Showing posts with label Agile Enteprise. Show all posts
Showing posts with label Agile Enteprise. Show all posts

Saturday, January 28, 2017

Hurricanes and an Architecture for Process

The idea for this post came from a previous post on this blog regarding enterprise architecture and religious organizations.

Definitions or Definitional Taxonomies

There are three definitions that are needed to understand this post; the definition of Architecture, process using the OODA Loop, and the Hierarchy of Knowledge.  These are somewhat personnel definitions and you may interpolate them into your model universe.

Architecture

Architecture—A functional design of a product, system, or service incorporating all the “must-do” and “must-meet” requirements for that product, system, or service.

OODA Loop

All processes supporting the mission, strategies, or infrastructure of any organization fall into the OODA model of Col. John Boyd.  The OODA, as discussed in several previous posts includes four steps: Observe, Orient, Decide, and Act.  I will discuss this shortly (below) using the example of the prediction of a hurricane.

A Taxonomy for the Hierarchy of Knowledge

I defined the following taxonomy of knowledge based on much reading and some thinking.  I will demonstrate what I mean for each definition by using it in the appropriate place in my example of the hurricane prediction.
Datum—some observation about the Universe at a particular point in four dimensions
Data—a set consistent datum
Information—patterns abstracted from the data.
Knowledge—identified or abstracted patterns in the information.
Wisdom—is the understanding of the consequences of the application of knowledge

Process Architecture and Forecasting Hurricanes

Since the process for predicting or forecasting hurricanes is most likely to be familiar to anyone watching weather on TV, it is the best example I can think of to illustrate how the OODA Loop process architecture works with the taxonomy of knowledge.

Observe

Initially, data is gathered by observing some aspect of the current state of the Universe.  This includes data about the results of their previous actions.  In point of fact,
Datum—some observation about the Universe at a particular point in four dimensions
Data—a set consistent datum
Obviously observations of current temperature, pressure, humidity, and so on, are basic to making weather forecasts, like the prediction of a hurricane.  And each observation requires latitude, longitude, height above sea level, and the exact time to be useful. So one datum, or data point would include, temperature, latitude, longitude, height, and time.
When the temperature is measured at many latitudes and longitudes concurrently, it produces a set of temperature data.  If other weather measurement, like pressure and humidity, are taken at the same locations at the same time, then you have several data sets with which to make a forecast (or a composite weather data set for a particular time).  Because this is a recurrent measurement process, the weather folk continue to build a successively larger composite weather data set.  But large data sets don’t make a forecast of a hurricane.

Orient

The Orient step in the process is inserting the new data into an individual’s model of how the world (Universe) works (descriptive) or should work (prescriptive).  These models are sometimes called paradigms.  Rules from Governance enable and support the Orient step, by structuring the data within the individual’s or organization’s model.  Sometimes these model or paradigms stick around far after they have demonstrated to be defective, wrong, or in conflict with most data and other information.  An example would be the model of the Universe of the Flat Earth society.
Information—patterns abstracted from the data.  This is the start of orienting the observations, the data and information.  Pattern analysis, based on the current model converts data into information is derived from the organization’s model of its environment or Universe.  For hurricane forecasting this would mean looking for centers of low pressure within the data.  It would also include identifying areas with high water temperatures in the temperature data, areas of high humidity, and so on.  This and other abstractions from the data provide the information on which to base a forecast.  But it is still not the prediction of a hurricane.
Knowledge—identified, combined, or abstracted patterns in the information.  Using the same paradigm, environmental model, or model Universe, people analyze and abstract patterns within the information.  This is their knowledge within the paradigm.  In weather forecasting the weather personnel uses the current paradigms (or information structures) to combine and abstract the knowledge that a hurricane is developing.
When they can’t fit information into their model, they often discard as aberrant, an outlier, or as an anomaly.  When enough information doesn’t conveniently fit into their model the adherents have a crisis.  In science, at least, this is the point of a paradigm shift.  And this is what has happened to weather forecasting models over the past one hundred and fifty years.  The result is that the forecasting has gotten much better, though people still complain when a storm moves off its track by fifty miles and causes unforecast wind, rain, and snow events.

Decide

Once the organization or individual has the knowledge, he or she uses input their knowledge within their models of the Universe to make decisions.
Wisdom—is the understanding of the consequences of the application of knowledge. 
This is the hard part of the OODA Loop because it’s difficult to understand both the consequences and the unintended consequences of a decision.  If your paradigm, environment, or Universe model is good, or relatively complete, then you’re more likely to make a good decision.  More frequently than not people make decisions that are “Short term smart and long term dumb.” 
Part of the reason is that they are working with a poor, incomplete or just plain wrong paradigm (view of the world or universe).  This is where the Risk/Reward balance comes in.  When choosing a path forward, what are the risks and rewards with each path?  [Sidebar:  A risk is an unknown and it is wise to understand that “you don’t know what you don’t know”.]  For weather forecasters it’s whether or not to issue a forecast for a hurricane.  To ameliorate the risk that the are wrong, weather forecasters have invented a two part type of forecast, a hurricane watch and a hurricane warning. [Sidebar: It’s split more by giving a tropical storm watch and warning.]
The reason for this warning hierarchy is that the weather forecasters and services are wise enough to know the public’s reaction to warnings that don’t pan out and lack of warnings that do; they understand the risks.  So when they give a hurricane warning, they are fairly sure that the area they have given the warning for will be the area affected by the hurricane.

Act

Once the decision is made people act on those decisions by planning a mission, strategies, and so on within their paradigm.
For governments and utilities in the U.S. this means putting preplanned hurricane preparations into effect.  For people this generally means boarding up the house, stocking up on food, water, and other essentials or packing and leaving.  And for the drunk beach comber this means grabbing the beers out of the frig, and either heading to the hills or back to the beach to watch the show.

Programmed and Unprogrammed Processes

In the 1980s I wrote a number of articles on process types.  After doing much research and much observation, I came to the obvious conclusion that there are two types of processes, Programmed, and those that I will call Unprogrammed and which includes design, discovery, and creative processes. [Sidebar: These three sub-types differ in that design processes start from a set of implicit or explicit customer requirements, discovery processes start from inconsistencies in data or in thinking and modeling the data, and creative really have no clear foundation and tend to be intuitive, chaotic, and apparently random.] 

Programmed Processes

Programmed processes are a set of repeatable activities leading to a nearly certain outcome.  Almost all processes are of this type.  The classic example is automobile manufacturing and assembly.  Since they are repeatable how does the process architecture model apply?
The short answer is to keep them repeatable and to increase their cost efficiency (that is making them less expensive in terms of time and money to create the same outcome).

Keeping Programmed Processes Rolling

To keep your truck or car operating requires maintenance.  How much and when is an OODA Loop process.  For example, you really should check your tires, both for wear and pressure regularly; otherwise the process of driving can become far too exciting.  So you are in the “observe” step.
As the tires wear out or lose pressure too often, the data set becomes information triggering the “orient” step in the process.  At this point a driver starts to gather data on which tires are wearing fastest and where on the tire they are wearing.  This last point may indicate that tire rotation is all that’s needed.
Based on this data our driver models the information (using the computer between his or her ears) to determine how much longer it’s safe to drive on the tires.  Based on results of that model, the driver will “decide” to buy tires, rotate tires, or wait a little longer.  [Sidebar: Actually, many drivers will go through the buy/wait decision based on additional data, the cost of new tires, and their budget.]  The driver will then “act” on the decision, either get new tires or wait (which is really an action).
The point here is that like everything else in our Universe, over time, everything breaks down; so repeatable processes require an OODA Loop process to maintain them.

More Cost Efficient

However, the OODA Loop process architecture elucidated here is important for programmed processes for another reason.  For repeatable processes the key OODA process is always how to make the faster, cheaper, or making a higher quality product at the same or lower price, and producing it in the same or less time.
This is famously what Adam Smith described in his pin example in the first chapter of “The Wealth of Nations”. By creating an assembly line process that he called “the division of labour”, he demonstrated that the same number of workers produce hundreds of more pins.  He went on to describe that each worker might now invent (or innovate, that is, refine or enhance) tools for that worker’s job. [Sidebar: Henry Ford went on to prove this in spades or should I say Model-T’s.]  [Sidebar: To me the worker’s inventing or innovating tools to help them in their job is quite interesting and often missed.  Tools are process or productivity multipliers.  In the military they are called force multipliers; you always want your enemy to bring a knife to your gunfight, because a rifle multiplies your force.  Likewise, the tooling in manufacturing can increase the quality of the product, the uniformity of what is produced, while reducing the cost and time to produce…fairly obvious.]
Both the “division of labour” and the creation of tooling require the use of the Architectural OODA Loop, which means that increasing the cost efficiency of manufacturing uses the OODA Loop with the knowledge taxonomy.

Unprogrammed Process

Unprogrammed processes have stochastic (creative and unplanned activities within them).  There are really three sub-types of unprogrammed processes, design, discovery, and creative. The key differences between the design, discovery, and creative processes are the whether the process has customer requirements driven and what the requirements are.

Design

The design process has customer requirements.  [Sidebar: As I’m using it, the design process also includes custom development, implementation, and manufacturing.]  It uses a semi-planned process, that is, program or project planning creates a plan to meet the objectives, but with latitude for alternative activities because there is significant risk.  The actual design activities within the programmed process are stochastic, from a program management perspective.  That is, the creative element of these activities makes less predictable, and therefore with programmatic risk with respect to cost and schedule.  Therefore, program management must use (some form or) the OODA architecture to manage the program or project.
The stochastic activities are themselves OODA Loop processes.  The designers have to identify (observe) detailed data of the functions they are attempting to create (the “must do” requirements), while working to the specifications (the”must meet” requirements) for the product, system, or service.  The designers then have to “orient” these (creating a functional design or architecture for the function), “decide” which of several alternate proposed designs is “the best”. Finally, they “act” on the decision.

