Think Bigger. Aim Higher. Go Further.

Tag: networks

Social Currency And The Innovation Bank

'Innovation and Growth, Chasing a New Frontier' book launch(2)The real estate market is trashed, money markets are unstable, commodities are in the tank, the banking system is corrupted to the core, inflation is looming around every corner, and the politicians are engorging themselves in a game of Cerebral Gridlock.

Literally, there is no safe place to put your money. Instead, people are investing their productivity in social media – social media is simply a storage device for knowledge assets. Soon it will become a stock exchange for knowledge assets. Investors should not take this lightly – the best place to store your money is in the real productivity of real people.

People are trading knowledge assets in social media. This exchange is denominated by a conversational currency. If we consider the structure of conversations and compare that to both the structure of social networks AND the structure of our financial system, we see a huge opportunity to develop an alternate financial system that can capitalize and securitize knowledge assets in social media.

Music by Phil Felicia

Tangible Knowledge; Options and Contingencies

In order for knowledge to become a tangible asset, we need to come to grips with the fact that human knowledge is fluid and mobile, whereas a condo or a piece of machinery is static.  A machine can’t walk away if it does not like their management.

With knowledge assets, the typical “Return on Investment” (ROI) model breaks down.  When assets have a mind of their own, there is no reliable way to calculate ROI without somehow corralling the asset inside some form of closed contract, a corporation, political system, social class, or by introducing barriers to exit, etc.  In the modern financial system, human assets are held tangible by debt obligations – today many people go to work in servitude of debt, not in creation of new ideas.

An option* is the right, without the liability of obligation, to exercise a decision in the future.  Human interaction accommodates this valuation model quite readily; it’s called free-will.  Therefore the option valuation model is an adequate method to assess knowledge assets as a means of making them tangible.

The value of a financial option can be calculated if one knows the following 5 variables: The asset price, the strike price, the date of maturity, the risk free interest rate, and the volatility – or, the odds on the bet.  By contrast, the ROI model requires us to know basically the same things; the cost today, the strike price (future sale price), the date of maturity, the risk free interest rate, and the probability of success – or variance of the expectation.  The equation is just a little different.

Individually, human behavior often appears chaotic and irrational, but in aggregate, we know that human behavior is really quite predictable.  If you put similar people together, you get similar ideas.  If you put extremely different people together, you get extremely unpredictable ideas.  If you put strategic combinations of people together, you should be able to predict the variance of the ideas.  This is all the information we need to place a value on our bet.   If human behavior is predictable, it is tangible.

Suppose we enter into a ROI venture and it fails miserably; the market was wrong or the product was wrong, or the people were wrong, etc.  Even though the investment failed, the knowledge accumulated from the attempt can be exercised in many other projects in the future. While the Patent may turn out to be worthless, the knowledge gained by the team can be used over and over again.  Each person gains a statistical data point in their experience set with which to assess comparable situations in the future.  This is an option and this option has value.  If the team were disbanded without somehow capturing the inventory of new knowledge assets, a very valuable set of options becomes squandered.

Some companies such as Google, try not to kill an idea, they morph the idea into something else.  Free-range knowledge tangibility must achieve those same objectives.  Today we see people building networks on Linkedin – this activity resembles the collection of options on future opportunities.  People post on social media to see and be seen by other knowledge assets as a means of collecting more options for their careers or actions. People would not be doing it if there was no intrinsic value.  The next big leap will happen when knowledge tangibility is married to the financial system through the direct valuation and capitalization of options.  Did I mention there is an equation for that?

The Ingenesist Project specifies a method and system for knowledge inventory that would produce a variance for knowledge assets.  The Percentile Search Engine would pull knowledge assets in combination that diversify variance into a highly predictable surplus assets and deficit assets.   The Innovation Bank would match most worthy surplus to most worthy deficit.  As such, the Innovation Economy itself is now a most worthy option for supporting a feeble financial system.

The ROI model is the mother of all squandered knowledge assets – the very same assets that are really purchased on a project, successful or not, are often willfully abandoned.  All of the parameters of an option valuation model can now be met with social media and The Ingenesist Project integration methods. Free-range knowledge assets can then be directly financed toward business objectives.  The idea of an innovation economy based on knowledge tangibility is well within our grasp technologically, culturally, and systematically.

Social media has an astonishing opportunity to integrate social, creative, and intellectual knowledge assets to trade that single most important part of the puzzle, tangible knowledge assets.  I suspect that this outcome will depend on whether these new tools are treated to an ROI valuation model or on an options valuation model.

* Italic used for clarity

The Credit Score Analogy; Part 2

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.

The Credit Score Analogy; Part 1

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

Powered by WordPress & Theme by Anders Norén