Category Archives: MIT

CONTROLLED DESIGN MANAGEMENT – Part 3

By Moises J Goldman & John Jonelis

Our business culture has evolved and attitudes have re-aligned.  In sharp contrast to the past, creative employees have finally gained the acceptance and respect they deserve for the crucial role they play in organizational success.  The business climate is faster-paced, than ever—rapidly changing, and multicultural.  Staunchly individualistic leaders backed by a computer savvy workforce characterize our high tech companies, and increasingly, our entrepreneurial ventures.  It is important to appreciate that sequential charts of managerial jargon are no longer well received.  Such things impose uniformity, and uniformity is anathema to today’s creative workforce.  Under these circumstances, it is extremely challenging to manage product design using yesterday’s managerial paradigms.

This is the third of four installments.  We’ve explored the history and current state of modern management philosophy.  Now, we will introduce an entirely new mode of thought—the Controlled Design Management Model.

To be meaningful in today’s culture, any shift in management strategy must meet certain critical standards.  It must be intuitive, adaptable, focused, practical, and measurable.  These are the goals we will set out to achieve.

  • Intuitive and Adaptable – No rigid chart or schematic to implement.
  • Focused – A practical structure, which zeros in on workflow.
  • Practical – Departments will implement the model themselves.
  • Measurable – Management can track progress.

In order to achieve these goals, we must build self-optimization into the product cycle and to meet that end, we base our new thinking on Control Systems Theory, as used in such places as computerized system controls and inertial navigation systems.  We call it the Controlled Design Management Model.  For the purposes of this paper, we will circumvent the complex mathematics of Control Theory and present the ideas in an intuitive format, reducing key concepts to graphical form.

Controlled System

At its most basic form, a Controlled System is a process by which an objective or Input generates an outcome or Desired Output.  Suppose, for example, that the system is a bicycle factory and we are trying to build a super bicycle.  If the factory, as a system, behaves appropriately, then the factory will output the desired output – a super bicycle.  If, on the other hand, the factory does not operate appropriately, the output will be an undesired outcome – perhaps a tricycle.  It will be useful to reduce this to graphical form.  (See Figures 3a and 3b.)

Figure 3a – Controlled System

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Figure 3b – Uncontrolled System

This may seem rather simplistic, so let’s build on it.  To make the system self-optimizing, we add a feedback loop to the above diagram. (See Figure 4.)  When the desired outcome becomes equal to the desired objective, then the error (or difference between objective and outcome) will be zero.  Else, corrections are made (called “pivoting” in Lean Theory) until we eventually arrive at the MVP or initial product deployment. 

Figure 4 – Simple self-optimizing Controlled System

Let’s see what this elementary flow chart accomplishes.  We plot the input and output of the above system, where Time is the X-axis and Magnitude is the Y-axis and produce a graph.  The process swings back and forth until it navigates the optimal path.  (See Figure 5.  Note the similarity to an internal navigation system.)

Figure 5 – Self-optimization through a feedback loop

From Figure 5, we surmise that the output reaches steady state, at t(1) which is when the desired objective is equal to the desired outcome, rendering the error equal to zero.  The behavior of the output prior to reaching t(1) is called the transient response and beyond t(1) is called the steady state response.

  • Transient Response is composed of idea, concept, feasibility, and definition (from the Traditional Model).
  • Steady State Response is composed of Deployment, Growth, and Maturity (from the Traditional Model) and the release of the Minimum Viable Product or MVP (from the Lean Model).

Transient Response relates to the problems of developing a product or process.  It might look like the following example:  How can we make an elevator reach the twelfth floor more quickly?  In actual practice, it may stop at any number of floors on the way, and even overshoot floor twelve before coming back to open the doors for you. Any number of solutions may be proposed.  We examine goals, stretch technology, and make tradeoffs.

Steady State Response deals with entirely different concerns.  The MVP of an optimized elevator schedule is ready to launch.  How can we standardize, market, deploy, and improve the new design or schedule?

Can we control how fast the outcome will reach its objective?  The answer is yes.  Goldman, Shieh, and Chen proved this many years ago by using the Second Cauer Form of continued fractions expansion.4, 5  Let’s look at it in graphical form.  By applying a few minor modifications to Figure 4, we have a self-optimizing module:

Figure 6 – Controlled Design Management Model

Figure 6 differentiates Transient from Steady State responses and adds an Internal Disturbance, representing noise due to poor product design, faulty test equipment, poor engineering, and other considerations. The optimization process reduces such noise closer and closer to zero via the process of a feedback loop.  Mathematically speaking, this is the same controlled system as in Figure 3(a), but this representation depicts the separate influences of the transient and steady state responses.

A New Perspective

What advantages does the Controlled Design management Model offer over the Lean and Traditional Models? The first is simply knowing which phase of the model contributes to the transient portion—idea, concept, feasibility, development—and which phase contributes to the steady-state portion—final deployment, growth and maturity of the design. For management, this is critical.

  • By controlling the part of development that contributes to the transient response, management can optimize the rise time and minimize time to deployment.
  • By controlling the factors that contribute to the steady state response, management can optimize the deployment, growth, and maturity of the product.

A mid to large organization includes many and varied departments through which product development flows from idea generation to maturity. What are some of the advantages to our new model?

  • By describing our model in the language of the digital age, each individual department can easily put it into practice.
  • Each department is responsible ONLY for what it can control. Each is given a unique decision input and desired output.
  • Each department can optimize its output using the model. This, in turn, yields an optimized organization.  An optimized organization is, quite simply, the sum of the optimized departments.

Next, we’ll demonstrate these ideas with a practical example.

Coming next: Part 4

 Go back to PART 1

 Download full paper (PDF)

.

References

  1. Deming, W. Edwards (1964) [1943].  Statistical Adjustment of Data. Dover. ISBN 0-486-64685-8. LCCN 64-24416. (1966) [1950].  Some Theory of Sampling. Dover. ISBN 0-486-64684-X. LCCN 66-30538.
  2. William Ouchi: “Theory Z” How American Business can meet the Japanese Challenge.  Addison-Wesley Publishing Company, 1981
  3. Lean was originated by Eiji Toyoda and Taichi Ohno of Toyota Motors.   Ohno, Taiichi (1988), Toyota Production System: Beyond Large-Scale Production, Productivity Press, ISBN 0-915299-14-3
  4. C. F., L. S. Shieh, Joint Automatic Control Conference, Michigan, p 454
  5. Shieh, L.S. and Goldman, M. J., 1974 I.E.E.E. Trans. Circuit Syst., 21, 341
  6. The Hollow Corporation, Anita Campbell, Small Business TRENDS (2012)  https://smallbiztrends.com/2004/04/hollow-corporation.html

Graphics

Flow-charts by Moises Goldman and John Jonelis.

