We call this wisdom
In the old days, the hiring manager was the person to know if you wanted to get a job. They would read your resume and compare it with the “bell curve” in their mind. This bell curve contains a statistical sample of all similar situations that the manager has witnessed, the variables involved, and a range of outcomes observed across their long and illustrious career…Ohhhmmmmmm
We Call This Simulated Wisdom
Modern HR systems try to simulate this wisdom through a series of innovations such as key word search, structured interviews, personality tests, and employee incentives. Now we can use Google (an information company) to derive sort of a proxy for wisdom as we assess search results in our own image. Facebook and Linkedin go a step further by providing us with another filter through which to pass judgement upon a future employee or partner. The problem is that the more we look into these systems, the more they deliver back to us a reflection of ourselves…Ohhhmmmmm
The Data need to be Normalized
The world has become so strange, complex, technological, and interwoven, that no single person can possibly posses such a vast and broad set of experiences as to arrive at an optimized outcome every time. Innovation favors strategic combination of diverse knowledge unlike the Industrial revolution which favored identical packets of similar knowledge. The Innovation Economy will require a completely new approach to social value creation.
The Social Credit Score
Not unlike the FICO score, the knowledge inventory is a collection of potential knowledge events where the social network is a reporting agency that has a vested interest in meaningful knowledge events. Unlike FICO however, the variables for knowledge can be infinite (think of the Dewey Decimal System). Also, a Social Credit Score would respond to positive events rather than a finite set of negative “hits”.
The Percentile Search Engine
Instead of just returning information, this new search engine must return probabilities from which an entrepreneur may test scenarios related to the likelihood of executing a particular business process at a known time, cost, proximity, ROI, etc.
Example
Innovation Economics
An entrepreneur may want to know if her team has enough knowledge to execute a business plan. Perhaps the team has too much knowledge and they should try something more valuable. Maybe the team does not have enough knowledge and they should attempt another opportunity or accumulate training.
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