Discovery

The requirements for research, risk reduction, and root cause analysis are generally unclear and may be close to non-existent.  One of my favorite research examples, because it’s well known, and because it so clearly proves the point is the Wright Brothers researching and developing the aircraft.  In 1898 the brothers started their research efforts.  Starting with data and information then publicly available they built a series of kites. With each kite, they collected additional data and new types of data.  They then used this to reorient their thinking and their potential design for the next kite.  They found so many problems with the existing data that they created the wind tunnel to create their own data sets on which to base their next set of designs.  By the end of 1902 they had created a glider capable of controllable manned flight and by 1903 they created the powered glider known as the Wright Flyer.  It took them at least two more cycles of the OODA Loop to develop a commercially useful aircraft.
Risk reduction also uses the OODA Loop.  A risk is an unknown.  It requires some type of research to convert the unknown into a known.  There are four alternative.  First, the project/research team must decide whether or not to simply “accept” the risk. Many times the team orients the observed risk in a risk/reward model and accepts the risk.  However, another to orient is to determine if there is knowledge or knowledgeable people to convert the unknown into a known. So “transferring” the risk is one way to reduce the risk.  A second method is to “avoid” the risk.  This means redesigning the product, system, or service, or changing the method for achieving the goal or target.  The final way is to “mitigate” the risk.  This is nothing short of or more than creating a research project (see above) to convert the unknown into a Known.
Likewise, root cause analysis is a research effort.  However, the target of this analysis is to identify why some function or component is not working the way it is supposed to work.  Again, its observing the problem or issue, that is gathering data, orienting it through modeling the functions based on the data, deciding what the cause is or causes are for the problem and how to “fix” the problem, and then acting on the decision.  Sound a whole lot like the OODA Loop.

Creative

Creative processes like theory building (both through extrapolation and interpolation), and those of the “fine arts” that come from emotions also use the Architecture of Process defined in this post.  For some theories and all fine arts, “the requirements” come from emotion, based on an intuitive belief structure [Sidebar: a religious structure, see my post on architecture of religion].  This intuitive structure provides “the data, information, and knowledge” on which the creativity builds.
However, for scientific theories, at least, they are sometimes based on inconsistencies in the results of the current paradigm.  The theorist attempts to define a new structure that will account for these aberrant data.

Why make a Deal about the Obvious?


To many it might seem that I’m making a big deal about what is obvious.  If it is the case, why hasn’t it been inculcated into enterprise architecture and used in the construction and refinement of processes and tooling to support the charter, mission, objective, strategies and tactics of all organizations?  Using formal architectural models like the architecture for process, presented in this post, will enable the enterprise architects to “orient” their data and information more clearly making Enterprise Architecture that much more valuable.

Tuesday, January 10, 2017

Enterprise Architecture, Systems Engineering, and Regulations: Process Rudders or Process Brakes


Regulations: The “Must Meet” Requirements

Regulations directly affect all organizations, products, systems, and services. Further, they can be a rudder guiding the organization or a brake causing the organization to stop making any progress in meeting its charter, goal, or in completing its mission.  This post discusses laws, rules, specifications, standard, regulations (or simply regulations) as a part of any enterprise architecture or systems engineering effort.

The Customer Requirements Identification and Management tool that I’ve developed, CARRMA®, uses the concept of Must Meet requirements to store both the regulations and the metrics for meeting the regulation.  If more than one project has a particular regulation imposed on it, the CARRMA®’s data store will allow for reuse.

Regulations the rudders of an organization

Any commandment, law, rule, specification, standard, or regulation creates process friction, by its very nature.  It inhibits what can be done or defines what must be done. For example, saying “Thou Shall not Kill” means that it’s not nice to end a vehemently intense discussion by bouncing your opponent “six feet under”, though that might be very satisfying at the moment.  That is, killing is not a good solution to an intra-group disagreement since it doesn’t promote understanding, knowledge and therefore value growth of the group and doesn’t instill trust with other groups.

Hoping that I’ve made the point that regulations curb action or ensure action, by an over-the-top example, a regulation acts like a rudder, making it difficult for a process and thus a strategy to go one way, thereby making it easier to go another.  This, in turn, may directly affect the organization’s charter, mission, or goal.  In any rational system it should enable both the charter/mission/goal and the strategies and processes for achieving these.
Fortunately or more importantly, unfortunately systems and organizations built by humans are not entirely rational and sometimes not rational at all.  If the economy is the engine that powers the ship-of-state in an organization, then each commandment, law, rule, specification, standard, or regulation enacted is a rudder with its own wheel guided by part of the crew steering the organization toward their own Avalon.

Arrow’s Paradox and Catch 22s

At some point the number of rudders pointing at all points of the compass are such that the organization be it private or a ship-of-state either comes to a complete halt or turns in tight circles.  The rudders have formed a damn that effectively stops all forward progress of the organization, which no amount of churning by the organization’s economic engine can overcome.  Some of these regulation rudders are small and some are very large.  Twist the large ones hard and the ship brakes to a crawl and it may not turn at all. 

Arrow’s Paradox

A bigger problem is that too many regulation rudders will simply cause the organizational ship to stop and not make any of the ports.  Dr. Kenneth Arrow’s is known for “Arrow’s Impossibility Theorem” [Sidebar: For which he won the Nobel Prize], which is also known as Arrow’s Paradox.  He demonstrated mathematically that if an organization has three or more goals that they want to optimize, they will be able to only optimize on two (or I suspect they can sub-optimize on all three).

The point here isn’t that organizations can’t have more than one goal or objective; it is that if the organization attempts to define more than two (or maybe three) objectives using the “policy/regulation” strategy, the organization will slow down, wobble around, and achieve none of the objectives.

If you add in that in a democracy the goals and objectives change as controlling constituencies change, normally you end up with more and more laws, regulations, rules, and standards each attempting to use its regulatory rudder to change the course of the ship-of-state to reach the objective for which it was enacted.  The net result is that either the ship-of-state will end up on the rocks or going in circles.

From personal experience with federal contracts and from a recent DoD report, I can illustrate the problem.  One goal, which probably should be the only goal of DoD contracting, is to provide the most effective weapons in the world for the US Military.  That is, the weapons should be the greatest force multiplier.

However, the contracting office is faced with a second objective (a second rudder) of acquiring these weapons cost efficiently.  There are two metrics for cost efficiency, the initial cost (including research, development, and construction), and life-cycle costs (maintenance, upgrades, and disposal).  The question for the contracting officer is, “Do you contract for the cheapest initial cost product or for the one that will cost the least over the product’s projected lifespan?”

Then there is a third rudder in the form of the dependability of the product, system, or service. “Dependability encompasses all of the “illities”, including reliability, maintainability, serviceability, and so on.  Each of these has metrics and standards that must be met.  In some cases the metrics for the standard or policy is either untestable in a timely manner or in a few infeasible or impossible to meet.  All of these rudders will force addition time and expense into the effort.

A fourth rudder is reconfigurability and upgradeability of the product, system, or service.  Before the US Civil War, the rate of change of weapons and support systems was such that weapons and weapons systems had no need for this “Must Meet” requirement/policy.  The weapon would be worn out long be the technology changed.  However, since then it’s obvious that technology has and is continuing to accelerate (to the point that for many systems, they must be upgraded before their development and implementation is completed).  These continue to increase the initial design costs. [Sidebar: Services Oriented Architecture can reduce these costs greatly for IT systems, and modular systems/product can do the same for hardware of all types.]

A fifth rudder, and first one that is politically/social motivated as well as costly is the implied policy that all congressional districts and states should have jobs related to weapons and intelligence system development, especially where the senator or representative sits on committees dealing with budgets and military programs.  A recent DoD study has shown that this can add 20 to 25 percent to the cost of a product, system, or service for the DoD.
Then comes the politically motivated socially liberal welfare policy rudders (those intended to regulate social welfare and social change).  For weapons and intelligence tools, these require that a certain percent of the work on the product be from female owned companies and another percentage be from “minority” owned businesses.  [Sidebar:  The social actives’ idea was that the only way these groups could break into DoD contracting was through regulation.  I think they were correct because most of the work they did that I observed over the 25 years I was associate with government contracted engineering demonstrated beyond a doubt that they were incompetent to compete with a level playing field.  Many times the prime contractor had to supply the engineering capability to complete the job over schedule and way over cost.]  While it isn’t Politically Correct to attempt to define how much money was spent on this contracting welfare, from personal experience I expect that it is very significant.

The point of this section is not to discuss the problems with the regulations and informal policies of DoD contracting, rather it’s to demonstrate that as more laws, policies, regulations, business rules, standards, and so on (the “Must Meet” requirements) are imposed on a program, especially, extraneous ones, that both the effectiveness of product and the cost efficiency of the project or program are reduced.  And at some point there are so many “Must Meet” requirements that the effort, even at the enterprise architectural level will fail.

Catch-22

The extreme case of Arrow’s Paradox is the famous Catch-22 where two regulations are diametrically opposed leaving whatever effort, project, program, organization, or enterprise going in circles and making no progress in any direction. Even with a ship-of-state the size of the United States (which is a supertanker sized economy), given enough Catch-22s and nothing will get done; too many steersmen, too many rudders, and too many goals (targets, harbors, or whatever).