Graphics from MS Office.

About the Authors

Dr. Moises J Goldman holds an MSEE and a PhD in Engineering Systems from UCLA, specializing in large-scale systems, process optimization, and product innovation. MBA from MIT Sloan, specializing in strategic planning and business development.  His focus is on periods of challenge and change, including startup, growth and restructuring.  Goldman served as CEO, COO, and CTO in diverse industries and developed business across the USA, Germany, Spain, Mexico, Dominican Republic, Jamaica, and Brazil, working with small firms as well as branded giants such as Lockheed, Rockwell, ATT, America Movil, GM, Ford, Scotia Bank, and HSBC. Sits on several boards where entrepreneurship and innovation are the primary goals.  Consults to merging companies during the integration phase as well as startups, helping them become going concerns. Member of several advisory boards at MIT.  Founding member of the TALENT program at IMSA.  Dr. Goldman can be reached at Moises.Goldman@outlook.com

John Jonelis patented seven products and developed dozens more in the field of air pollution control.  Created the Revelation suite of trading algorithms.  Private equity investor.  Artist.  Writer, and publisher of Chicago Venture Magazine and News From Heartland—the Journal of the Heartland Angels.  Author of the novel, The Gamemaker’s Father.  Illinois Wesleyan BFA, 1974.  Kellogg MBA 1989.

Copyright © 2019 Moises Goldman & John Jonelis. All rights reserved. Quotation with attribution is permitted for educational purposes.

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. Please perform your own due diligence. It’s not our fault if you lose money..
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CONTROLLED DESIGN MANAGEMENT – Part 2

by Moises J Goldman & John Jonelis

In the early 2000s, after the internet bubble burst, it became abundantly clear that the US needed a new competitive edge.  A product management philosophy took hold, called Lean—Lean Development, Lean Manufacturing, Lean Planning, Lean Sigma, Lean Start-up. 2  Lean is a management philosophy that considers any part of the enterprise, which does not directly add value to the final objective, as superfluous—be it product development, customer service, or for that matter, the entire enterprise.  It examines all processes and eliminates the ones that do not add value to the end objective.   Lean is an attempted departure from the traditional way of doing business.  It found favor in the US and, to one extent or another, became a dominant model.  This is the second installment of a four-part article about managing creative enterprises. 

Lean

In Lean Management, a project is broken into two phases.  Phase 1 – Stealth Mode – represents the alpha version of a product.  The nascent prototype is tested in the internal company environment.  Further development leads to a beta version for which certain companies, by invitation, test the product before release to manufacturing.  Phase 2 – Market Mode – represents the completion, approval, and release of an MVP—minimum viable product—which then goes through a correction phase that includes bug fixing.  At the same time, a company will test features. This includes, by implication, changes to marketing plans, sales strategies, etc. (See Figure 2.)

Figure 2 – Lean Development Mode

The Lean Model does a superb job of describing the modern way of thinking about the product cycle, but the same thinking that governs the Traditional Model drives it.  As before, it finds expression as a high-level sequence.  It provides a manager no road map to improve a situation, and instead depends entirely on personal talent and resourcefulness to win the day.

Traditional vs. Lean

Lean presents certain points of emphasis that distinguish it, such as the MVP, but the irony is that when we compare the Lean Model to the Traditional Model, we find that they are basically the same.

  • Idea, Concept and Feasibility” in the Traditional Model are no different from “Objectives, Ideation, Definitions, and Mockups” in the Lean Model.
  • “Preliminary Business Case, Definition, and Final Business Case” in the Traditional Model are not any different from “Proof of Concept and Alpha Version” in the Lean Model.
  • “Development” and “Deployment” in the Traditional Model is the same as the “MVP and Releases X” in the Lean Model.
  • “Initial Growth” in the Traditional Model is the same as “Release 2.0 and Releases 2.X” in the Lean Model.
  • “Maturity” in the Traditional Model is no different from “Release 3.0 and Releases 3.X” in the Lean Model.

Obviously we could point out more similarities and the reader may ask what we have gained out of the so call Lean Model.  The answer is actually quite profound: A significantly different perspective on the same thing. 

New management models may induce radical change in various ways, but companies will always consist of people, their ideas, and a structure.  A commercial concern can be described as the organized creation and distribution of products and services.  That probably will not change.  So we are dealing with the same basic material, but the point of view and emphasis makes the difference between one model and the next.  The change in perspective can be highly valuable and the ramifications extreme.  Compare for a moment some of what has already been discussed:  Japan’s renaissance in the 1980s, JIT, Lean, and the Hollow Corporation.  But we can do better.

The Current Environment

Today, automation is reversing the problem of cheap overseas labor and increasingly bringing manufacturing back to our shores.  We are only at the beginning of this new cycle.  Meanwhile, a new entrepreneurial economy is bursting forth.  Design is moving to center stage.  Our business culture has evolved and attitudes have re-aligned.  In sharp contrast to the past, creative employees have finally gained the acceptance and respect they deserve for the crucial role they play in organizational success.  The business climate is faster-paced, than ever—rapidly changing, and multicultural.  Staunchly individualistic leaders backed by a computer savvy workforce characterize our high tech companies, and increasingly, our entrepreneurial ventures.  It is important to appreciate that sequential charts of managerial jargon are no longer well received.  Such things impose uniformity, and uniformity is anathema to today’s creative workforce.  Under these circumstances, it is extremely challenging to manage product design using yesterday’s managerial paradigms.

Along with previous models, Lean has proven its worth.  But once again, current conditions call for an entirely new point of view—a clear and simple model that works with creative organizations that have no patience with past modes of operation—a model that adapts to most every organization regardless of mission and organizational structure.  We all seek efficiency and excellence in our design and manufacturing processes, and we emphasize these objectives more than we do any others.  Today, for the release of any complex product, we need a new model that optimizes and controls efficiency and excellence.

The Controlled Design Management Model

At their root, all the models that have gone before are based on the same kind of thinking—the placing of categories in the right sequence.  Now we will come at the problem from with a different set of criteria and a different mode of thought.  We will lay aside any disputes between high-level models, and in fact adapt to most any sequential life cycle that an organization embraces.

The next article will describe this radically new way to manage creative organizations.

Continue to PART 3

Go back to PART 1

Download full paper (PDF)

.

References

  1. Deming, W. Edwards (1964) [1943].  Statistical Adjustment of Data. Dover. ISBN 0-486-64685-8. LCCN 64-24416. (1966) [1950].

Some Theory of Sampling. Dover. ISBN 0-486-64684-X. LCCN 66-30538.

