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Major Concepts: Realsearch ||| Enterprise Model ||| Maturity Model
                        Knowledge & Agility ||| Agile System Principles
Book: Response Ability - The Language, Structure and Culture of the Agile Enterprise
Value Propositioning - Perception and Misperception in Decision Making

(Section from paper presented at March 1998 IEEE Aerospace Conference)
Download: Realsearch A Framework for Knowledge Management and Continuing Education
View Section: Executive Overview, 1. Introduction, 2. Objectives and Building Blocks,
3. Framework and Process, 4. Testing the Approach,
5. Conclusions, References, Appendix: Local Metaphor Model Example

1. Introduction

As human beings we distinguish ourselves from other life by generating and applying knowledge. Our increasing population is building upon an increasing body of past knowledge - which increases the rate of new knowledge generation and speeds the decay of knowledge value - making the general business environment, which is built on knowledge, more unstable. Knowledge is the driving force of both proactive and reactive change. New knowledge demands to be acted upon; and when one business acts upon new knowledge others have no choice but to follow. Conscious knowledge management will return general stability in the long run. Short term it will provide preemptive advantage to those who master it first.

Insights are very powerful forms of knowledge, but very difficult to transfer to others. They stem from some internal understanding that is either too complex to convey in language or simply not consciously understood.

Our interest, therefore, is in helping people gain new knowledge at the depth of insight, within an environment dominated by constant change, an environment growing less tolerant of a time-out for learning.


In the late ’ 80s the National Center for Manufacturing Sciences (NCMS) pegged technology diffusion as a principal problem in American competitiveness [1]. On the surface, it simply took too long for new valid ideas to become adopted by industry. Underneath, it was evident that effective process knowledge and practice for diffusion did not exist. As one of the early government-funded partnerships with industry and academia this consortium put the problem high on its agenda, requiring all collaborative project work to be organized for application rather than (or in addition to) research and development. Real work in understanding the processes of technology diffusion remained wanting - the core of dissemination and adoption problems appeared to be social in nature and therefore difficult to fund and support through technology-focused channels.

Later, in 1991, government was the catalyst for the industrially led project facilitated at Lehigh University that resulted in the identification and definition of Agile Enterprise as a newly required competitive competency [2]. In 1994 DARPA through NSF breathed considerable life into this concept by significantly augmenting industry funding at the Agility Forum, the industrially led subsidiary of Lehigh University that grew from the 1991 project. The Agility Forum was so named precisely because it provided a forum for people from government, industry, and university to develop new knowledge about this new concept of Agile Enterprise. The forum-like structure was adopted and formalized so that people with similar interests but diverse experiences and problems could explore together a common set of problems - each bringing different needs and view points.

The author played a key role in the organization of both the NCMS and the Agility Forum approaches to collaborative knowledge development - first as Chairman of the NCMS Technology Review Board, and subsequently as the Agility Forum’s first Director of Strategic Analysis. Coming later in time, the Agility Forum benefited from a more focused and structured approach [3], as well as a less restrictive funding environment. The principal focus was upon creating new and immediately actionable insights in the minds of participants.

Industry workshops typically bring together people with different backgrounds and different agendas - and this often leads to poor productivity as the group spends its time seeking common ground, or suffers for lack of it. We found that structuring a working group's activities with a fixed analysis process and a clear objective eliminates these problems; driving the activity toward discovery of new knowledge. We have also found it counterproductive to require consensus on the conclusions. The people who went back from the early Agility Forum workshops to implement what they had learned all went back with very personal ideas, formed from their own conclusions about the new knowledge that was developed.

The author has continued to refine these knowledge development/dissemination techniques as a concept now called Realsearch, as opposed to research, as it employs real people addressing real problems in real time to develop or increase a useful body of knowledge that they can employ immediately.

This paper describes the Realsearch process that has evolved from those early consortium and subsequent Forum workshops into a process focused on developing insight and managing knowledge. It is still a work in process; but one which is already showing results in an area that cannot wait for the final answer.

2. Objectives and Building Blocks


The management of knowledge is emerging as the central theme in business today. We are beginning to realize that its application is the distinguishing factor among companies - but we don't know how to measure it or display it on the balance sheet. Nor do we know how to capture and package it so that we can spread it freely among employees. Nevertheless we know that it is what core competency is all about, and it is what competition is all about - for it is what the business is based upon.

We also know that knowledge is being generated faster than ever before, applied faster than ever before, and decaying in value faster than ever before. We have become concerned about managing knowledge as a business practice as a result.

Knowledge is a people thing. Though it may be technical knowledge we are talking about, it was a person who generated it, it is a person who has it, and it will be a person who tries to understand it - or decides not to. That's where the difficulty resides: People.

