The Fundamentals of HyperNet

HyperNet is an innovation-optimized Internet.  There are five layers involved in a global knowledge working fix.  HyperNet is the final layer on these fixes.

The first layer is the tranformation of the social grid to a user-centric Internet.  See CLOUD, Inc. for a great explanation of what this is and how it works:  http://cloudinc.org/

The second layer is establishment of an electronic civic space.  Physical and virtual civic spaces have been decimated, especially in the U.S.  I think many tech companies are attempting to privatize electronic civic space assets by creating profit centers around them.  Personally, I think we need a '.pub' domain that is funded and built through corporate social responsibility programs, volunteers, and national governments.  I-Open is a great example of a civic space Internet and the kind of content that belongs there: http://i-open.posterous.com/

The third layer is to fix the mechanics of the copyright system.  Copyright is pretty much a global process

The Six Sigma Achilles Heel

This post will distinguish the key differences between Six Sigma/Kaiizen and performance consulting approaches and will explain why both are needed.

Both Six Sigma and Kaiizen were born in the manufacturing environment.  Kaiizen is more focused on improvements overall and Six Sigma is focused on the elimination of quality defects with a reliance on statistical analysis.  In a purist sense, both Six Sigma and Kaiizen methodologies operate in different ways within the same basic framework:

1. Describe the current process
2. Detect and measure waste or increase efficiencies (Six Sigma uses statistical method)
3. Identify improvement(s) to eliminate that waste
4. Implement improvement(s)
5. Measure the impact of improvement(s).

But in this context, it is extremely important to ask yourself a few questions like: "What are problems?  What is waste?  And what is inefficiency?  Your answer will determine the effectiveness of your performance improvement approach.

Since both Six Sigma and Kaiizen were born in the context of manufacturing or 'making/producing things,' both tend to see problems as production waste and/or production inefficiencies.  In a production context, waste is any unneeded step(s) in a production process and inefficiencies are any unnecessary cost in production processes.   Said another way, what step(s) are not needed to make the things you want to make and what money does not need to be spent in the process of making things you want to make?

Enter performance consulting.  While performance consulting is typically associated with training, it is really the science of solving any performance problems—and training is only one of many interventions that solve performance problems.   In my personal approach to performance consulting, I delineate five categories of performance: 1) thinking, 2) knowing, 3) saying, 4) doing, and 5) enabling.  2 and 3 can be combined, but I use these five as a framework for analyzing what problem you need to solve and also as a framework for performance measurement.

At any rate, in the performance consulting frame, problems are seen in a much broader context than in the Six Sigma/Kaiizen frame.  From a performance consulting perspective, problems are anything that prevents objectives from being accomplished, waste is anything that does not contribute to the accomplishment of those objectives, and inefficiency is anything that adds unnecessary cost to accomplishing set objectives.

Because it is centered on accomplishing objectives, performance consulting is a compliment to the performance management process.  Companies set strategy, derive objectives from that strategy, and they set out to accomplish those objectives with execution governed by performance management.  Performance consulting then, works in this context, seeking to understand why objectives are not being met, or it works to ‘raise the bar’ of performance expectations. 

In performance consulting, a performance needs assessment, a performance analysis, or a gap analysis is used to determine what problem needs to be solved.  There are many different models for this which I won’t get into in this post, but suffice it to say that performance consulting looks quite extensively and comprehensively at all aspects of performance, not just production or process aspects. 

As such, the definition of a ‘problem’ in the performance consulting frame is much broader than it is in the Six Sigma or Kaiizen frame.  An organization can use Six Sigma/Kaiizen to remove all wasted and costly steps in a process and still have performance problems that need to be solved.  For example, the employees may not be motivated to perform that 100% waste-free, efficient process.  Or the employees themselves may have knowledge or skill gaps that prevent them from performing it.  Performance consulting looks comprehensively at the performance problem, well beyond the Six Sigma/Kaiizen production mindset.

It is because of this Achilles heel in problem identification, that Six Sigma and Kaiizen, when applied to overall performance within an organization, starts to become ineffective (or even cannibalistic) after about 5 years of implementation.  The obvious problems are identified and solved early in the implementation, and the deeper or more abstract problems that remain are best identified through a more sophisticated approach like performance consulting.  It is possible to avoid this affect with customization, but most companies squarely hit this wall.

But while both Six Sigma and Kaiizen are weak in terms of problem identification, they are both very strong in terms of actually solving certain problems.  Performance consulting has a broader set of interventions than Six Sigma/Kaiizen have, but both Six Sigma and Kaiizen are much stronger than performance consulting when applied to production problems.

The optimal approach is an integral blend of performance consulting and Six Sigma that leverages the strengths and avoids the weaknesses in each.  It is critical to establish a comprehensive measurement framework that includes all aspects of performance (think, know, say, do, enable), and then to use each methodology to its strengths, measuring the impact holistically.

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Empirical and Rational Logic

Science is knowledge rooted in experience or empiricism.

Technology is knowledge rooted in thought or rationalism.

When we advance science we ‘discover’ reality and move forward our understanding of that reality. When we advance technology we ‘invent’ new reality by rearranging existing reality. When this is applied it becomes industry or the science of making things.