  1. William Ouchi: “Theory Z” How American Business can meet the Japanese Challenge.  Addison-Wesley Publishing Company, 1981
  2. Lean was originated by Eiji Toyoda and Taichi Ohno of Toyota Motors.   Ohno, Taiichi (1988), Toyota Production System: Beyond Large-Scale Production, Productivity Press, ISBN 0-915299-14-3
  3. C. F., L. S. Shieh, Joint Automatic Control Conference, Michigan, p 454
  4. Shieh, L.S. and Goldman, M. J., 1974 I.E.E.E. Trans. Circuit Syst., 21, 341
  5. The Hollow Corporation, Anita Campbell, Small Business TRENDS (2012)  https://smallbiztrends.com/2004/04/hollow-corporation.html

Graphics

Flow-charts by Moises Goldman and John Jonelis.

Graphics from MS Office.

About the Authors

Dr. Moises J Goldman holds an MSEE and a PhD in Engineering Systems from UCLA, specializing in large-scale systems, process optimization, and product innovation. MBA from MIT Sloan, specializing in strategic planning and business development.  His focus is on periods of challenge and change, including startup, growth and restructuring.  Goldman served as CEO, COO, and CTO in diverse industries and developed business across the USA, Germany, Spain, Mexico, Dominican Republic, Jamaica, and Brazil, working with small firms as well as branded giants such as Lockheed, Rockwell, ATT, America Movil, GM, Ford, Scotia Bank, and HSBC. Sits on several boards where entrepreneurship and innovation are the primary goals.  Consults to merging companies during the integration phase as well as startups, helping them become going concerns. Member of several advisory boards at MIT.  Founding member of the TALENT program at IMSA.  Dr. Goldman can be reached at Moises.Goldman@outlook.com

John Jonelis patented seven products and developed dozens more in the field of air pollution control.  Created the Revelation suite of trading algorithms.  Private equity investor.  Artist.  Writer, and publisher of Chicago Venture Magazine and News From Heartland—the Journal of the Heartland Angels.  Author of the novel, The Gamemaker’s Father.  Illinois Wesleyan BFA, 1974.  Kellogg MBA 1989.

Copyright © 2019 Moises Goldman & John Jonelis. All rights reserved. Quotation with attribution is permitted for educational purposes.

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. Please perform your own due diligence. It’s not our fault if you lose money..
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CONTROLLED DESIGN MANAGEMENT – Part 1

By Moises J Goldman & John Jonelis

Today’s business culture is more strongly creative and entrepreneurial than at any time in history, posing new organizational opportunities and challenges.  That calls for a new way to think about and implement design management.  Using the language of the digital age, this article introduces a new perspective, applying a radically different technique to the management of the creative process, and then demonstrates an intuitive working model that functions in any modern organization.  This is the first installment of a four-part article. 

Current Management Models

Management models have undergone disruptive changes over the years.  The early 1980s was a time when Japanese productivity achieved the highest level anywhere in the world. At that time, productivity had fallen in the USA, and many felt that America could and should learn from Japan.  There was a real call to break from the Traditional Model of product management.

Curiously, the Japanese renaissance was, in large part, the product of an American—the pioneer W. Edwards Deming.  He espoused high product quality coupled with a humane approach to managing people.  He laid out a complex set of principles to realize those ideals.  Deming built his approach on different assumptions than the Traditional Model.  I had the pleasure of working at a company founded on his principles.  This was rare in the USA, but the Japanese implemented his theories with fervor.  Much can be said about the details, but when you boil it down to its simplest terms, Japanese success was actually based on three broad factors:

  • A focus on a strong corporate structure
  • Long-range staff development
  • Consensus decision-making

These factors led to lower turnover, higher job commitment, and higher productivity.  This initiative was then adapted for use in the USA by William Ouchi and became known as Theory Z.1   For a time, Eli Lilly, Rockwell International, General Motors, Westinghouse and many other large corporations embraced this new dogma.

But this new paradigm clashed with the ideas of western management and the expectations of an American workforce.  Theory Z didn’t gain lasting traction in America, where the Traditional Model continued to dominate.  Why the cultural clash? It has to do with the way we think—more particularly, the way in which we picture or imagine a process.  Figure 1 lays out the Traditional Model of product management in graphical form:

Figure 1 – Traditional Product Management Model

The Traditional Model can be expressed as a high-level sequence and it is, quite simply, one specific mode of thought.  To its credit, it does an excellent job of defining a product life cycle.  Everything is placed neatly in a row.  There is a defined beginning and end.  But the weakness of this model slows many organizations that use it and it does nothing to improve or optimize a process.  The inherent top-down mode of thought is a limiting factor, and is also limiting to the models that grew out of it or rose up in reaction to it.

New Paradigms

Nowhere was the contrast with Japan greater than in automobile manufacture.  Japan, long known for its cheap, low-quality vehicles and other junk, began to crank out the best-made cars, electronics, and other products in the world.  Meanwhile, Detroit remained mired in the concept of planned obsolescence.  Consumers took notice and they voted with their wallets.

Then Toyota rolled out Just-in-Time Manufacturing (JIT) as a way of reducing the cost of inventory.  Among other changes, JIT heightened the awareness of design management itself.  Eventually America had to adjust if it was to compete with the Japanese, and the resulting chaos changed the way we do business today.  Companies began to adopt JIT, and increasingly moved toward a new ideal—the Hollow Corporation—also known as the Virtual Business.6

At its extreme, the Hollow Corporation is an organization stripped of almost every function.  Brand means everything and the company makes nothing.  Everything is measured in money, and profit is the only goal.  A simple example of a hollow corporation is an American clothing designer taking on a European-sounding name and making designer clothing in China for sale to the world.  As this trend grew, companies outsourced more and more functions.  This intensified the importance of brand marketing and marketing for globalization.  While this was going on, America was busy transforming itself into a service economy.

Globalization Matures

But industry discovered that it was not only possible but also cheaper to manufacture products overseas and ship them back to US shores.  Whole industries moved their factories offshore—especially to China.  The entire textile industry left.  Tool and dye left.  Electronics manufacture left.  With time, others followed, including crucial smokestack industries such as steel.

The next logical step was to offshore project management and product development.  Creative and physical design had always been a key competitive advantage in the USA.  Its business world smugly expected it to remain so.  But due to the ability to collaborate across the internet, actual design began to take place at multiple locations across the globe, with products for sale to the world—and with great success.

These trends were not without intriguing and sometimes counterintuitive aspects.  Businesses made adjustments.

  • Many US electric generation utilities sold off their physical power plants in search of greater profits as distribution networks.
  • Fluctuation in the currency market led Japanese automobile manufacturers set up production facilities in the USA, closer to the end consumer and using American workers—and still, American manufacturers struggled to compete with them.
  • US automobile manufacturers and other industries abandoned the policy of planned obsolescence and over time learned the new culture of quality.
  • South Korea began to design and manufacture high-quality goods—from pianos to automobiles to mobile phones.
  • China began outsourcing to the Vietnam and other third world countries in search of even cheaper labor.