A good current and everyday example of regulatory Catch-22 is deicing roads.  Having icy sidewalks can be very exciting and occasionally lethal—so it really is not a good thing.  So deicing the sidewalks is mandatory.  Deicing calls for the use chemicals like sodium chloride (salt).

The problem is that there are regulations (must meet) requirements for the use and storage of “salt” because it “pollutes the environment” (and it does, you should see my grass near the sidewalk and road).  So you must use chemicals to save lives but you must not to save the environment.  Two regulatory “must meet” requirements (rudders) are in opposition, one to save lives and one to save the environment.  This is a small example of a big problem that can and will bring the economic ship-of-state to a dead stop.

Reducing the Number of Regulatory Brakes but Keeping the Rudders

To get any organization to at least head to a goal it should be clear that removing internal policies that interfere with the attainment of the goal is necessary.  For large organizations with many sub-organizations, the issue becomes one of identifying which regulations guide the organization in the direction its charter, goal, or mission state and which are braking it to a stop.  For many organizations, but especially democratic style governments, there will always conflicting goals and missions and therefore conflicting regulations.  So how should a large organization or government determine which are rudders and which are brakes?
To my mind, this is a good place to apply Enterprise Architecture and the architectural model that I set out both in my book and in this blog.  The nice thing about that architectural model is that it can start as a static model that can be used to identify customer requirements and end up as a dynamic model of the enterprise (even the Ship-of-State).  As such, it can identify policies that are braking or causing bottlenecks in the processes enabling the strategies for attaining the goal or mission.  Until you can dynamically model the enterprise, you will never really be able to identify the unintended consequences and negative externalities of any policy, standard, or regulation.  Nor, as the goal or mission changes can you identify those policies, standards, or regulations that truly impede progress in the changed direction (though many politicians in the organization will be able to tell you, or so they believe).

For those policies and standards internal to the organization, the leadership should be able to understand which regulations support the organization’s strategies and process and which don’t.  Additionally, the leadership can propose changes, deletions, and new regulations, which the enterprise architect can then model to determine the likely consequences, both intended and unintended.  Once the enterprise architects have oriented the changes the leadership proposes [Sidebar: See the OODA loop] the leadership can then choose what internal policies, standards, and regulations to change and which changes to implement with a much lower risk while seeing the their organization move more quickly toward achieving its goal.  [Sidebar: The modeling will also show where leaders and managers of sub-units are working on their own agenda which might or might not be steering toward the overall goal.  Remember the Systems Engineering axiom, “Optimizing the sub-systems sub-optimizes the system.”]

For governments, especially for the legislative branch, architectural modeling is particularly important both to determine conflicting laws, regulations, rules, standards and codes.  If, as the architectural models mature and their predictions help to make better decisions, there may even be fewer vehemently intense discussions about which laws, regulations, rules, standards, and codes to enact and which to remove or rewrite…Interesting.

Monday, January 2, 2017

If You Want to Create an Enterprise Architecture; Don't!

One of the last presentations I made as an Enterprise Architect for a major DoD contractor was to the Chief Architect of the US Veterans Administration.  I walked in with a fully prepared presentation that was to take about 10 minutes of the time allotted to our team only to find the Chief Architect cutting the presentation off with a question, "How do we go about creating an IT architecture for the VA?"  Even though I had a very good answer and had applied it on a couple of occasion, my mind blanked.  I want to share with you his problem and the answer I should have given.

The Problem
The problem that the Chief Architect of the VA has is the same problem that plagues CA's of all large organization and most of medium and smaller organizations.  That question is base on the very logical idea very much the analog of the idea that before you start changing the plumbing, you should know design of the current plumbing; that is, before you can create a "to be" or "next step" architecture you need to have a "current architecture".  Obviously, if you don't know which pipes connect where and start making changes to the plumbing you could end up with some very interesting and exciting results for which you may need to call your insurance company.  Likewise, if you want to improve the effectiveness and/or the cost efficiency of the organizational processes and information systems, most Enterprise Architects assume they must first define and delimit the "as-is" processes and information systems for the organization.

The conundrum is that, in today's technological environment, by the time an IT architecture team has mapped out (structured and ordered) an "as is" architecture, some, most, or all of the elements and data of the architecture will be obsolete and out of date.  For something as large as a major corporation, a department within a state or the federal government, the cost and effort involved would require a tour de force on a very large perhaps unprecedented scale.  This cost and level of effort would be such that the senior management would cut funding to the effort as a waste of time and money, since having an "as-is" architecture by itself produces little in value to the organization.

As can be found in the literature, there are many ways to "solve" or at least ameliorate the problem of creating an "as-is" architecture.  For example, one of the best, that almost works, is to chop the organization into its components and create an "as-is" architecture for each component separately.  Then try to stitch the architectures together.  I've tried this and it works up to a point.

There is a truism in Systems Engineering, Systems Architecture, and Enterprise Architecture, "Optimizing the sub-systems will sub-optimize the system".  I have demonstrated this to many people many times and experienced it several times.  But this is crux of the problem for those that try to create an Enterprise Architecture for a large organization.

The Solution
The simple answer is "Don't".  That is, "Don't attempt to create an "as is" architecture for an organization, especially a large organization, because it will create itself with the proper procedures in place.  So how would I do it?

1.
 Define, delimited, and structured an initial set of classes and attributes for the Organization's Enterprise Architecture.  These should include:
  • Its Charter, Mission, Goal
  • Its Strategies for achieving its charter, mission, or goal
  • Its Processes supporting its strategies
  • Its Tooling and infrastructure
  • Its Governance that affects any of the above, including:
  • Internal Policies and Standards
  • External Regulations and Standards
I worked with one Enterprise Architecture database that had over fifty classes, each class with ten or more attributes.  This was a fairly mature architecture.  My recommendation, don't try to think of all the classes you may need or all of the attributes for each class; that's way over thinking.  Instead, start simple and add through the cycles

2. Once you have designed and structured the initial set of classed and attributes, create a data base structured according to the design.

3.
 Here is the key to creating an "As-Is" Architecture by not creating it...Huh?  Design and implement processes to capture the current state of strategies, processes, and tooling/infrastructure as part of review of funding for revision and upgrades to the current systems and processes.  

4.
 When personnel in the organization propose a project insist that these personnel demonstrate the value of the process or procedure that they intend to update or upgrade. The "value" would include demonstrating which of and how the current product, system, or service enables the processes, strategies, and charter, mission, or goal of the organization. My experience has been that the initial attempts will be fuzzy and incomplete, but that as the number of proposed projects in the database (which is generally called the Asset Management System and on which the "as-is" architecture is built) increases both the completeness and clarity of the current enterprise architecture will increase.

The reason I say "Don't" try to create an "as-is" architecture is that
 every 3 to 7 years every component of the organization's information system will need replacement.  This means that within 3 to 5 years simply by documenting and structuring the inputs from all of the efforts the organization's "as-is" architecture will be synergistically created (and at minimal cost) [Sidebar: There will be some cost because the project proposers will need to think through how their current charter, mission, or goal and the strategies they support links to and supports the overall charter, mission, or goal of the organization.  This is not necessarily a bad thing.]  For large organizations, no matter how much time or effort is put into attempting to create an "As-Is" Enterprise Architecture, it will take a minimum of a year and a great deal of funding; so it simply makes no sense.

As this Enterprise Architecture evolves you will begin to see a number of things that managers want to obfuscate or hide completely.  For example, a number of processes and component or sub-organizations will be demonstrated to be obsolete.  In this case obsolete means that the process or component organization no longer supports any of the organization's strategies or its goal.  Since managers want to build or at least keep their fiefdoms they will not appreciate this much.  Additionally, it will demonstrate which internal policies, regulations, and standards help the organization and which hurt it in meeting its goal.  Again, the gatekeepers of these policies, regulations, and standards will object--strenuously.  

But there are two more insidious problems that a good "As-Is" Enterprise Architecture will reveal, nepotism and the famous "Catch-22s".  

Nepotism
Nepotism in this case is more broadly defined than what most people think of as "nepotism".  In the sense I mean, nepotism can include creating a non-level economic playing field. In all large organizations, but especially in the U.S. Federal government (probably in all governments) the type of nepotism I’m identifying is rampant.  In fact a December 2016 report from the Department of Defense highlights what most federal employees and DoD contractors have known for years, because representatives and senators will only vote for a large program if their district or state gets a part of it, the DoD estimates that the cost of the program increases approximately 20 percent.  This is "jobs welfare" on a massive scale.  Some major defense contractors have plants in every state for just this reason, not because it make any sense from a cost efficiency perspective.  Further, Congress had passed laws to ensure that minority and female owned businesses.  The reason is that minorities and women scream that the good old boy network doesn't allow them to compete for sub-contracts [Sidebar: Actually the reason for the "good ole boy" network is that the prime contractors have sub-contractors that actually know what their doing.  In my experience, many times primes will "encourage"--read subsidize--inexperienced and frequently incompetent minority and female owned businesses in order to meet these regulations imposed on their proposals.]  Again, this is a form of social welfare to ensure all political constituents that scream loudly are appeased.  This adds up to the DoD being one of the larger governmental welfare organizations. [Sidebar: While, seemingly, I've picked on government organizations, especially the U.S. DoD, and while I have found that all governmental organizations in a democracy will have this type of nepotism.  This is what lobbing is all about.  Only when it goes so far that it's plain to all and when it's not openly enacted into law that we call it graft and corruption.]  And it's not only governments that suffer from this type of nepotism, all large organizations have the same problems, though generally on a smaller scale.  For example, sometimes the nepotism is written into union contracts.  Along with finance engineering, the auto industry in Detroit suffered a near collapse due to contractual nepotism.