Realsearch is the name for a learning process we have been testing and refining. To date it has been employed in workshop format, generally with participants from mixed backgrounds and companies. The focus has been on business practices and processes, with the intent to learn why and how highly adaptable ones work, and to learn how to design new ones so that they, too, will be highly adaptable.

Our principal objective is to expedite the creation of insights about the value and nature of change-proficient business practices among a broadening base of people.

On the Nature of Insight

When do you do your thinking? If you are like me, it is principally when you're addressing a real problem. When do you get your insights? Mine generally come when I'm trying to solve a problem I haven't faced before, don't have a ready answer for, and don't know a formula or recipe or roadmap to employ in the process.

I think of insights as those nuggets of knowledge that are the shortcuts in our abilities to understand things clearly. They're like x-ray vision - they let us look at something and all the extraneous information just melts away; leaving only the essence that clearly explains what we are focused upon. Think of insights as lean knowledge. The best part is that most insights seem to stem from mental patterns so basic that they have broad applicability - knowledge patterns that are reusable under many seemingly different circumstances.

Nice stuff if you can get it. Geniuses seem to have a lot of it - that's how they make simple sense out of the things that baffle the rest of us. It's obvious we don't get it in school or we'd all have a lot more.

Why is this so important? The knowledge brought to bear on the job, whatever the job, determines how well it is done; and that knowledge, whatever it is, is getting obsolete faster and faster. So the manipulation and renewal of knowledge is a cornerstone of viability today - whether you're a company or a person.

The stuff of both personal and corporate core competency is knowledge, the leverageable stuff of knowledge is insight, and insight is possessed by people. So companies want to know how they can get more insightful people - either those who come with a storehouse of insights or those capable of developing them as needed.

Dan Seligman [4] suggests that intelligence is the attribute to look for, no matter what the job position or responsibility. "In jobs all across the skills spectrum, highest [IQ] test scores are associated with shorter training times, greater productivity, and lower turnover rates". Every job has an ideal IQ range, he says, and companies should attempt to fill those positions with people in the upper, rather than the lower, end of the range. He reminds us that Microsoft hires with this in mind: "promoting worker intelligence as a business strategy".

A study at Bell Labs disagrees. Robert Kelly and Janet Caplan [5] showed that among engineers a higher IQ didn't help - initiative and networks counted the most for productivity, and seven more "strategies" played important roles as well. Initiative: instead of simply identifying a problem, fix it. Networks: instead of simply asking others for help when stumped, cultivate respect among a group that trades in knowledge.

Interesting concept, this trading in knowledge. A source of indirect insight that allows a person to get beyond the roadblocker problems. It taps into many minds. It isn't teaming in the sense that we employ that term, yet it makes use of a team in the sense that we employ that term - it taps the knowledge of others who are willing to entertain your problem and provide a solution - or at least some ideas that could help enlighten your path to a solution.

After a certain age we begin to value experience over intelligence and a quick mind. Why? Because experience is a collection of ready-to-use insights indistinguishable from intelligence. Mere intelligence, on the other hand, must create an insight on-the-spot in order to solve the same problem equally well. Sometimes it can; but if you could find a way to increase your own pool of insightful patterns you would function at a seemingly "smarter" level. And if you could help others increase their collections of insights you would have about you a more effective group of people.

The point: it doesn't matter how the insight patterns get there (in your head), it only matters that you have them.

Remember the old plumber's justification for his high price for five masterful minutes of work: "$50 for whacking the pipe, $5,000 for knowing where to whack it". The plumber's knowledge might fit into one of three categories:

1) Maybe someone showed him where to whack it,

2) maybe he just "knew" where to whack it, or

3) maybe he understood why to whack it there.

Category one is the least leverageable kind of knowledge (it's only information masquerading as knowledge) and the most prevalent form - a set of circumstances repeats itself and you can solve the problem because you've seen that one before. This kind is built over many years of exposure to working situations and is the basis of craftsmanship maturation as well as most formal education. "Here are some tools - I'll show you how to use them. Here are some applications, I'll show you how to approach them. Now go out into the world and use this information, and if you run into something different, seek advice from someone wiser".

Where do these wiser people come from?

Category two is the least predictable but generally the most prevalent form of insightful (rather than rote) knowledge. We exhibit genuine useful insight into the way some things work but we can't explain it, we just apply it. X-ray vision. We all employ this form of insight to different degrees every day in the course of just living. Those we call talented often exhibit this unconscious insight in their area of expertise.

Category three is the most valuable form of insightful knowledge because it is transferable. It has higher leverage than that which is unconsciously exercised by a single person with a gift. Remember we're talking insight here, we're not talking about an application of formulas and process that cranks out an answer. We're talking about people who come up with an answer in the absence of formula, and then show us how to do it too. In essence they have given us a new mental pattern that we use thereafter to filter all the things we see, along with any other such patterns in our mental library.