Lean

In the early 2000s, after the internet bubble burst, it became abundantly clear that the US needed a new competitive edge.  A product management philosophy took hold, called Lean—Lean Development, Lean Manufacturing, Lean Planning, Lean Sigma, Lean Start-up. 2  Lean is a management philosophy that considers any part of the enterprise, which does not directly add value to the final objective, as superfluous—be it product development, customer service, or for that matter, the entire enterprise.  It examines all processes and eliminates the ones that do not add value to the end objective.   Lean is an attempted departure from the traditional way of doing business.  It found favor in the US and, to one extent or another, became a dominant model.

The next article will compare and assess Lean in light of previous models.  Then we will introduce an entirely new way to manage creative enterprises.

GO TO PART 2 – LEAN

Download full paper (PDF)

.References

  1. Deming, W. Edwards (1964) [1943].  Statistical Adjustment of Data. Dover. ISBN 0-486-64685-8. LCCN 64-24416. (1966) [1950].  Some Theory of Sampling. Dover. ISBN 0-486-64684-X. LCCN 66-30538.
  2. William Ouchi: “Theory Z” How American Business can meet the Japanese Challenge. Addison-Wesley Publishing Company, 1981
  3. Lean was originated by Eiji Toyoda and Taichi Ohno of Toyota Motors. Ohno, Taiichi (1988), Toyota Production System: Beyond Large-Scale Production, Productivity Press, ISBN 0-915299-14-3
  4. C. F., L. S. Shieh, Joint Automatic Control Conference, Michigan, p 454
  5. Shieh, L.S. and Goldman, M. J., 1974 I.E.E.E. Trans. Circuit Syst., 21, 341
  6. The Hollow Corporation, Anita Campbell, Small Business TRENDS (2012) https://smallbiztrends.com/2004/04/hollow-corporation.html

Graphics

Flow-charts by Moises Goldman and John Jonelis.

Graphics from MS Office.

About the Authors

Dr. Moises J Goldman holds an MSEE and a PhD in Engineering Systems from UCLA, specializing in large-scale systems, process optimization, and product innovation. MBA from MIT Sloan, specializing in strategic planning and business development.  His focus is on periods of challenge and change, including startup, growth and restructuring.  Goldman served as CEO, COO, and CTO in diverse industries and developed business across the USA, Germany, Spain, Mexico, Dominican Republic, Jamaica, and Brazil, working with small firms as well as branded giants such as Lockheed, Rockwell, ATT, America Movil, GM, Ford, Scotia Bank, and HSBC. Sits on several boards where entrepreneurship and innovation are the primary goals.  Consults to merging companies during the integration phase as well as startups, helping them become going concerns. Member of several advisory boards at MIT.  Founding member of the TALENT program at IMSA.  Dr. Goldman can be reached at Moises.Goldman@outlook.com

John Jonelis patented seven products and developed dozens more in the field of air pollution control.  Created the Revelation suite of trading algorithms.  Private equity investor.  Artist.  Writer, and publisher of Chicago Venture Magazine and News From Heartland—the Journal of the Heartland Angels.  Author of the novel, The Gamemaker’s Father.  Illinois Wesleyan BFA, 1974.  Kellogg MBA 1989.

Copyright © 2019 Moises Goldman & John Jonelis. All rights reserved. Quotation with attribution is permitted for educational purposes.

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. Please perform your own due diligence. It’s not our fault if you lose money..
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TO BE OR NOT TO BE HACKED?

by William Shakespeare,

alias Moises J. Goldman and John Jonelis

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Hamlet—To be or not to be hacked? That is the question. Whether ‘tis nobler to suffer the slings and arrows of outrageous fortune, or to take arms against a sea of phishes, gouged by creatures who boast no scruple, nor affect any purpose higher than foul destruction—and by opposing, end them?

[Editor’s translation—Hackers are a bummer. This is war.]

 

William “Moises” Shakespeare

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Or may say ‘tis wiser to remain in dungeons rank and old—to sleep, perchance to dream—ay, there’s the rub. For in that sleep, what dreams may come? The internet makes cowards of us all.

[Editor’s translation—Should I upgrade the robustness of my internal infrastructure and firewalls?]

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Horatio—But soft, me lord, to think upon the many turns a kindom make.

Betwixt two means shall we choose to take.

[Editor’s translation—There are two good options.]

 

Hamlet—Ay, the dilemma. To guard an angry pack of dogs that tear and rent and hack away till strength and blood be spent—or flee? How wouldst thou fight, Horatio? I would not hear your enemy say you could do it. Nor shall you do my ear that violence.

[Translation—Don’t feed me a pack of lies. If we encrypt all sensitive data and cyber-secure our network we still can’t achieve fail-safe.]

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Horatio—Hear me lord; I make my case:

Should bits and bytes habitate high Cloud

A kingdom’s gold to free?

No arms, no knights, no castle wall to tug a purse’s string so proud!

‘Stead exult in markets, foul of hogs and sheep and goat?

Entice the sorcerer to play in darker art, in unknown moat?

To raise a legion—conquer lands anew beyond the sea?

And so extend a kingdom’s reach?

[Option #1: The Cloud is cheap.  Save your money for marketing, R&D, and expansion.]

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Hamlet —Methinks this boy hath soundly grounded thought. He makes PaaS-ing SaaS at learning dearly bought. It takes no brain to buy his train of thought.

[Seems like a no brainer. The Cloud.  Platform as a Service—Software as a Service. Let’s do it!]

.

Horatio —But soft, me lord, I fear foul play!

This Cloud by wild winds be cast astray.

It boasts no force to hole such gauze with tumult and in fray,

And by doing so, steal treasury of intellect away.

‘Tis best, to build yon castle walls of stouter stuff, some say.

Keep bytes and treasure close and spend on fodder and on hay.

[Option #2: The Cloud is way too vulnerable to attack. Update your in-house network.]

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Hamlet —Wouldst thou squeeze gold from a lark? Something is rotten in the state of Denmark. But harken thee—where may best advantage be? What odds see ye?

[That equipment’s really expensive! What’s the probability of getting hacked either way?]

Horatio —Sorcerers be that wouldst draw

Straight crook from snarled oaken saw.

[Mathematicians use probability trees.].

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Hamlet —O cursed spite that ever I was born to set it right! 

[I hate math!]

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Horatio —Of haste take not. Outcomes be but three.

Take heed of which I shew to thee.

[No big deal. There are only three probable outcomes.]

Hamlet—Hold, varlet! A fourth ye lacked—that one repent and not be hacked.

[Hamlet has noticed a missing variable: An enterprise upgrades internal systems and yet escapes hacking.]