This presents a problem for any Enterprise Architect.  The as-is architecture will highlight the nepotism of this type more clearly than any report.  The Enterprise Architect won't need to report it to the management, it will be self-evident.  I've experienced a situation, as I suspect many of you have, where the management kills the messenger in order to not address the problem.  In my case, three times I've been chased off programs when I reported that the effort was subsidizing silliness.

Catch-22
The second significant problem that policies, regulations, and standards become contradictory to each other or in combination make it impossible for the organization to achieve its goal.  Again, a good enterprise architecture will highlight these, though frequently, when management from one generation of technology with its set of policies and standards, finds the next upon them, they will refuse to resend or modify the existing regulations, preferring instead, again, to kill the messenger.  So like Systems Engineers, I've found that enterprise architects are only respected by other enterprise architects.

5.
 When the development and implementation team completes a project, and once it goes into operation, then as a final step in their effort, they should review the data they gave to the enterprise architect, revising the data to accurately reflect the "as-built" instead of the "as-proposed".  The as-built documentation must include all component, assembly or functional, and customer acceptance testing, and all post production required changes.  This documentation will inevitably lead to additional class attributes of the Asset Management System and structure in the enterprise architecture.

6.
 As the Asset Management System and the Enterprise Architecture matures, management should prepare for a paradigm shift in the way projects and other efforts are proposed.  This is where Enterprise Architecture really demonstrates how it can make the organization both more effective and cost efficient.

A mature enterprise architecture can serve as the basis for a dynamic business or organizational process model for the organization.  Management can use this model to identify obsolete processes, (and as discussed) policies, regulations, and standards; ones that the organization should eliminate.  Additionally, with the help of the Enterprise Architect, management can identify missing or inhibiting processes and tools, and identify bottlenecks and dams in process flows.

Further, they can model what happens when the missing and inhibiting processes and tools are added or when the bottlenecks are eliminated or reduced.  This modeling will then indicate where there is a need for new efforts and to some degree the effectiveness and cost efficiency of such efforts.  It's a paradigm shift in that no longer to component or sub-units of the organization propose changes.  Instead, senior management working with the Enterprise Architect and the component or sub-units will identify and fund efforts.  They now have a way to measure the potential of the change in meeting the organizational goal, which means senior management has a better way of managing organizational change.

Finally, once management has identified targets for change or upgrade, the enterprise architect together with a system architect can define alternatives to meet the effort's requirements.  They can model alternative process and tooling changes to forecast which has the lowest potential risk, the highest potential return, the least disruption of current activities, lowest initial cost, lowest lifecycle cost, the most adaptable or agile, or any number of other targets defined by the senior management.  This will make the organization much more cost efficient, and perhaps more cost effective; and this is the purpose of Enterprise Architecture,

To sum up, using this six step, high-level process is an effective way to create both an Asset Management System (an "As-Is" Architecture) and an effective Enterprise Architecture process; perhaps the only way.  


Friday, December 2, 2011

Economies of Scale or Economies of Knowledge?

This Post is of an unpublished paper I wrote in 2008 and 2009.  Dr. Chris Marai helped me by commenting and proposing edits.  The concepts it presents and some sections of the writing I subsequently used in my book, Organizational Economics: The Formation of Wealth.  I think it may be of interest.  If there are things with which you don't agree, please comment in the box below this post.  Bob

The Fiction of Economies of Scale and Barriers to Entry[1]
Robert S. Ellinger Ph.D.

Abstract

The global economy is on the threshold of a change in the structure of industrialization, from mass production to mass customization, whose root cause is the exponential growth of knowledge and the unprecedented ability to store, and communicate this knowledge.  While, a number of leading business and economic thinkers have predicted this change, and while the precursors of this change are already self-evident to many.  The present fluctuations and perturbations of all of the commodity, stock, and financial markets may well be an example.  Firms and other organizations that ignore or miss this new reality will not thrive over the next ten years and may not survive.
There are two ways that growth of knowledge is causing this structural change; by removing economies of scale and barriers to entry, and by creating a collaborative and technology savvy generations, that expect repetitive and non-thinking jobs will be performed by automation.  However, currently, proponents of many mergers and acquisitions and consolidation of industries base their mergers on the twin concepts of economies of scale and barriers to entry.  In today’s global and knowledge-based economies, these concepts are fictional.  While both economies of scale and barriers to entry are real with a constant a given level of knowledge, economies of scale only exist for a given level of knowledge and that as the knowledge increases the economies become diseconomies; barriers to entry function in the same manner.  Further, for the Generation X and Y with their use of technology including the Internet’s collaborative environment, these economic and business cultural concepts will appear as fiction.
The implications of the change in status of economies of scale and barriers to entry from near religious economic axioms to fiction are major.  For example, many more generation X and Y will own small firms, rather than working for large firms.  These small firms will sell innovative products and services.  While the current economic strategy of major corporations is buying entrepreneurial firms to survive, this strategy will become a difficult strategy to execute because the small firms will not be for sale.  Instead, consortiums of small firms will execute large programs and because of automating most of the house keeping (or cost of doing business) functions and because of inter-organizational international standards, they will out-compete the major corporations on quality, cost, and schedule.  For firms embracing this new paradigm there are eight recommended change strategies to enable them to survive and thrive in this new culture and environment.

“Current Shock”

In 1970, A. Toffler in his book “Future Shock” argued that society was, and is, undergoing a revolutionary transformation from the “industrial society” to what he termed a “super-industrial society.”[2]  Further, he argued that this change would overwhelm people, with the accelerating rate of technological and social change leaving them disconnected and suffering from “shattering stress and disorientation,” which he terms “future shocked.”
The paper will discuss two effects of this revolutionary transformation, a fundamental change in economic theory and a shift in culture.  It will then describe how these effects will cause change in the structure of firms and industries.  Finally, it will recommend strategies that will enable firms and other organizations to cope with this transformation.
The fundamental change in economic theory is that two tenets of microeconomics, economies of scale and barriers to entry increasingly are becoming fictional.  The paper will argue that while both concepts are valid as long as the knowledge-based remains constant, once the knowledge-base starts expanding at a rapid rate, the barriers to entry become knowledge barriers to entry and economies of scale become economies of knowledge.
The fundamental change in culture is from regional cultures to global generational cultures caused by the growth of knowledge and the resulting growth in technology.  Until the end of WWII, cultures were solely regional; that is, there was the Far Eastern, the Islamic, the Western European, and so on, cultures.  Each could be mapped with core and peripheral areas, and each was easily sub-divided.  However, since 1945 culture is becoming much less regional and much more generational; that is, the Boomer, the YUPPIE generations, and Gen X and Gen Y.  These cultures occur globally, rather than regionally and are stratified along their acceptance of and acculturation to technology.  Now, 7 and 8 year olds have avatars meet in a virtual club house on the Internet.  North Americans, may have “friends” from Europe, Asia, and South America for their play time; a virtual global village.  They learn to collaborate and team virtually using the technology.  Consequently, technology and knowledge are creating a generation with a completely new set of skills and expectations.
Firms and other organizations that do not prepare, plan, and strategize to take advantage of both workers and customers with these skills, talents, and culture, likely will not survive and thrive in the next 10 to 15 years.  This is the “Current Shock” – “Future Shock Now.”

Are There Really Economies of Scale?

The change in knowledge growing exponentially and technology is defusing this knowledge globally nearly instantaneously.  Further, the increasing knowledge is producing new technology and the technology is enabling the production of new knowledge in an accelerating double helix of cumulative causation. 
Economies of scale occur only when technology and process knowledge is constant.  As the knowledge base grows, economies of scale shrink.  Therefore, in today’s environment, in which information, conservatively, is doubling every two years, economies of scale are fictional, and should be replaced by economies of knowledge.  Further, the paper will posit that the economic concept of the barrier to entry is really the knowledge barrier to entry.

Economies of Scale: The Example of Steel

It is a tenant of economics that there are economies of scale; that large lots of a product can always be made more cheaply than small lots; services can be provided more easily at a large scale than small.  The concept of economies of scale has been “the reason” for many mergers and acquisitions, which may have been true fifty years ago, but are not true now.  This concept permeates business thinking; didn’t Henry Ford reduce the cost of automobile assembly using this concept; didn’t Andrew Carnegie, Paul Mellon, and J.P. Morgan reduce the cost of producing a unit of steel by using the concept of economies of scale?
From the 1970s to the 1990s, the United States steel industry went into a severe decline.  At the time, this decline was blamed on “steel dumping” (i.e., that is selling below cost) from steel plants in emerging economies and the high price of labor in the US due to trade unions. While there may have been some truth in both of these charges, there was a false underlying assumption, that large-scale steel plants can make steel more cheaply than small plants.
The steel industry people based their assumption of the economies of scale on the history of the steel industry.   In 1855, Henry Bessemer took out a patent on a process to turn pig iron into steel economically.   The Bessemer converter could transform batches of 8 to 30 tons of pig iron into steel.  This process produced much larger quantities of steel than the previous processes and at a much lower cost per unit; but the equipment and installation costs were much higher.  This eliminated the weak competitors; meaning those that either culturally are unwilling to adopt the new technology or financially unable to acquire the new converters.  Eliminating many small mills led to concentrating steel making.  “Sharp practices” in the parlance of the day, further concentrated steel making in the hands of Carnegie, Morgan, and a few other “robber barons”, aided an abetted by the railroad barons.  These monopolists sold the concept of this concentration solely on the bases of economies of scale; that is, they needed to concentrate enough demand so that they could use the new tools and processes, which, in turn, would greatly reduce the cost per unit of product.
While President Theodore Roosevelt remediated many of the monopolist practices that caused the “economies of scale”, the concept of economies of scale remains axiomatically fixed in the discipline of economics.  And why not?  After all imperial data demonstrated that there are economies of scale and barriers to entry (that is the economic analog to the sound barrier in physics.)
After WWII, the steel making in the United States underwent a sever decline, in part due to foreign competition.  Other reasons included the price of labor and the costs of meeting new environmental standards, but it was easiest to blame “foreign dumping” that is, selling the steel below the cost of making the steel, in part because there was some foreign dumping.  Killing off the competition by selling below cost had been a favorite tactic of the “robber barons” that built the US steel industry.  Nonetheless, part of the reason that the foreign competition could “sell below cost” (in addition to foreign government subsidies), was that their large integrated steel plants were constructed using modern technology and processes, acquired from the increased metallurgical knowledge base.  That refinement increased the plant’s throughput.
Then in 1968, Nucor Inc. started producing steel in small batches using an electric arc furnace.  This was a complete change in technology based on new knowledge of technology and processes.  These micro-mills could produce specific grades and qualities of steel at prices competitive with the major manufactures.  Further, the cost of building micro-mills is much less, than the integrated steel works.  That is, the economies of scale are less, and the barrier to entry is lower.  So, are there really economies of scale and barriers to entry, or rather, like the sound barrier, economies of knowledge and barriers caused by lack of knowledge?

