, this simple list of numbers does not capture the knowledge of a person any better than the flawed “key word” search system that we are trying to replace. So we need to do something more.

If your mind were a library and you attempted to map it all out, one would see that everything is related in some way – intuitively, this is what defines you. If we looked at your brain, we would discover a huge network of experiences, relationships, books read, lessons learned, and people encountered. We would find a system of knowledge rather than random facts. Your likes and dislikes would be reflected in what you do and do not want to do. Everyone is different – nobody is the same. Everyone innovates, everyone has knowledge, and everyone shares information.

Somehow we need to reflect this on our computer readable resume.

The Universal Decimal Classification (UDC) System was built on top of Dewey for precisely this reason, to catalog complex and dynamic knowledge. The UDC system uses symbols to connect and relate the categories.

• Addition (+) allows for a string of subjects to be listed together.

• Forward slash (/) defines a range – or a “system” of subjects matter.

• Colon (:) identifies categories that are related like; sports and medicine, ethics and law; innovation and economics.

• We can even employ Boolean Operations such as IF, AND, OR, NOT statements. For example; we can say Polo IF Horses NOT water OR trade marks

• In a Global Economy, we can employ language and culture assets as well.

Now, we have a system of numbers and symbols represent the knowledge of the person.

For example: {20,12};[302+307], (330):[607+17]+[500/519]

Now we see that a computer language is emerging for human knowledge. This “resume” is for a specialist in Social systems and communities of practice. Knowledgeable in economics related to educational research, ethics, and natural sciences. They also employ statistical analysis in their work and can do it all in either English and Spanish

This is starting to demonstrate several key advantages:

1. It is Infinite and expandable to any field of knowledge
2. Paints a picture of knowledge not simply a list of information about a person.
3. Machine programmable and machine readable.
4. knowledge of several people can be combined to represent the knowledge inventory of a team, group, or company

We are getting closer to the elusive true “Knowledge Asset”. Part 3 will demonstrate how knowledge can be made to look like a buck, walk like a buck, and quack like a buck.


We identified the 5 essential elements of a market economy. Then, we discussed the currency of the Innovation Economy; people trade information and turn it into knowledge and new ideas using factors of production; Intellectual Capital Creative Capital and Social Capital. Now we’ll discuss the inventory strategy for knowledge assets.

Most companies have an inventory of every nut, rivet, or panel that they need to build something of value. Innovation Economics will be no different – we need an inventory of knowledge in our community so that we can build things with it.

Google and Wikipedia offer us a huge inventory of information – we read that information and turn it into knowledge through a mental process. Since knowledge can only exist inside people, we need a catalog of what people know. Our Knowledge inventory must be able to catalog and classify all human knowledge from the past, present, and future. It must account for Intellectual Capital, Social Capital, and Creative Capital. If done correctly, our knowledge inventory will begin to take on the characteristics of assets – knowledge will look like money.

Suppose that we say your resume is like a book about you. This isn’t too strange since every book that you have read has become part of your knowledge inventory. Every conversation with another person has become part of your inventory. Every new idea that you have tried, successful of failed, is part of your inventory. The things that you like to do, things that you do not like to do, and things that you do not know are part of this inventory as well.

The Dewey Decimal System is a way to catalog information. Even though Dewey is somewhat archaic, it provides a good example of how a knowledge inventory should be structured. Entrepreneurs will improve it if needed – so let’s just understand the concept for now.

For a quick review, the body of written information is divided into 10 main categories. Each main category is divided into 10 more categories and each of those are divided into 10 categories – and this can go on forever. For example, the term 519 identifies a piece of information. The main category is 5 = natural sciences, sub category is 1 = mathematics, and the next sub category is 9 = probabilities. So to have the number 519 on your resume says that you have knowledge and can solve problems related to probability and statistics.

You will also notice that some Dewey categories favor Social Capital, some favor Creative Capital, and some favor intellectual capital. While a knowledge inventory may sound daunting, computers and modern Internet applications can now do much of the work for us – in fact, they already are doing this work.


Every time humans invent better ways of doing things, the economy gets a little bigger. This is a simple idea. The cave dwellers discovered that they did not have to travel as much hunting and gathering if they could sharpen a rock enough to chop a tree down for firewood or for spearing animals.  That same tool helped them to dig holes to plant seeds.  By growing food and domestication animals, they could stay in one place and conserve energy.  By living in cities, the division of labor led to more efficiency as the farmer, metal smith and rancher bartered their services.  Enough surpluses were created so that a leisure class was free to develop philosophical thought leading to early scientific principals.

After a while, the invention of the printing press greatly advanced the availability of formal education.  In the Early 1800’s, Eli Whitney stunned the world first with the cotton gin and then with his concept of “interchangeable parts” where he disassembled ten working muskets, scramble the parts and reassembled ten working muskets.  What seems trivial today lead to great advances in the industrial revolution, becoming further refined in the manufacturing economy.  Computers then ushered in the Era of Information followed by the knowledge economy that we live in today.

At each stage, there was a quantum leap in human productivity and financial wealth.  Obviously the two are related.

If we look at this history from the big picture, we notice that each level of human development was derived from the prior level by integrating the tools of that prior level.  As such, the knowledge economy was derived from the information era by integrating the computer tools leading to the Internet.  The agrarian economy was derived from the hunter-gatherer tribes by integrating the wheel, wedge, and lever into agriculture and livestock.  The industrial revolution integrated scientific principles from the Renaissance. This is fairly consistent.

If we look at this history from a microscopic view, we see that no single idea drove human development, rather, billions upon billions of little ideas from many diverse sources combined in unique ways to form larger ideas which then combined to form even larger advances eventually leading to those big innovations that we see as the milestones above.

Also, we notice that the over time, rate of change at which these ideas have been combining is getting faster and faster.  The hunter-gatherer phase lasted 2 million years, The agrarian age lasted about 40,000 years. The scientific revolution lasted 1500 years.  The knowledge economy is barely a single generation in play.

These are important concepts because later, when we build a mathematical model for the next economic paradigm, we will use a few tricks of calculus called the “derivative” and the “integral” to describe how things change over time so that we can measure and analyze productivity and wealth creation in the new economy.

Finally, we ask, what comes after the knowledge economy?  There are two things that we can be certain of.  The next great leap in economic development will be derived from the knowledge economy by integrating the tools that we developed in this knowledge economy.  I strongly suspect that computer enabled society – or social networking will have something to do with it.

Welcome to the Innovation economy.