.

Horatio—‘Tis true M’lord, yet is it moot?

Foes be met; nought ground ‘neath heel o’ boot.

Complication wears poorly on thee.

There be no guarantee.

This outcome we call 1-P3…….(1)

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Hamlet—Ha! There are more things in heaven and earth, Horatio, Than are dreamt of in your philosophy.

[Maybe I’m not as dumb as I look.]

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Horatio —‘Tis sooth, my liege—I seek not to deceive.

Perchance I draft a map—deeper knowledge ye may tap.

Yon magic shall appease;

Thy grace’s ire set at ease.

[I’ll make it simple, so even you can see. Take a look at this probability tree.]

 

M’lord do you see?

If systems new and hacking lacking,

Probability is simply 1-P3.

[The probability of an internal network not getting hacked.]

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Hamlet—What make I of this wonder? To ask a fool is to blunder.

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Horatio—Magic formula ye seek, to make right your decision?

Fortunately, Shakespeare knows it with precision.

[Be cool. I got this.]

Look here, dear Ham, and spy yon enterprise,

Floating on the Cloud ’tis wise.

Not to hack or nick sharp blade.

We dig our likelihood with spade.

‘Tis thus: P1+(1-P1)(1-P2)=1-P2(1-(1-P1)………(2)

[The probability of not getting hacked on the Cloud.]

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Hamlet [Aside] Madness in great ones must not unwatch’d go. A screw is loose. He rhymes like Dr. Seuss.

[Horatio’s gone bonkers.]

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Horatio —But hark—magicians work dark secrets in a day

That mortal man can plumb no other way.

I spell it in a cypher so you see

The final answer to this mystery.

[Here dummy, I’ll spell it out for you.]

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Hamlet—Indeed, this must I see.

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Horatio—Floating on a Cloud,

Yon enterprise two chances escape plunder,

To hide from doom, not hacked asunder.

The Cloud foul Russian must attack rapaciously

Before cursed knife shall reach its mark with certainty.

[If your enterprise is on the Cloud, hacking is a two-stage process. The Cloud may get hacked. But even then, your enterprise may escape damage.]

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To ride the Cloud in skies of blue, equation (1) must be less than (2).

Hence:  1-P3<1-P2(1-P1)…….(3)

We boil down that poison thus, and there we gain the clue.

If fates would their due, we sing this song,

Our enterprise will float along.

And thus:  P3>P2(1-P1)

 [This is the absolute condition for an enterprise to go to the Cloud.]

 

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Hamlet—Dost thou think me easier play’d on than a pipe? For ‘tis sport to have the enginer hoist with his own petard, an’t shall go hard.

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Horatio—M’lord salves the ego with a threat.

Is this the way your friends are met?

But hear me, sire, ‘tis plain to do.

I will write it out for you.

Be ye not a foe to the way the numbers go.

Ye shall recall the probability of hacking free be 1-P3.

If wise man, on gauzy Cloud his merit bent,

To the tune of 80%,

The numbers shew:  1-P2(0.2)

[Here ya go, Mr. Bigshot CIO—if the probability of not getting hacked on the Cloud—P1—is 80%, then 1-P2(1-0.8) hence 1-P2(0.2)]

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Hamlet—Still it be Greek to me.

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Horatio —Here, my lord, I will unravel

The way that ye must travel,

To the ending of thy quest.

Be in knowledge, not in jest.

[Gotcha!]

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Hamlet—Get it over before I die.

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Horatio —Here’s an end so ye may rest

Like bones inside a chest.

If P3>(0.2)P2 be true,

To the Cloud get ye hence,

Else makest equipment new

And play yon cards close to thy vest.

[This is how the CIO makes the decision.]

Hamlet[Aside] This be a fellow of infinite jest, of most excellent fancy. He rhymes obtuse like Mother Goose. Yet I shall the effect of this good lesson keep as watchman to my heart.

[Translation—Good! Let’s get some pizza.]

[Curtain]

[DOWNLOAD ARTICLE IN PDF FORMAT]

.Read the sequel – [THE JOB INTERVIEW WITH WILLIAM SHAKES]

NOTE – This example follows similar logic and Decision by Professor J. Sussman used in his lecture to the Engineering Systems Division entitled, DID BELICHICK MAKE THE RIGHT CALL?

[READ BELICHICK PART 1 – PDF]

[READ BELICHICK PART 2 – PDF]

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About the Authors

Dr. Moises Goldman is uniquely involved with STEM (Science, Technology, Engineering, and Mathematics). He is a member of several advisory boards at MIT and is a founding member of the TALENT program at IMSA.

John Jonelis is a writer, publisher of CHICAGO VENTURE MAGAZINE and NEWS FROM HEARTLAND, author of the novel, THE GAMEMAKER’S FATHER. BFA, MBA from Kellogg.

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Photography and Graphics – John Jonelis, MS Office

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. Please perform your own due diligence. It’s not our fault if you lose money.
.Copyright © 2017 John Jonelis – All Rights Reserved
.
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THE SUM OF ALL PARTS

Optimizing Human Behavior with a STEM Model

by Moises Goldman PhD

 

The Human Conundrum

For the last 15 years I have given numerous seminars aimed at optimizing executive and managerial performance in technology driven firms. The goal is to optimize departmental performance resulting in the larger optimization of an entire firm. As the theory goes: If the whole is the sum of the parts, and each part is optimized, then the whole is optimized.

These experiences have challenged my ability to communicate with people involved in STEM fields. This group represents a highly gifted segment of the population, and they tend to be very results driven. How does one reason, interpret, and convince scientists to modify their own behavior?

At first, I struggled with the appropriate lingo. I pondered how to describe my ideas using managerial jargon. I realized that I needed another language—a language that both empirical and intuitive thinkers will readily grasp and put to good use.

Then my eureka moment came to me. STEM initiatives are defined by basic human bevavior and not the other way around.

To some, this may seem counterintuitive, so let me elaborate. If we first accept and understand any given issue at hand through basic human reasoning, we can then interpret it in a STEM format. Once we do that, we can use the tools of science to bring about an optimized outcome. Let me add some clarity with the following example:

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Kalman Filtering

My Ph.D. is in Inertial Navigation and my Masters in Control Systems. I spent many years as an executive in the aerospace industry and came to be expert in Kalman Filtering, a complex mathematical algorithm used in the guidance and navigation of aerospace vehicles. It occurred to me to apply this knowledge to the human equation.

Kalman Filtering is also known as Linear Quadratic Estimation (LQE), but it’s not necessary to go into the math here. I will attempt to make this example clear and concise. All we need is a simple diagram. I’ll describe it in layman’s terms and then apply it to the human condition.