The Concept of Economies of Scale

The Forbe’s Investopedia has a good and understandable definition of economies of scale,
“The increase in efficiency of production as the number of goods being produced increases. Typically, a company that achieves economies of scale lowers the average cost per unit through increased production since fixed costs are shared over an increased number of goods.”[3]  It goes on to say, “There are two types of economies of scale:
·         External economies – the cost per unit depends on the size of the industry, not the firm.
·         Internal economies – the cost per unit depends on size of the individual firm. 
Economies of scale give big companies access to a larger market by allowing them to operate with greater geographical reach. For the more traditional (small to medium) companies, however, size does have its limits. After a point, an increase in size (output) actually causes an increase in production costs. This is called "diseconomies of scale.”[4]
Internal economies of scale are the most fundamental.  For example, having giant earthmoving equipment (tools) has revolutionized the way many miners mine, especially for low-grade ores.  The cost of moving earth to extract the minerals has been dependent the quantity of earth moved per unit of time; which means that large equipment is more cost efficient than small.  Therefore, the largest trucks ever built are found working in mines.
Yet, if a new chemical or physical process is invented that allows for on sight separation  of minerals from the rest of the material, then, all of the investment in mega-earth moving equipment may become “diseconomies of scale” such as is found in the integrated steel works.  For example, if a low cost chemical method could be found for separating traces of gold from seawater, then gold mines might be outdated.  This example makes the point; there are not economies of scale in a knowledge-increasing environment.  Rather, for a given level of knowledge, there are economies of scale and of barriers to entry, which like the sound barrier are overcome or destroyed by new knowledge.

Adam Smith and Pins

The underpinning example in Adam Smith’s book “Wealth of Nations” is the production of pins.[5]  Using the example of a “trifling manufacture; but one in which the division of labour has been very often taken notice of, the trade of pin-making”, he demonstrates that by breaking the manufacturing process into discrete tasks and adding specialized tools, the output per unit of labor is much greater.[6]  By bringing 8 to 10 “pin makers” together, and having each perform one pin-making task with special tools, they could produce 10 times the number of pins as the pin makers could individually.  This produces the effects known as economies of scale and barriers to entry.  That is, individual pin makers could not compete with the pin making organization.  Each individual did not need all of the skills to make a pin, only those for the one task he was doing; so the organization could pay these individuals less (having less skill.) 
Further, individuals invented tools to help themselves make pins of more uniform high quality; in effect, they were embedding some of the skill one function of pin making in the tool, which meant that yet less skilled individuals could make large numbers of uniform quality pins.  For an organization, embedding skill and knowledge in tools (that is, technology) reduced the cost of labor, while increasing the capital necessary to buy the tools—creating a barrier to entry.

The Fiction of Economies of Scale

Frequently, internal economies of scale is cited as the reason for many of the best known mergers and acquisitions, especially in the financial industry.  Firms like Citigroup, J.P Morgan Chase, and so on, which are a product of mergers, are so large that they have difficulty accounting for all of their assets (and their value), let alone demonstrating that they achieved the economies of scale they predicted going into the merger.  In today’s technology and knowledge-based business context, this reasoning may be fallacious.

The Growth of Information Handling

Intel co-founder Gordon E. Moore empirically described the growth of the complexity of integrated circuits in a 1965 paper[7].  Based on the increase in complexity at that time, the paper describes a long-term trend in the history of computing hardware.  In brief, Moore’s Law, as it became known, described that from the invention of the integrated circuit in 1958, the number of transistors that can be placed efficiently on an integrated circuit doubles approximately every two years.  Numerous papers have corroborated this “law” for 50 years and is not expected to stop for another decade at least and perhaps much longer.  Since this empirical law applies equally to all digitally-based devices, in terms of processing speed, storage capacity, and so on, nearly all devices from PCs, to cell phones, to digital cameras, to network switches are improving exponentially as well.
The exponential increase in computing power and the use of that power in handling information has dramatically transformed in nearly every segment of the global economy.[8]  For example, until the 1970s, there were many small financial institutions, like banks, stock brokerages, and insurance firms.  The reason for the number was that after a certain point, the paper-based technologies supporting those organizations’ processes were incapable of supporting more than a relatively small number of customers.  For example, the cost of storing the data in a paper format becomes expensive; in the 1970s the floor space for one file cabinet could total $150 per year, including environmental factors for the storage of paper.  More importantly, the friction caused by simply retrieving the information, the time it would take a file cleric to find one document, even if it was not misfiled, could be a half hour.  At some point, this tool-based friction (paper being the information repository tool in this case) caused diseconomies of scale.
Enter the mainframe computer.  In the 1960s and 70s, with the advent of large-scale computers (those with at least 1MB of memory and 100 MB of storage) house in environmentally controlled rooms (the “glass house”), the cost per retrieval transaction dropped drastically.  However, the sunk costs for the mainframe and glass house, soured; creating new economies of scale and a major barrier to entry.  Consequently, a few of the larger firms in these industries gradually acquired many of the smaller firms because of economies of scale and barriers to entry.
Now, the United States faces mega, and oligopolistic financial institutions, which it cannot to let founder, and which are managed for short-term benefit of its management and shareholders.  At the same time, the cost of computing power has followed Moore’s law so that people carry most of the computer power of an old-technology mainframe in their MP3 player, which is only part of their cell phone.  This means that the technology-based economies of scale and the barriers to entry no longer exist in these industries.  Instead, the mergers and acquisition teams claim that the economies of scale come from the need for relatively fewer employees in large financial institutions as compared with small firms and that large firms are more resilient to risk than small.
As recent events have shown the latter is false, large financial firms can fail, and when they fail, it can damage the entire global economy.  Actually, small financial firms can hurt the global economy much less than large firms and both are only as strong as their management and its decision-making abilities.
A further consequence of Moore’s Law is that it militates against economies of scale.  For example, take large systems purchases. Since these take a large investment, the idea is that the organization will use this investment for an extended period.  However, computing systems become obsolete within 6 months of the time an organization acquires them.  According to Generally Accepted Accounting Practices (GAAP) things that last only 6 months are an expense item; not a capital items.  Therefore, a large investment in computing power is difficult to justify creating further diseconomies of scale.

Organizational Friction

With respect to merging financial firms to reduce labor costs per transaction, that axiom is false too.  The larger firm will always have more people than the two prior firms.  Any organization of more than one person generates organizational friction; simply because consistently clear succinct communications is impossible.  All expend time and energy used to correct a misunderstanding is organizational friction.  Simply put, it reduces an organization’s process throughput, while increasing the costs in time and resources.  As more people are added, the organizational friction increases.  While using standard terms, phrases, help, there is still much violent agreement.  Organizations over twenty people use standardized processes, procedures, and templates to reduce this friction, as well as dividing the organization into functional sub-units, all to reduce organizational friction.[9]
Regardless of how an organization manages its processes and functions, and how formally it is organizes; the organizational friction will increase with size.  One reason is that people miscommunicate; the larger the size, the higher the probability of miscommunication.  Even with standardize processes, procedures, methods, and templates, if these functions and processes are non-repetitive, as in research, design, development and customizing solutions, then standardization will create some process friction; the more inventive, the more friction that formal processes and procedures will create.  When a merger occurs, generally, the management of the new organization is less willing to take risks on inventive ideas, chasing the inventive personnel of both legacy organizations out of the merged organization, so that the general level of inventiveness decreases.  Consequently, large organizations have lower ratio of inventiveness than small organizations.
A second reason is that people can achieve the same result through different processes and procedures.  Just look at Microsoft word; there are several methods, built into the tool, for copying and pasting.  Why; because people work differently, but achieve the same result.  Standardizing a process or procedure helps some people, but hinders others.
A third reason is “span of control” versus “increasing overhead.”  Span of control refers to the number of subordinates that each superior has, be it individuals or departments.  The situation is:
“that with larger spans, the costs of supervision would tend to be reduced, because a smaller percentage of the members of the organization are supervisors [which reduces the organization’s overheads]. On the other hand, if the span of control is too large, the supervisor may not have the capacity to supervise effectively such large numbers of immediate subordinates. Thus, there is a possible trade-off to be made in an attempt to balance these possibly opposing tendencies.”[10]
Much research has found that the span of control should be in the range of 3 to 7 (US Homeland Security specifies 5).[11]  Other experts claim that for very routine jobs (those that are transaction or assembly line-based), one manager can supervise up to 30 subordinates. Davis (1951) divided managerial work into two categories, one requiring the attention to physical work, the other one requiring mental activity. Depending on the type of supervision, a span of 3-8 subordinates for managers at higher levels was considered adequate, while first level supervisors, i.e. those supervising shop floor personnel could have up to 30 subordinates.  While, 30 subordinates per first line manager may be applicable to a shop floor, finance departments have generalized it to include all first line management. The result has been the growth of quality control and quality auditing organizations.  This means that for large financial firms, each account, now, has higher costs of coordination for the “management labor” than smaller firms or has less ability to control the quality of services provided. This is not good where large sums of money are involved.  Either way, the result is diseconomies of scale.
Without technology-based barriers to entry, and with diseconomies of scale due to inherent management risk from either span of control problems or increasing overhead costs, large firms, are doomed, particularly large financial firms.