It's not really that simple. Installing a new insightful pattern needs a receptive mind - one that is struggling with a problem that this new pattern solves. One that accepts the new pattern because it recognizes the void that can now be filled. Someone cannot give you one of these patterns when your mind is not in the inquisitive state. Insights cannot be handed out willy-nilly.

Good teachers create this state in our minds before they show us the keys. I had only one such teacher in my entire educational experience. They are all too rare. Guided insight development is unlikely in the classroom: it requires extraordinary teaching insight and a set of thought problems natural in this artificial environment.

One way to get insight: Tackle a problem for which you have insufficient knowledge to reach a straightforward solution, and no readily available book or expert to consult. One way to accelerate the development of insight: Tackle these problems in the company of others equally in the dark and equally engaged in the discovery process. When are the best insights built? When you're equally in the dark about the problem as you are about the solution - this is why you learn more from benchmarking outside your industry - you have to define the problem first - something we usually take for granted.

According to Kelly and Caplan, engineers at Bell Labs did it. The insight development was actually done by the Bell engineers themselves. They did have structured guidance; but they took charge of the initiative - defining the problem as well as the solution to higher productivity. They created their own state of inquisitiveness and developed their own insights into high-productivity knowledge-work. Powerful stuff - with full ownership. And then these same engineers turned around and organized self-discovery productivity workshops for all the other engineers. Unlike other forms of productivity training, Bell engineers that went through the six-week training experience continued to improve their productivity over time, rather then showing a short term, quickly decaying, post-workshop effect. They clearly had new leverageable insights - not simply new information.

Importantly, they used workshop exercises to apply the new knowledge they had discovered - and found out that fake exercises were not useful - so they brought in the real problems. They researched real problems with real people in real time. I call that Realsearch.

Building a Context

Not Invented Here - NIH - is a phrase we all understand from first hand frustration. An old Calvin and Hobbes cartoon put it straight. Talking to his teacher Calvin says: "You can present the material, Mrs. Wormwood, but you can’t make me care."

Imparting new knowledge to others seems to grow in difficulty in direct proportion to its applicability. Why don't people recognize good information when it stares them in the face? Perhaps it is more fruitful to ask: How can we help people to care?

Eric Drexler puts his finger on it directly in his book, Engines of Creation [6]. He suggests that the biological immune system we are all familiar with serves a valuable function when it rejects the cell types that were not present at birth, like bacterial and virus invasions; and that an equally necessary system protects us on the mental plane. "The oldest and simplest mental immune system simply commands ‘believe the old, reject the new.’ Something like this system generally kept tribes from abandoning old tested ways in favor of wild new notions." He goes on to give some solid grounding for the NIH syndrome, and finally notes: "This simple reject-the-new system once worked well, yet in this era of organ transplantation it can kill. Similarly, in an era when science and technology regularly present facts that are both new and trustworthy, a rigid mental immune system becomes a dangerous handicap."

So it’s not just pig headedness after all. But maybe there’s a way to trick this immune system, to insert a new idea disguised as an old, familiar idea. Like suggesting that product flow through a factory has a lot in common with traffic flow at commute time - helping us understand that high "utilization" causes "accidents", which decreases throughput; and when utilization is really high the accidents cause accidents, resulting in even lower throughput. The power of the metaphor is mighty.

I remember one postmortem discussion at an auto plant when both union and management representatives decried the fact that their lean production training sessions were not working. People did some things differently after sitting through class but stubbornly refused to change others. They finally asked somebody why this was: "You guys don’t know what you’re talking about. If we do what you want you’ll see production go down."

Spoken from the heart; but it wasn’t accurate. The class preached a new way to people who had unreceptive mental patterns, patterns that could not connect with the new information, patterns that were unable to recognize value in the new suggestions.

We all do it all the time. We understand the problem we have been working on, the problem we have found a solution for, so well, that we assume it is obvious to everyone. So we blurt out the solution and provide all its wonderful detail to people who haven’t traveled the same road, and aren’t prepared to value the same insight.

To transfer knowledge effectively, we must first create a context of understanding. We must build the patterns of understanding and value before we can hope to have new information embraced.

One masterful example: Jack Stack’s Great Game of Business [7] set out to teach every employee at a discarded International Harvester plant how to read and relate to the monthly corporate financial statements. What an uphill battle that must be - if you try it straight on: "When your shift is finished we’d like you all to join us for a two hour session on Balance Sheet reading". What Stack did, instead, was to teach people how to build a personal financial statement, and how to build a financial statement for a family side business like baking muffins and making jams. He captured interest with a personal connection and latched on to existing value patterns before distributing company financial statements. And it works - you have only to read Open Book Management [8] to see how well this technique has spread throughout all types of companies.

So we use metaphors to connect new information to old trusted knowledge patterns. These are reusable, reconfigurable, scalable knowledge patterns.