The diagram below describes the guidance control of a space vehicle. The vehicle is at position “time-zero” or T(0). We want to get to position T(1,000,000). We calculate the location of our target relative to our present location. We recognize that any internal disturbance, such as bad sensors, electronics, and perhaps bad computations must be eliminated. (We get rid of them.)

  • We predict the trajectory of the vehicle over a short increment of time.
  • We measure the actual flight path against our target and factor in real environmental conditions (noise), such as wind speed, meteorites, etc.
  • We correct our trajectory.

The vehicle is now at T(1)—a very small part of the entire trip. T(1) is the next starting position. The algorithm repeats, bringing the vehicle to the next position T(2), then T(3), and so on. We iterate—continue to perform the same steps—predict, measure, correct—to optimize the overall trajectory to the target—T(1,000,000).

Perhaps you recognize this as a description of the way a child learns to walk. It’s commonly called a feedback loop. It governs behavior in many human pursuits. It’s the way our central nervous system directs us to negotiate a curve while driving down the road. It’s the way a baseball player catches a ball and executes a play. It’s how a circus performer walks a tightrope. It’s the way we all learn optimum behaviors.

Our minds perform this function intuitively through ordinary mental concentration, focus, or attentiveness. Concentration is an iterative process and the higher the number of iterations, the higher the degree of accuracy.

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Optimizing Human Behavior

If we can model our human behavior and reasoning in STEM format then we are able to optimize it. As an example, let’s choose a simple human behavior and describe it using Kalman Filtering:

Behavior—Tomorrow I’m taking a final exam; I need to arrive at 8 am—the target.

Method—My class always meets at that time, so I already know approximately when to wake up. Since there cannot be any internal disturbances, I eat a good dinner, plan my breakfast and what to wear to school. I give myself time to study and get to bed early. I set my alarm for 7 am. I’m at position T(0) on the diagram.

  • Prediction—I estimate the time it takes to get ready and walk to the exam. (About the same as a normal day.)
  • Measurement—I reach the door and glance at my watch. It’s raining and I’m running late.
  • Correction—I grab an umbrella while at the same time speeding up my pace.

I get to the exam location on time, and the algorithm repeats itself for the next activity (assuming my intention is to optimize the next behavior).

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A Simple Model for STEM Communication

It’s amazing how simply human behavior can be optimized using a STEM model—whatever the circumstances may be.

We know our current state. [We are on a diet, T(0).]

  • We predict the meal that we are going to eat. [A nice juicy zero carb steak.]
  • We eliminate any internal errors [If we’re cooking it, we make sure all the ingredients are there; check the labels for carbohydrate count; grill in working order; plates and glasses, etc.]
  • We set out to eat, then get a call that we’re needed immediately somewhere else. We make a correction. [Either we eat extremely fast or put the meal away for later, at T(1).]

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Optimizing Complex Behavior

Now let’s apply this same optimization process to a non-linear human behavior—investing in the stock market. We have some money to invest, T(0), in a given company stock. We eliminate all the internal disturbances by doing our homework. We read quarterly statements, look at the fundamentals, research the competition, analyze price and volume activity on a stock chart, and interpret technical indicators such as MACD and Slow Stochastics.

  • We predict our next move—[buy the stock]—T(0).
  • As we are getting ready to buy the stock we hear news of the latest unemployment report and we realize it will have a direct effect on the stock we are buying. We must correct. [We buy more, less, a different stock, or sit tight. Which correction we use will have a direct effect on the optimization.]
  • We decide to buy more of the stock. Now we are at T(1), and must predict T(2)—[sell, hold, or add to position].

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Achieving Greater Accuracy

The more we are able to reduce the size of T (time), the more we increase the Kalman iterations, and the better the optimization. In human terms, optimization is inversely proportional to the size of T, and directly proportional to Intelligence. Please note that human thinking is continuous in time, so the smaller our intervals, the closer we approximate a continuum.

As you see, I found my language for communicating optimization of human activity in any given organization. It is an amazingly powerful tool.

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MORE FROM MOISES COMING SOON

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Moises Goldman at IMSA

About the Author

Dr. Moises Goldman is uniquely involved with STEM (Science, Technology, Engineering, and Mathematics). He is a member of several advisory boards at MIT and is a founding member of the TALENT program at IMSA.

 

Kalman Diagram—Moises Goldman

Portrait of Moises & Chicago Globe—John Jonelis

Other graphics—MS Office

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. Please perform your own due diligence. It’s not our fault if you lose money.
.Copyright © 2017 John Jonelis – All Rights Reserved
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POWER PITCH

by John Jonelis

What happens when you give kids—kids gifted in math and science—a real chance to bust out with their God given talents and excel?

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  • What if you trust them to lay their greasy little hands on equipment normally available only at elite universities?
  • What if you allow them to direct their own time?
  • What if you challenge them to construct their own goals and learn by themselves how to accomplish them?
  • What if you dare them to build real startup businesses at such a tender age?
  • And what if you throw them into a competition against a panel of critical judges from the real private equity world?

What happens? Good things! Good things happen! They happen here at IMSA – the Illinois Mathematics and Science Academy. I’ll give you an intimate peek at the inner works of this educational powerhouse so you can see for yourself what makes this one of the biggest success stories in the country.

Showcase – Chandra Gangavarapu

This is a high school with a serious entrepreneurship program. Many of the ideas, business models, and pitches produced here outshine what we’re accustomed to in the business world. Mere students, you say? Some of their companies have gained funding and gone to market. And many of these same students intern at real-world startups throughout Chicago.

According to Britta McKenna, Chief Innovation Officer at IN2, “Kids love to have real-world problems to actually work at. This space provides that opportunity.”

Today’s event is the grueling POWER PITCH. Each team presents its company twice before separate panels of judges—the finalists pitch three times.

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What Do the Judges Say?

The judges are all smiles as they feed at the idea bar after the first round. Competitors get whittled down by secret ballot. I corner John Lump. He’s a colleague at Heartland Angels and a professor at DePaul where I’ve lectured at his invitation on risk profiles in private equity. See IN YOUR FACE RISK.

This a practical guy who’s knee-deep in the real world of business as VP of Federal Home Loan Bank of Chicago. I can count on him for an honest opinion. Here it is verbatim:

John Lump — Judge

“I love being a judge here. Second year I’ve been doing it. And it’s exciting and a lot of fun. The enthusiasm and energy of the kids is just fantastic.”

Swelly – Tyler Stock

“I saw several interesting businesses.

  • Swelly is a temporary insurance company.
  • Blabl is a company to help students with speech disabilities.
  • Rethink Numeracy is one that helps students with Downs Syndrome learn math—a more visual approach.

Some really cool ideas here.”