Economies of Knowledge: The New Reality

The new reality is that with the continuous acceleration of the quantity of data, information, and knowledge collected, any economies of scale are ephemeral.  An investor should treat any economies of scale based merger or acquisition with skepticism.  If it is economies of scale based on technology, it is probably that both the barriers to entry and the reduced costs will disappear shortly and if it is based on reduced labor, that if the organization is large enough, the organizational friction will eat up any cost savings.
However, there is a second culturally based force militating against large organizations and mergers and acquisitions, the up and coming technology generations.  Until the 1950s, researchers did not name generations.  Yet, since WWII, they have been named. These include “The Greatest Generation” (born in approximately 1920 to 1940), the Boomer Generation (born mostly from 1945 to 1965), Generation X or the “Me Generation”, (born in the 1970s and 1980s), and Generation Y or the “Techno” or “Millennium Generation” (born in the late 1980s to the current time, though we may be into Generation “Z?”.) 
The simple fact that researchers and marketers are naming these generations is important.  In the 2000 thousand years or more prior to WWII, there was no such naming and no such importance attached to generations.  Instead, researcher named epochs or ages; the Stone Age, the Copper Age, the Bronze Age, the Iron Age, and so on.  Additionally, these included the Dark Ages, the Middle Ages, the Renaissance, the Industrial Revolution, the Age of Mass Production, the Atomic Age, the Space Age, and the Information Age.  Researchers are describing these human generational epochs in terms of technology, the knowledge gained, or the political environment of the time.[12]

Generation X and Y

Since WWII, knowledge and the consequent technology have grown so exponentially fast and so globally that researchers are treating each generation as separate populations that have grown up with separate characteristics, attributes, values, and cultures, as far different from their parents as the cultures of the Renaissance and the Industrial Revolution.  Consequently, the researchers have named them as such.  The characteristics of generation’s X and Y differ greatly the previous generations and from each other.  The cultural differences are so great that it is the equivalent of a US or EU firm attempting to set up a plant in China, India, or an African country.

Attributes of Generation X

Individuals in Generation X were born early in the period of the transformation from paper information storage and retrieval to automated; from early mainframes to notebook computers, PDAs and cell phones, and the Internet.  Information storage has included, 8 track tapes, cassettes, floppy disks, CDs, and “thumb drives.”  Researchers have not entirely agreed on the cultural characteristic Generation X has derived from this experience, but most maintain that the culture of Generation X includes the following:
·         Are not loyal to an organization, but to themselves.  They have seen how firms treat their parents, laying them off without warning because of management ineptitude in the face of the continuously changing business environment (e.g., technology changes, or globalization), where extremely important skills become obsolete overnight.  So they are always looking for training and certification so they can change organization and survive and get promoted that way.
·         Want challenging work.  Generation X has grown with the exponential growth computing power, per Moore’s Law.  They expect computing and automation to reduce the repetitive work to a minimum.
·         Want the freedom to manage time and work.  Generation X has grown up being self-directed.  Further, since they are not loyal to an organization, they will take a new job that promises more freedom to manage their time and work.
·         Want to work for organizations that understand the value of the individual and nurturing relationship with the individual.
·         Finally, they expect feedback and recognition from the organization.  If not, they will find a new job.
Only employers that can meet these requirements will attract and keep the best personnel.  If the organization is not responsive, it will keep only those that are mediocre, at best.  This is far different from the way many organizations currently treat their personnel.  Large organization, especially, attract transactional managers; managers that manage only to cost, schedule, and company policies, and have no ability to create a sense of vision or mission within their organizations.  This is opposed to transformational managers; managers that lead with vision and a sense of mission.  On the other hand, entrepreneurial organizations are entrepreneurial because of their sense of mission and vision.  These are likely to attract the best and brightest. 

Attributes of Generation Y

Generation Y was born into a computing and networking technology environment.  They expect to be connected with “everyone, everywhere, everywhen.”  They don’t pass notes in class, they “text” one another.  Generation Y expect to be able to call, e-mail, IM, or “Tex” anyone, anywhere, at any time of the day, and they are comfortable with all of these technological forms of communication. This has shaped their culture.[13] 
Again, while researchers have not entirely agreed on the cultural characteristics or attributes of Generation Y, they generally agree that they include:
·         They expect technology.  Generation Y has never been without technology.  They do not “go to the phone”, or login to the computer”; they expect to have computing power, storage, and communications wherever they are.  They have inculcated technology into the daily life, that is, they use it without thinking about using it, like their senses.  Technology enables them to stay connected with their friends and associates.  They use UTube, and Facebook to communicate the way the Boomer Generation used the car and the drive through restaurant to associate.
·         They expect to be connected 24 hours a day, 7 seven days a week.  They work with their friends who are located globally and communicate with their associates whenever they feel like it.
·         They are collaborative.  They use their technology and the global interpersonal networking to work on their personal and professional challenges and opportunities. 
·         They are impatient for answers, whether personal or professional.  Their experience with the technology, including the data and information mining applications on the World Wide Web, and the instantaneous wireless communications in several modes, has taught them to expect it, now.  Additionally, they have grown up in a period of abundance and instant gratification.
·         They work well on teams because they have always had instant collaboration due to the digital and communication support throughout their lives.  These teams do not need to be co-located, but can be virtual in space and time.
·         They are comfortable with change; and in some cases, they expect and embrace it.  After all, they have never lived without constant change in technology and a constant enlargement of their community to include the entire globe.
Generation Y expects change and expects to collaborate and team in unorthodox ways to transform their environment.  Any organization that is too hierarchically driven will find their best minds leaving and making large sums of money off new ideas on which they have collaborated with others.  Immediately, these organizations will be on the going out of business curve.

The Home Office as an Enabler

Another trend is enabling Generation X and Y’s expectations, that is, the home office.  With the increasing ubiquity of high speed Internet and associated software systems, knowledge workers could start to telecommute.  This has advantages for the worker, for the employer, and for the transportation infrastructure.  For the worker, there can be significant time and cost saved in driving forth to and back from work each workday.  Additionally, it allows the worker significant flexibility when they work, allowing for a more balanced work/life experience.  For the transportation infrastructure, fewer vehicles commuting each day, reduces the wear and tear on the system, which in turn, reduces the maintenance costs.  For the employer, the benefits are enormous. Researchers estimate that employers save approximately $15, 000 per telecommuter per year.[14]  Consequently, many large employers have embraced the concept.
However, if a valuable Generation X or Y employee works from a home office there are two negative externalities.  First, they are used to working on their own, with little informal interactions of the “water cooler” variety.  This further decreases the team spirit of the knowledge worker; making him or her feel more like a consultant and less like a team member.  Second, if a telecommuting worker changes jobs, but continues to work from the home office, many of the psychological barriers to change are removed, since all that changes are the voices of the rest of the participants are on the teleconference, the website, and servers on which employee works.  If the websites are poorly designed, the organization’s policies are overbearing, the organization has transactional management (management that is only interested ensuring the policies are followed, e.g., CYA managers), or the salary, benefits, and training are poor, then the employee can easily change employment.