Local Metaphor Models

Virtually every business unit within a company has a few practices that exhibit high change proficiency. Typically these competencies emerge as necessary accommodations to an unforgiving operating environment. Maybe it's the ability to accommodate frequent management changes - each with a new operating philosophy. Or the production unit that automatically tracks a chaotically changing priority schedule. Or the logistics department that routinely turns late production and carrier problems into on-time deliveries. It might be a purchasing department that never lets a supplier problem impact production schedules. Or an engineering group that custom designs a timely solution for every opportunity or problem.

Every business unit has its own brand of tactical chaos it manages to deal with - intuitively - implicitly - routinely - automatically - without explicit process knowledge rooted in change proficiency. Yet at the same time virtually every business unit today is facing strategic challenges that cry out for this same innate competency.

To illustrate, we will use a practice from the General Motors Pittsburgh metal fabrication plant analyzed in our second workshop application of the Realsearch process. In brief: this plant stamps and assembles low volume, after-model-year, auto-body service parts. With responsibility for some 1000 assemblies the plant constructs a custom assembly line for a specific part, produces a few hundred doors maybe, tears down that assembly line and builds another in its place for a few hundred deck lids maybe (trunk doors) - and does this many times a day.

A one-page configuration diagram guides the production team in constructing an assembly line from common reusable modules of various types. The Appendix contains a 3-page local metaphor model that synopsizes the underlying principles at work in this just-in-time assembly line construction approach - graphically depicting the concept of assembling reconfigurable systems from reusable modules.

We have discussed the power of metaphors to create and communicate insight. The trick is to find a meaningful metaphor that can transfer this leverageable knowledge among a specific group of people. We accomplish this by creating a metaphor from a business practice that is well known (or at least accessible) and respected within the target group - hence the local designation.

Discovery Workshops

An effective technique for giving people insight is to involve those people in the actual knowledge discovery process. A structured approach for what I call discovery workshops is important, so that the group stays focused and achieves the objectives - both individually as well as collectively.

There is definite leverage in building new knowledge patterns when a discovery workshop takes place at a non-competitive site. Unlike benchmarking, where we want to see how a competitor does it, discovery workshops benefit when the shields are down, when the participants don't already think they know the subject cold and have strong filters already in place.

Through Paradigm Shift International I conducted a series of discovery workshops in 1997. These workshops would focus on identifying and understanding an underlying set of design principles for change proficient business practices.

Five years of probing at the nature of change proficiency with Agility Forum industry groups in real-life industrial settings provided a solid starting point. People from over 200 organizations had helped identify, postulate, test, analyze, and verify basic concepts and models for measuring and describing change proficiency across a broad base of business activities [9].

Ten design principles had been postulated previously, encompassing a framework/module architecture (see Appendix bottom of last page). Though there was studied work behind these concepts they had yet to be vetted in meaningful business settings. More to the point, they had yet to be packaged into a useful and understandable body of knowledge.

This, then, was the task at hand. But it was not viewed as a task for academics, nor as an academic task. Though the rigors of the scientific approach could yield more precise definitions, more precise mathematical models, and more defensible conclusions - the results would lie in books and reports with too much math and too little application. Initially, this was a task for business people who had problems to solve and opportunities to grab.

The Process—An outside Realsearch team works side-by-side with local personnel (who may also be part of the traveling Realsearch team) to examine two practices that exhibit high change proficiency. For each practice the structured analysis process builds a model of the change proficiency issues (proactive and reactive response requirements) and the architecture (reusable modules, compatibility framework, system engineering responsibilities). Then we examine these architectures for local manifestations of ten specific design principles.

The combined results produce two local metaphor models for change proficiency - local in that they are present at the plant site and respected intuitively for their capabilities - metaphor models in that the analysis explicitly illuminates common underlying principles responsible for this change proficiency.

Then we examine a third area of strategic interest that isn't yet designed, or must become more adaptable, and employ the metaphors to guide the application of design principles. This exercise at GM's workshop, for instance, was focused on designing a process for capturing and mobilizing core competency knowledge.

View Next Section: Framework and Process

(Section from paper presented at March 1998 IEEE Aerospace Conference)
Download: Realsearch A Framework for Knowledge Management and Continuing Education
View Section: Executive Overview, 1. Introduction, 2. Objectives and Building Blocks,
3. Framework and Process, 4. Testing the Approach,
5. Conclusions, References, Appendix: Local Metaphor Model Example

Features: Home | Library | Corp Info
Major Concepts: Realsearch ||| Enterprise Model ||| Maturity Model
                        Knowledge & Agility ||| Agile System Principles
Book: Response Ability - The Language, Structure and Culture of the Agile Enterprise
Book: Value Propositioning - Perception and Misperception in Decision Making

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Last modified: May 30, 2019