Blabl – Ayan Agarwal

“Obviously these entrepreneurs are quite young. There are some still in Jr. High. You’re talking kids that are 10, 12, 13 years old and already starting businesses! At Heartland Angels, we see entrepreneurs in their 20s up to their 50s and 60s. So these kids need much more mentoring. But I think you’re going to see some business opportunities here.”

Rethink Numeracy – Akshaya Raghavan

I touch base with Moises Goldman. As I’ve said before, he’s an old hand at private equity in Chicago and a VIP here at IMSA. I’ve known him a long time, and trust what he says. He’s a guy that projects humility, but receives deference and respect.

Moises Goldman – Judge

Today Moises is bursting with exuberance and he speaks with more passion than I’ve ever seen. What he says is as intuitive and emotional as it is insightful.

“Two of these kids blew me away. The company is called Fast Exit. One brother is 12 and the other is 15. Twelve and fifteen! I looked at the father and just jokingly said to him, what is it that you do? These kids are very, bright. Very, very bright—both of them.

[Moises is talking about the Orr brothers, Joshua and Maxwell. The older brother is in 8th grade at Avery Coonley. They are each pitching their own companies today.]

“What blew me away was that they’re two brothers, so I look at the father and I just wonder, what are his challenges as a dad with these two amazing kids? Because the social environment that they have—it must be an alternative universe to the one that I’m used to—that I grew up in.”

Jim Gerry with Joshua Orr of Fast Exit

[I suggest to Moises that their home life must be very nurturing.]

“Yes, somehow. But I’m amazed. That really blew me away—that blew me away. Last year, the older boy had a drone project that was a game you could adapt to Dave and Busters in that kind of environment.”

[I recall that drone project and ask if they’re both planning to attend IMSA.]

“The 12-year old—I don’t know. The 15-year old is applying for the coming year.”

OneNote Quiz – Maxwell Orr

Today there are 17 judges at Power Pitch – Patrick Bresnahan, Dane Christianson, Moises Goldman, Joe Jordan, Sanza Kazadi, Christine Krause, Maria Kuhn, John Lump, Josh Metnick, Nancy Munro, Kelly Page, Jacob Plumber, Lance Pressl, Julia Sanberger, Chris Stiegal, Tom Voigt, Joe Zlotniki. I agreed to be an alternate and fortunately don’t get that tap on the shoulder. I want to see the whole event.

Shop Cheetah – Catelyn Rounds, Julian Kroschke

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Entrepreneurship

IMSA’s entrepreneurship program is called TALENT—Total Applied Learning for Entrepreneurship—led by Dr. Carl Heine, Britta McKenna, and Jim Gerry. Jim is technically retired from the program but still volunteers his time. This is too much fun to stay away.

Heat2Heal – Sushil and Pranav Upadhyayula

At this place, students get real-life experience and opportunities to solve real-world problems and bring ideas to market. The goal is to instill the thinking patterns and mindset of an entrepreneur:

  • Develop a product
  • Form a team
  • Communicate ideas
  • Formulate a business plan
  • Protect intellectual property
  • Work your network
  • Raise funding
  • Start the business

Really? These are high school kids—some even younger. In a world of schools dominated by gangs, drugs, and fear, who would think them capable of such positive desires and accomplishments? Then I come across one of the quotes on the wall:

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IMSA Fast Facts

  • Teaching philosophy – The Socratic approach. Self-directed learning and problem-based learning.
  • 99.8% of IMSA students attend college.
  • 70.1% pursue majors in science or math.
  • 47% of faculty is PhD.
  • Alumni hail from every district in Illinois.
  • This is the school’s 30th year.

The IN2 Entrepreneurship Center at IMSA

I snag Dr Carl Heine, as he moves between presentations. He’s director of IMSA TALENT, their entrepreneurship program. I ask him if IMSA still has a presence at 1871, the huge incubator in downtown Chicago, or if all the activity is at the new IN2 facility.

Dr. Carl Heine, Director of IMSA TALENT

“IMSA is still a member of 1871. We take our students on Wednesdays to intern at companies. They’re embedded in startup teams. We can’t teach a class that’s better than that.”

“We do it every Wednesday. 1871 is just one location. We have students at the James Jordan Foundation downtown. Three of them are interning there right now, working on summer curriculum. There are students at a variety of other spots, too.”

[“This year’s Power Pitch is better than I’ve ever seen.”]

“POWER PITCH is an event that makes people feel good about the future. I hope you feel that way as a result of your involvement.

“The top three high school teams are advancing to the Next Launch regional competition in Indianapolis on May 17. If you would like to continue to work with your favorite team as a thought partner, a mentor or more, the purpose of IN2 and TALENT is to make that happen.”

Yoda

[I decide that Carl is the Yoda of IN2. I ask him, “What other events are coming up?”]

“This has been an academy for 30 years now, so we’d like to have a celebration. We’ve put it on March 30th this year, so there’s a 30 and a 30. As part of that, we’re doing the ribbon cutting for the IN2 space, and the new science labs that are part of a capital campaign that just wrapped up as well. And we’re celebrating the accomplishments of the institution over the last 30 years.”

This is just brilliant!

IMSA trains students not to fear any subject. I noticed THEORY OF ANALYSIS on the course syllabus. Normally, that’s offered only at the university level and it’s a course that’s hated and avoided by math majors nationwide. Never be intimidated by difficult subjects.

Award Ceremony

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17 Student Teams

IMSA’s President, Jose׳ M Torres, and the Stephanie Pace Marshall Endowment present the awards.

The top three high school teams—Blabl, Heat2Heal and Flameless—advance to the Next Launch Regional Competition in Indianapolis on May 17. The two winning middle school teams are Fast Exit and Shop Cheetah.

Blabl– Ayan Agarwal

 

Social Good Category Finalists & Winners

  • BlablAyan Agarwal – A mobile application that engages speech impaired children in conversation with an avatar – $1000 prize, Top 3 HS team
  • Heat2HealSushil Upadhyayula, Pranav Upadhyayula – A hands-free, self-powered Arthritis Wrap that converts body heat into electricity to provide targeted massaging & heat therapy for stiff joints – $500, Top 3 HS team
  • Rethink NumeracyAkshaya Raghavan – Teaching numeracy to children with Down Syndrome, leveraging their learning strengths.
  • Double-CheckRishi Modi – A protective biometric alternative to prevent ID theft.

Heat2Heal– Sushil Upadhyayula & Pranav Upadhyayula

Social entrepreneurs create self-sustaining businesses that promote social good. The STEM category is for-profit tech companies.

Fast Exit – Joshua Orr

STEM Category Finalists & Winners

  • FastExitJoshua Orr – A life-saving solution for managing exit signs – $1,000 prize, middle school team.
  • Shop CheetahCatelyn Rounds, Julian KroschkeA groundbreaking store navigation system that saves times and routes customers through the store$500 prize, middle school team.
  • FlamelessSivam Bhatt, Nikhil Madugula – Extinguishing cooking fires automatically with sound waves – Top 3 HS team.
  • SwellyAneesh Kudaravalli, Tyler Stock – A mobile app that allows users to get flexible insurance on personal items in an instant.