An Assembly Line of Suppliers: Examples of Economies of Knowledge

Given that knowledge is growing exponentially and consequently, the barriers to entry will continue to fall and current economies of scale will disappear (reducing the ability of large firms to compete).  Further, the future leadership is pro transformational management, rather than transactional management (that occurs in large organizations), organizational economics dictates that, over time, large firms disappear, unless propped up by laws and regulations.  The question is what organizational models will replace them?
Currently, several industries have business models based on economies of knowledge.  Researchers and others call these models by terms such as “Mass Customization” (as opposed to mass production), the “Virtual Enterprise”, the “Virtual Extended Enterprise”, and “Next Generation Manufacturing.”  All of these models have one thing in common; they assemble organizations from small component organizations, based on knowledge (in the form of needed core competencies).  These assemblies are of two types, alliances or associations of geographically dispersed firms, all providing the same products or services, and supply chains that design, assemble, and manufacture complex products.
Two examples of the associative model are IGA and Best Western.  The Best Western hotel chain (alliance), founded in 1946, is the world’s largest hotel chain.  The hotels are independently owned and operated.  They are more an alliance than a franchise, since, unlike a franchise, they differ great from hotel to hotel.  The chain formed by formalizing an informal alliance of independent hotels, whose owners would recommend one another’s hotels.  This improved everyone’s business; which is still the reason for the chain.  Today, “the chain” provides two key functions; first, it sets and enforces quality standards for the rooms at each hotel, and second, it provides marketing services, like a reservation system to the hotels.
The Independent Grocery’s Alliance (or IGA), founded in 1926, includes nearly 4,000 independently owned supermarkets worldwide, supported by 36 distribution companies and more than 55 major suppliers.  This is a supply chain, (vertically federated) as well as a marketing (horizontally federated) organization.
Other industries, like the beer brewing industry and the movie industry have started migrating to these economies of knowledge models.  Until the late 1980s, a few major brewers dominated the US market.  The reason was mass marketing and the economies of scale in the brewing process.   However, beginning in the late 1980s, a micro-brewing movement started.  These breweries produce small batches beer with varying characteristics of taste.  Today, these microbreweries produce 20 percent of the industry’s total and continue to increase their percentage of the market.
The Movie Industry, too, continues to migrate to economies of knowledge.  Early in its history, the movie industry consolidated into a few major studios, (e.g., MGM, RKO, Universal, and Disney).  Virtually everyone involved in the industry was an employee of one of the studios, since these controlled the distribution network, that is, the movie theaters.  However, the 1960s, for a number of reasons independent films have become important.  The major studios are still an important marketing and distribution organization, but now a film company forms around a script.  The producers find the resources, hire a director, and the others necessary to produce the film from the various gilds and unions.  This relatively complex organization is relatively ephemeral, since once the film has been completed the organization dissolves.
The Automotive Industry is divesting itself of its internal supply chain.  The best example is General Motors “spinning off” Delphi.  The major auto manufacturers are abandoning their vertically integrated model, which they have used since the industry grew into a mass production industry.  When Henry Ford set about creating the Ford Motor Company he felt that it was necessary to control the complete supply chain, in order to get the materials he required in order to achieve the economies of scale he desired.  Therefore, he bought iron mines, and iron ore transport ships, rubber plantations, glass manufacturing plants, and so on.  Other pioneers followed suite, which created a tremendous barrier to entry.
However, when the Japanese entered the automotive market, they used an entirely different model of a supply chain of many suppliers.  Using the supply chain model for manufacturing was one of the reasons that the Japanese were able to gain global market share.  The US automotive industry took more than 15 years to react, which allowed the Japanese to maintain their competitive advantage and turn the “Big Three” into the “Detroit Three” automakers.
With today’s technology and supplier-base, a visionary model of the automotive industry of the future might be much more akin to the current movie industry.  A consortium of suppliers led by a “general contractor” could design a new vehicle, and set up an assembly line to manufacture it, dependently of any “major” manufacturer; each supplier might set up its own workstation on the assembly line, greatly reducing the barrier to entry.  Examples of these suppliers could include: The Eaton Corporation, Stewart-Warner, TRW, and Magna International.  The general contractor could contract with an association of auto dealers to sell the vehicle.  A prototype of this automotive manufacturing model is found already in racecar and custom car construction.
Generation X and particularly Generation Y take this trend to a further extreme.  For example, in the fashion industry, today’s automated/robotic technology would enable an individual to stand in a booth to get his or her measurements.  The person could then choose a style of garment and see it on a virtual model of him or herself.  They then could choose a material and color, push a pay button and within a day or two have the garment delivered.  This technology has been available for the past 10 years.
There are two reasons that this technology has not established itself in the fashion industry.  The first is a set of cultural behaviors including, shopping behavior as a recreational activity and the need for privacy with respect to body dimensions.  The second is economic including the current investment in the entire apparel supply chain from the fabric makers, to the garment manufacturing, to the apparel marketing industry, to the retailer, and to the mall owners.  Additionally, there is the cost of retooling the industry, given the cost of the new equipment and the current sunk costs by the supply chain.  Sure sounds like barriers to entry.
However, given Generation Y’s propensity to embrace new technology and use it with facility, and given the continued decrease in the cost of automation and robotics, there will be a significant market shift to this type of an apparel industry within the next 5 to 15 years; and it is likely that these manufacturing facilities will be small sized, but serving a global market across the Internet.

Facing Large Challenges with Small Organizations: Swarming

One reason for large organizations is to meet the resource requirements for large challenges or opportunities.  It is difficult to see how many small organizations can construct a mega-cruise ship, or mega-tanker ship.  Yet, other major construction projects create 100+ story buildings, 15-mile tunnels, and 17-mile bridges using just this process.  A general contractor coordinates the other subcontractors and an architectural firm creates the overall design.  This general contractor has two roles.  First, the contractor has the mission to complete the job and produce a product that meets all of the customer’s requirements, both programmatic (cost and schedule) and system (what the system is supposed to do and how well it is supposed to do it.)  Second, the contractor must either enact and enforce or use others’ policies and standards to minimize the process friction among the sub-contractors.
With today’s technology and the emerging technical and business service standards, there is no reason that small firms cannot transform nature’s tactic of swarming to attack these large challenges and opportunities.  For example, in nature, a swarm of bees attacks any animal they feel is threatening their hive.  Again, white blood cells swarm to any wound to fight any invading bacteria and viruses.
The US military is looking at resurrecting a concept used in WWII; that of having many small units (approximately 40 troops) that can swarm to carry out a mission.[15]  Using many small units, each with specialized functions (e.g., infantry, artillery, and so on), coordinated by a mission commander (the analog of the general contractor) is a much more flexible than throwing large units into the mission.  For very large missions, the mission commander could form a command hierarchy for its duration.  When the swarm completes the mission, the hierarchy dissolves.
In WWII the swarming concept was applied to armored units, since prior to the war the US Army produced two doctrines for its use.  The first was as mobile artillery and machine gun support for infantry in breaking through enemy main lines of resistance.  This was the doctrine pioneered in WWI.  The second was the concept of mechanized cavalry.  This doctrine was pioneered at Camp Knox, (later For Knox) in the late 1920s and early 1930s.[16]  The Germans, who visited Fort Knox in 1933, built on this doctrine and implemented it as the “Blitzkrieg” that Hitler’s armies used so successfully in 1939 and 1940. 
By 1944, the US Army had implemented both doctrines.  Armor had separate battalions that the army commanders could assign either to infantry divisions in support of a breakthrough of the enemy’s lines or to armored units to support a breakout behind the enemy.  This demonstrates swarming as an agile strategy.   With today’s technology-based precision strike weapons and command and control systems, swarming is again becoming preferred.  It allows the commander to much more easily mass the correct balance of forces, yet economizes the total use of forces.  Additionally, it enables flexible (or agile) use of the forces available.
If swarming is a favored model of nature, is becoming a favored model of the military, is already in use in some industries, and is sociologically a good fit with the Generation X and Y cultures, then CEOs and investors should expect the expansion of economic swarming of knowledge-based services model in the near future.  This model is the virtual extended enterprise.  Small firms provide these services and vie with one another for a place on a team to build some unprecedented complex system.
One of the first of these swarming “organizations” in the IT industry is “Linux Unincorporated.”  In the 1990s, many computer geeks took umbrage with Microsoft’s dominance of the PC operating system and office products market.  These individuals formed a loose software development confederation.  Each of the approximately 750,000 members of Linux Unincorporated worked on what they were interested in, had the skills for, or had a problem with, with respect to the product, the Linux operating system.  While much of the output this team has been scrapped or superseded, several companies, notably, Red Hat, have marketed some of the best code at very competitive prices.  The net result is that Linux has a small, but significant share of the PC server operating system market.  Their competition is based on their knowledge.  Again, the economies of knowledge and knowledge barriers to entry rule, not economies of scale and financial barriers to entry.