Genetic knowledge is knowledge that is physically inherent to the mind. The age old argument of empiricism or rationalism is solved when one not only realizes that both are valid, but when one also comes to see that these two are the two worlds of knowledge. One is convergent, and one is divergent. One is associated with discovery and the other with creativity and invention. One is building upon observations and one is building thoughts upon other thoughts. And both operate by the same logic, but it simply flows in different directions (convergence and divergence).

On Expertise

The wrapper for all industrial applications is performance. Only through performance do organizations accomplish their goals.

• Capabilities or competencies can exist, but people can choose not to apply them to performance.
• Or people can, for whatever reason, not be allowed to use their capabilities or competencies and hence these cannot be applied to performance.
• Or people can not have the capability or competency to start with and hence it is never applied to performance.
• Or the capability or competency a person has is not needed or required to meet performance objectives, so they are not applied to performance. – etc. (other performance gaps)

In other words, performance is often found struggling against things like apathy, politics, a lack of acceptance, a lack of free flow for ideas, ignorance, or lack of focus. Capability and competency are dormant performance. You could also say that they represent the potential to perform. This potential is not always realized, and in all of these scenarios, motivation is a key factor in shoring up performance gaps.

The other key is cooperation. If individuals do not apply knowledge (perform) cooperatively, then its objectives are hindered. In knowledge working outside of industry, society suffers for the same reason. In terms of industry, only one thing matters, and that is performance. If a discipline like knowledge management, or a component, or a department, or even a person, is disconnected from this aim then there are performance gaps within the organization, and all organizations have these gaps. The goal is to minimize them.
I like to talk about the term expert because I think it contains a conundrum that represents most of the problems with knowledge working today.

• If a person is deemed an expert strictly by social recognition or solely because they are published, then logic can become irrelevant.
• If a person is deemed an expert by position, then logic can become irrelevant.
• If being an expert is more important than knowledge itself, then we have given up knowledge for position power. – If a person is deemed an expert by their knowledge, but without regard to social recognition, then their knowledge will likely not be valued or used.
• If a person is deemed an expert by knowledge context, then they may sit down in that context and never advance it (intelligence without knowledge creation).
• If a person is deemed an expert because they advance a knowledge context, then knowledge context is being confused with knowledge creation, which is a separate and distinct process and skill with that process.
• If a person is deemed an expert because they perform in a given situation, then expertise is a synonym with performance, so why use the term at all?

The term ‘expert’ encapsulates all of the confusion in knowledge working today. In short, we’ve confused all kinds of concepts like intellect, knowledge creation, social acceptance, and knowledge context. All of these are interactions that work together cooperatively in a single, cohesive system of knowledge working. They are not individual concepts that stand alone or can be interpretted outside of the context of the other knowledge interactions. Knowledge is one and questions are one–and the sum of interactions associated with these two is the whole of knowledge working.

Articles on the Fallacy of ROI

Meaningful metrics beyond ROI – Parkin’s Lot

Why ROI Can Sometimes Lie – Adrian Mello/ZDNet

How to Improve Performance Management – CFO.com (A good article on overall measurement)

Sensing User Intention

One of the coming waves in technology will be the ability for the machine to sense user intention. As technology moves into this realm, the line of fusion between mind and machine, or the ‘interface’ will become very thin.

HyperInstruments

HyperInstruments has a special interest in inventing musical instruments that “understand” the artistic intentions of the performer, allowing for the enhancement and extension of musical expression.

“We design these instruments for use by highly skilled performers, as well as for students, novices and amateurs. We also explore how new media technology can modify music itself, and how such concepts can in turn be applied to interactive intermedia art and entertainment forms, of which opera is a particularly sophisticated example.”

Current directions in the group are to develop creative experiences and “musical toys” for children from ages 6 to 12, and to design future performance spaces that measure and react to performer sound, gesture, and intention.

Noetic Spaces: The human mind and the sense of reality

The philosopher John Searle explains the difference between the mind and the computer is its’ existence or absence of intentionality.

The digital languages are inputted and outputted data through conduits of proxy systems. On the other hand, minds interpret the information by filtering it through people’s belief systems.
Searle defines “seeing” as “seeing as”, and “perceiving” as “perceiving as” according to the focus of each person’s attention.  He states that the mood and state of minds filter information as to how and when we perceive things.

I assume it is because each person’s “semantic engine” or “conceptual apparatus” (both are metaphors of mind) are different according to their configurations (ways of thinking or personalities).
Then Searle’s states, “computers will never function as human minds because computers do not have intentionality.”

Examining the lexical item “intentionality” may be helpful to explain the meaning of “mind”. The lexical item “intend” is originated from the Old French, from Latin “intendere”. The Old French “in” means “toward”, and “tendere” means, “to stretch”.

It shows one of the natures of the” mind” which has plasticity and a scope of attention. The ancient Greek used a metaphor of mind-as-a slingshot, which may be to define mind as something which has intention, or mind as intention itself.

See Also:

• Intending, and Artificial Intelligence – Larry Hauser
• The next computer interface: your finger – ZDNet
• Brain-Machine Interfaces – Nature

Levels of Intentionality

User thinks or acts in accord with his or her own intention.

Computer interface records and responds to user intention from a device (e.g. a mouse)

Computer interface records and responds to user intention by interpretting motion from the user.

Computer interface records, responds, and anticipates user intention.

Computer records, responds, and anticipates intention from brain waves and the interface disappears.

Transfer human intention to computer.

Computer anticipates or predicts intention from a quantum dimension.

Computer develops its own intention.