Shop Cheetah – Catelyn Rounds & Julian Kroschke

 

Other Competing Teams

  • AlertAshritha Karuturi, Priya Kumar – An app that efficiently connects homeowners to rescue workers, saving time and lives.
  • Be BettahZoe Mitchell – The food search engine and cookbook series that allows for bettah nutrition without changing your lifestyle.
  • Electrofood Alex Orlov – A microbial fuel cell that converts food waste to electricity.
  • OneNote QuizMax Orr – The personalized quiz generator.

Flameless – Sivam Bhatt & Nikhil Madugula

  • SafeSeatElliott Cleven – An app to alert parents if their child is left in a car unattended.
  • ShowcaseChandra Gangavarapu – A web app for musicians and dancers to gain recognition for their art.
  • Social BreadVainius Normantas – Using social media advertisements to raise funding and awareness for communities in need.
  • StrobeJayant Kumar, Zaid Kazmi – LED light strip supplements for fire and carbon monoxide alarms to assist the hearing impaired.
  • Verifact!Shreya Pattisapu – An effective and efficient way to couter fake news.

 

Go to Part 1 – THE NAME IS IN2

Hope you enjoyed Part 2 – POWER PITCH

Read Part 3 – INQUIRY & INNOVATION

 

 

IN2 Contact Info

Address – 1500 Sullivan Rd. Aurora, IL 60506

Website – https://www.imsa.edu/

Carl Heine – heine@imsa.edu

Britta McKenna – bmckenna@imsa.edu

Tami Armstrong – tarmstrong@imsa.edu

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Photography by John Jonelis

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. It’s not our fault if you lose money.
.Copyright © 2017 John Jonelis – All Rights Reserved
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Filed under 1871, angel, angel investor, Chicago Startup, Chicago Ventures, Education, Entrepreneur, Entrepreneurship, Events, IMSA, Innovation, Innovation and Culture, Invention, investor, MIT, MIT Enterprise Forum, MIT Enterprise Forum Chicago, MITEF, MITEF Chicago, Social Entrepreneur, Startup, startup company, vc, venture capital

THINK FAST

Combat Brain Training T

Brain Tech – Part 3

Adapted from the Journal of the MIT Enterprise Forum – Chicago

John Jonelis

“I must’ve walked down that alley 100 times, but for some reason something told me I shouldn’t go down there.” But the Marine dismisses the thought and carries on with his mission. Next, he gets blown up.

The soldier’s intuition tells him to avoid the alley but his observation and cognition do not. Something is happening that he cannot account for. How can we fix this picture?

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The Speaker

Armed forces, professional athletics, and even business include crucial bursts of heightened stress and times of rapid change. Such times call for laser focus, situational awareness, and fast mental and physical reactions. We must process real-time data quickly.

New discoveries enable us to rev-up the processing power of our brains. Such training—recently used in the military—is now available to athletes, trading professionals, and business people.

The program is called PACEtmProgressively Accelerated Cognitive Exertion. Over 2,500 individuals, from Marine Snipers, Rangers, Recon and Special Operations Forces, Pilots, Professional Athletes, Business People, and sufferers from Brain Trauma have had their lives positively changed by this training. John Kennedy developed the program and claims that 100% of those have reported significant improvement in performance. A hundred percent!

John Kennedy

Mr. Kennedy’s comments are given before an audience of entrepreneurs, investors, and PhDs assembled at the MIT Enterprise Forum, Chicago.

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The Challenge

Kennedy tells of his call-to-action in 2006 when his brother came back from Iraq and said, “Those IEDs are killing us.”

So he went to IED training. IED survivors accompanied him the whole time, and that motivated him in a powerful way. Meanwhile, the Marines were independently looking for a solution to the problem.

“The Marines had already mapped-out processes,” he says. “The entire kill chain—all the way from motivation to boom. And the prevent chain. Very smart people were doing this. But for every innovation they designed to protect against explosives, the enemy found a way around it. That approach was too slow.”

Up to that point, decision-making science was based on what happened in the past. In a rapidly changing environment, there may not be enough time to think through all that information.

Recalling the story of the Marine in the alley, Kennedy postulates: “If a guy in the field can think better, maybe he can avoid the explosion.”

Combat Brain Training

Speeding up the Brain

What are the components of mental performance? Certainly, there’s learning and experience. According to Kennedy, Marines go through tons of training and over 900 learning objectives. But what is this phenomenon we call intuition? “It may simply be the act of processing information faster,” he says. “Everybody loves a faster computer. How can we do this for the brain?”

Physicists say it’s impossible for a Major League Baseball player to hit a fastball. Think of it: The bat swings at almost 100 mph. The ball comes at the batter at almost 100 mph. There’s no way that consciously, he can see the ball leave the pitcher’s hand and swing the bat in time to hit it. Yet batters DO hit fastballs with startling regularity. Coaches tell the batters, ‘Don’t think,’ because cognitive thought is too slow. When the ball leaves the pitcher’s hand, the subconscious takes over.

According to Kennedy, neuroscientists call this a Zombie System. If you repeat an action over and over again, you get to the point where you react subconsciously. It becomes a habit. Subconscious processing is faster than conscious analysis. “Excellence is a habit,” he says. “Conscious thinking is too slow.”

So Kennedy set a goal: “To make the brain act on real-time data as quickly as on memory.”

The ultimate result is what he calls Cognitively Primed Anticipation. Instead of being overwhelmed, the brain becomes so fast that it’s waiting for information to come in. “We’re working more and more off the Zombie System in the subconscious,” he says. “Freeing cognitive functions to deal with change.”

The marine, going though that alley time after timenow his brain is ready to anticipate more information; he’s effectively using more real-time data. Maybe he notices there aren’t the usual kids in the road any more. The dogs are away. There’s more trash that could be hiding an IED. He’s not confused by his intuition any more—it’s become a cognitive tool for him.

More detail on Kennedy’s program coming in Part 4 of this series.

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GO TO PART 4 – THINK LIKE A ZOMBIE

GO TO PART 1 – WHAT MAKES INNOVATION

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Contacts

MITEF Chicagohttp://www.mitefchicago.org/T MITEF

John Kennedy – Combat Brain Training 

www.combatbraintraining.com

1022 Greenleaf, Evanston, IL 60202

847-791-19825  john@combatbraintraining.com

Photo credits – John Kennedy

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Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. It’s not our fault if you lose money.

.Copyright © 2014 John Jonelis – All Rights Reserved

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1 Comment

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