Implications and Recommendations for U. S. Business

The twin concepts of the economies of knowledge and the technology generational cultural gaps will have an enormous impact on US business.   In fact, economic chaos in the financial markets may be part deconstruction caused by the change implied by these concepts.  Large firms will have a difficult time attracting and keeping talent.  As more customers of large firms become accustomed to working with consortia, there will be less emphasis on doing business with known firms and more on getting the right combination of performance, dependability, cost, and schedule.  This change has at least eight implications for US firms.
First, successful organizations must have agile processes and agile systems.  About 1991, the Virtual Extended Enterprise Workgroup of the Agility Forum defined agility as “the ability to respond successfully to unexpected challenges and opportunities.” The reason that firms must have agile processes and systems is that knowledge is increasing so rapidly that in the three to six months it takes to implement a new system, it becomes obsolete.  Consequently, firms will require modular implementation of all products and services.  For example, large mining shovels, some of the largest earth moving equipment, is already being automated to enable increased productivity.  However, it is unclear how modular the control systems are.  However, in the future, all of the onboard electronics will need to be modular, to keep the technology up to date and to enable it to work with the rest of the mine’s automated systems.  These may include measuring the quantity of ore in each bucket, to optimize the loads on the trucks, and sensing impending maintenance problems before they become an expensive repair.
On assembly lines, robotic systems have become the standard because of their agility.  No longer are many large single purpose machines built.  For example, as early as 1985, one furniture manufacturing plant spent an additional significant amount of money to allow their 40 ton metal fabrication presses to have their dies changed in under one hour, instead of the 12 hours normally taken at the time.  With the continued increase in automation and increased modularity of functions, this time has probably dropped to minutes.  This would allow the manufacturer to fabricate of a part on demand, rather than needing to warehouse a large number of parts until needed; greatly reducing costs.
Recommendation: When defining or refining the firm’s processes and supporting systems, especially core competencies, structure them to enable change. 
Second, successful organizations will produce customized products.  This mass customization is a natural result agile processes and systems, as just described.  However, the reason for customization is to increase customer satisfaction.  Since customers like products and services customized to meet their requirements, any firms that can meet or exceed the customer’s requirements will take business from those that produce a product that meets the narrowest common set of customer requirements, as mass production does.
Recommendation: When building or refining the firm’s processes and supporting systems, enable the employees to reconfigure quickly both functions and process flow to enable product customization.
Third, successful organizations will emphasize consistent policies and standards and a consistent and agile governance process for enacting policies and adopting standards.  Modular processes and tools will not work without known and well-described interfaces to connect the modules or hardware and/or software.  Without these policies and standards, there will be an enormous amount of friction at the interfaces among the processes, functions, procedures, and systems.
Without consistent policies, the process or system creates an enormous amount of process friction, as exemplified in the novel Catch 22.[17] If the policies or standards become too numerous or convoluted, the processes and systems will operate as if there was sand in their gears; again, process and system friction.  Only by having a simple governance process for instituting and transforming policies and standards, while maintaining consistency among the organization’s policies and standards, will the organization have the ability to be successful.
Contract policies for standard terms and conditions (T’s & C’s) and business process service level agreement (B-SLA’s) will permeate the supply chain; otherwise, the friction of the supply chain will make virtual extended enterprise (VEE) impossible.  The VEE will spend too much time and budget negotiating and not enough time doing.
Recommendation: When building or refining the firm’s processes and supporting systems a disciplined and flexible governance and policy management  processes are  vital to the organization’s success.
Fourth, consortiums of small organizations will supplement or replace large organizations on programs of significant size.  An organization’s core competencies will become the organization’s services that it can market within the VEE.[18] There are five types of core competencies that will be needed; these are the analog of infantry, armor, and artillery in an army.
·         General Contractor – the organization or service that coordinates development, manufacturing, and operational tasks.  The general contractor is accountable to the customer for defects in the product or service.
·         Teaming partner – an organization or service that provides an overall core competence for the design, manufacture, or operation of some significant portion of the product or service.  The teaming partner shares the overall accountability with the general contractor.  For example, an architect will share in the overall accountability with the general contractor of a new resort complex.
·         Sub-contractor – an organization or service that provides a significant core competence for the design, manufacture, or operation of some significant portion of the product or service.  However, the sub-contractor is accountable only for the portion of the product or service it provides to the general contracting team, and not the customer.  For example, the electrical sub-contractor will be accountable for the installation and/or operations of the electrical subsystems of the resort.
·         Supplier – an organization or service that provides components or materials that meet a standard set of specifications to one of the above.  The supplier is accountable for meeting the stated specifications only.  For example, the supplier of cinder blocks for the walls of the resort is only accountable to ensure that they meet the cinder blocks specifications as given to it by one of the above.
·         Concierge – the service or organization that discovers, evaluates, and maintains a library of core competencies.  The concierge is accountable for its evaluation of other organizations core competencies.
Recommendation: When a medium or large sized firm prepares to meet the challenges and opportunities of the economies of knowledge environment, its executives must evaluate the services of each of the firm’s division and departments to determine what service (core competence) it provides and if the service has value in the firm’s vision and future direction.
Fifth, there will be fewer large development programs and more outsourcing programs with both development and operation components.  Large development efforts require an implementation period of years.  In this period, significant advances in technology may reduce the knowledge barrier to entry to the point that the system is obsolete when the general contractor delivers it.  Therefore, for anything other than projects like constructing a skyscraper or cruise ship, the customer will modularize the project into small efforts.  That is, instead of a single $1B effort over 5 years, it could be 100 $10M efforts, each less than a year, done concurrently as well as sequentially.  This allows the customer and contractor to introduce new technology in the process reducing the risks of obsolescence and total project failure.  Additionally, it allows the customer to both add and update requirements during the construction period and to use the Initial Operating Capability (IOC) while additional portions are constructed.
Recommendation: All firms developing products or transforming systems under contract will need strategies for creating processes that enable short cycle iterative development and implementation.
Sixth, there will be a reduction of the size of successful firms.  The economies of knowledge and the decreasing knowledge barriers to entry, plus the increasing standardization of both technology and business practices are the reasons.  Large firms will have diseconomies of scale due to their overhead of hierarchy of high priced management, when compared with consortia.  Further, with fewer large development and operational programs and many more small programs, there will be less need for large sized firms.
Recommendation: When a medium or large sized firm prepares to meet the challenges and opportunities of the economies of knowledge environment, its executives must flatten the management hierarchy and treat the firm’s core competencies as independent services provided to the global market.
Seventh, there will be an emphasis on transformational leadership rather than transactional management throughout the organization.  Management researchers have defined a transactional manager as a supervisor that ensures that all employees of the organization follow its policies, procedures, and standards.[19] A transformational manager focuses on achieving the organizations mission using its strategies.  When an organization’s policies cause organizational friction sufficient to put its mission at risk, the transformational manager will work to change the policy so that the firm can better meet its challenges and take advantage of its opportunities.  In this new knowledge-based context, changing an organization’s policies, procedures, and standards to enable the organization to take advantage of business and technology challenges and opportunities may be the difference between success and failure; therefore, transformational management behavior will be high priority.
Recommendation: When a firm prepares to meet the challenges and opportunities of the economies of knowledge environment, its executives must not only ensure good governance and enactment policy management processes, but also ensure that both the policies and the personnel enforcing the policies have disciplined flexibility so that policies that run counter to the firm’s business strategies are culled or replaced and that the firm has only those policies necessary to insure a minimum of organizational friction both internally and with suppliers and customers.
Eighth, in this emerging business context, attracting and keeping knowledge workers, not management, will be critical to business (mission) success.  Excellent management without talented and knowledgeable workers will not produce results, but excellent Generation X and particularly Y workers will; and they will need less (transactional) management because of the collaborative culture. This will mean that, in the future, the knowledge workers will get bonuses and extended benefits, either in addition (or instead of) mere management.  Firms, like Google and Microsoft have taken a few initial steps to embrace this culture.
Recommendation: When a firm prepares to meet the challenges and opportunities of the economies of knowledge environment, its executives must ensure that the dysfunctional genius[20] has a significant place in the organization as well as all transformational thinkers.  A firm will need to continue to “court” these people, to the same level they continue to “court” executive talent, in terms of training, tools, and bonuses to keep them, that is, show loyalty to the knowledge worker.   
Like economies of knowledge replacing economies of scale, these eight recommendations run counter to the prevailing quarterly financial business culture.  Yet, executives that dismiss these recommendations are little better than the battleship admirals before Pearl Harbor ignoring the aircraft carrier as only an auxiliary to the fleet. 
The current accelerating knowledge growth rate is invalidating the economic concepts of economies of scale and barriers to entry.  Additionally, the understanding and use of technology by the coming generations are changing the organizational cultures and the economic context of organizations.  Together, these will have a major impact on all firms in all industries globally.  The trend to economies of knowledge will directly effect all stakeholders of large firms, including investors, management, suppliers, workers, and retirees, as well as governmental organizations and the firms’ customer-base.  While there still will be some relatively large firms, these will be far fewer and will have far fewer workers.  Understanding the coming changes and planning for them will ease the transition, which will otherwise be more traumatic than it need be.


[1]The Concepts for this paper were derived from R. Ellinger, Organizational Economics, (unpublished manuscript, 2008)
[2] A. Toffler, Future Shock, (New York: Random House, 1970).
[3] http://www.investopedia.com/terms/e/economiesofscale.asp
[4] http://www.investopedia.com/terms/e/economiesofscale.asp
[5] Adam Smith, An Inquiry into the Nature and Causes of The wealth of Nations, (Dublin: Whitestone, 1776)
[6] Adam Smith, An Inquiry into the Nature and Causes of The wealth of Nations, (Dublin: Whitestone, 1776), p.1.
[7] Moore, Gordon E., Cramming more components onto integrated circuits, Electronics, (Volume 38, Number 8, April 19, 1965).
[8] Rauch, Jonathan, The New Old Economy: Oil, Computers, and the Reinvention of the Earth, The Atlantic Monthly,  (January 1, 2001), see http://www.theatlantic.com/issues/2001/01/rauch.htm 
[9] However, as the number of sub-units increase, the organizational friction will increase because of conflicts and hidden agendas of the management of those sub-units.
[10] Mackenzie, Kenneth D., Organizational Structures, (AHM Publishing Corporation, 1978)
[11] “Span of Control: A supervisory range of three to seven individuals, with the ratio of one-to-five being established as optimum.” Found on :http://www.usda.gov/wps/portal/!ut/p/_s.7_0_A/7_0_1OB?navid= HOMELANDICSGL&parentnav=HOMELANDICSC&navtype=RT#glossary_S

[12] While some may quibble that these are very European centric terms, and that is true, nonetheless the growth of human knowledge across the globe is embodied in these terms.
[13] An example of this is a television ad where the Generation X’er admits that her 3 year old (Generation Y) knows more about her computer than she does.
[14] See “Inteleworks Cost-Benefit Analysis Worksheet for a Part-time and Full-time Home-based Teleworker” found at www.inteleworks.com (2001).  This worksheet is based on J. Niles, Managing Telework: Strategies for Managing the Virtual Workforce ().
[15] B. Alexander, How Wars Are Won: the 13 Rules of War from Ancient Greece to the War on Terror, (New York, Three Rivers Press, 2002), pp. 11-20.
[16] M.H. Gille, Forging the Thunderbolt: History of the U.S. Army’s Amored Forces, 1917-45, (The Military Service Publishing Company, 1947).
[17] J. Heller, Catch 22, (New York: Simon and Schuster, 1961).
[18] See G. Hamel and C. Prahalad, Competing for the Future: Breakthrough Strategies for Seizing Control of Your Industry and Creating the Markets of Tomorrow, (Boston: Harvard Business School Press, 1994) for a discussion of core competency and core business.
[19] P. Northouse, Leadership: Theory and Practice, 4th ed (Thousand Oaks CA: Sage Publications, 2007), pp. 175-207.
[20] Dr. House of the television program “House” is an example of this type of individual.