Knowledge Variables

Have you ever been in a situation where you had to exchange ideas with people that are from a different layer of society, level of education, or culture while communicating using the same language? And, have you ever had to explain your ideas repeatedly in different ways just to get your point across? Those of you that have can appreciate how difficult it could be to communicate even the simplest of ideas to people who don't quite get your point (even if the ideas are crystal in your mind). I know I had.

The assumption we implicitly make is that people of differing cultures and backgrounds will naturally understand and interpret ideas in ways that fit their own context. The fact is, even people coming from similar backgrounds have unique ways of absorbing, communicating, understanding, retaining information and different ways of “knowing”. This uniqueness can lead to either a rich exchange ideas that builds an entirely new body of knowledge or result in an all out conflict.

Human beings are complex creatures. We each look, learn, retain and communicate in different ways, using different styles and methods which are uniquely our own. For us to get along with others, it is necessary for us to communicate what we think in ways that could be appreciated and in a language that could be understood by others. How we communicate our ideas is revealing of the depth of knowledge we each possess concerning a given subject. And how we act consistently with what we know determines the depth of wisdom we each have as individuals. Knowledge and wisdom, however related, are mutually exclusive.

Knowledge is complex. But what is knowledge? The origin of the English word “knowledge” comes from the Greek word “gnosis” (pronounced as “nowsis”) which means “to know.” In the present-indicative-active, it communicates the idea of a never ending drive to know. Practically defined, it is the collective sum of an individual’s understanding of the world around him in general, and of specific domains in particular. By “collective sum” I mean, the sum of experience, data, information, customs, learning styles, language, interpretation, world view, culture that is tightly coupled to what makes the individual uniquely individual.

Knowledge is made up of multiple variables. It is mathematically impossible to define an algorithm that can precisely tell us how each of these variables interact or contribute to how an individual forms and organizes knowledge. In this regard, the term “knowledge management” sounds more like an oxymoron than an accurate description of the study. If we cannot define an algorithm to precisely determine how knowledge is formed and organized in human beings, then how can it be truly managed?

From an applied standpoint, it is not my intent to discuss the ontological roots of this area of study, but to provide practical information that will allow all of us to get to the first base of knowledge, which is, understanding.

Some of the variables that make up the formation “knowledge” are as follows:

1. Language
2. World view
3. Presuppositions, Fears, Culture, and Superstition
4. Personal Beliefs, Values and Norms
5. Collective Experience (direct and indirect)

Some of the variables that affect the formation of knowledge are as follows:

1. Psycho-sociological variables
2. Personal Behavior
3. Personal Need
4. Environmental Conditions (circumstance, opportunity or risk)
5. Societal Parameters for Interaction
   

These variables that make up and affect the formation of knowledge are all mutually complex variables by themselves. How each is used to form knowledge in an individual is not quite known. What is a generally accepted principle is that these variables affects the individual’s formation of knowledge.

Any one of these variables can weigh more heavily than the others given specific contexts. What knowledge is formed as a result of context depends on the orientation of the individual in that specific context. Behavioral scientists have been trying to determine, in mathematical terms, how each of these variables relate to each other and in what situations new relationships are established. So far, only “fuzzy math” exists.

How can this help you? By helping you understand the parts from the perspective of wholes.

This study will not go into the technical details behavioral scientists have to deal with. Rather, I will focus on providing information (in as layman terms as possible) that will allow each of my readers to draw their own conclusion, to help each frame their own applied patterns as it pertains to the subject of managing knowledge.

In future posts, I will discuss each of these variables I mentioned, in detail. I will also attempt to provide specific situational contexts to help my readers apply the information in very practical terms.

The situational contexts will revolve around both the personal (relationships, family, friends, etc.) as well as the professional (practice domains, industry, etc.). I am preparing studies that will help marketing professionals, medical practitioners, HR practitioners, entrepreneurs, and company executives apply core KM principles to help enrich their own experience and in the process, through feedback, attempt to create new knowledge.

Meanwhile, tell others about this post. Spread the word! If you wish for me to cover specific topics that affect you, just send me an email. I would be delighted to hear from you.

Until next time…

Corporate Universities: Developing Innovative Corporate Training Programs

I have often wondered if the incumbent practices employed in corporate training programs really provide the desired benefits for organizations for both the short and long term. Have you ever participated or enrolled in any of these programs?

Over the past few years I have casually observed how corporate training programs have been conducted, and have, on occasion, been a customer myself (sending employees for training). The program pretty much follows a template: printed courseware materials, case studies, and Power Point slides. The length of the training program depends on the scope of the subject at hand. But most of the time, it takes up about three days of productivity from each participant on the average.

The session begins by the instructor’s posture—certifications, years of experience as a trainer, subject matter (courseware) knowledge, and so forth. The objective of course, is to establish subject matter authority by dumbfounding their students with “academic credentials” to deflect from the reality that most of these young instructors have little to no real world experience.

If you look at the age group of participants, the range will vary. For technical courses, the majority will be under 30, but with management courses the age range spans between 33 to 50 years old. The irony in this setup is that the very people who should be teaching are usually the very people enrolled in the program. Most of them possess first hand, real world experience on the subject matter but had to endure the grueling few days just to receive a sheet of paper saying they have completed the course. Most of the attendees have to go through this process if they ever expect to advance in the workplace. Besides this reason, especially for those with real world experience, the course was really a waste of their time and their employer’s money.

Three days are over and participants return to work. Managers expect them to produce results that demonstrate enhanced subject matter and domain knowledge. A month goes by, and then two—nothing. So, what happened? The company paid an average of $500 USD for every attendee they sent, but they have yet to realize benefit? If you’ve ever sent people on training, you know what it feels to spend on a financial “black-hole”.

Most of these generic training programs produce little by way of results that will directly benefit the paying company. It simply adds a little knowledge to make the attendees a little more dangerous. Worse, a piece of paper could mean increased cost for the company the moment the certified employee jumps ship.

Of course, a distinction has to be made for training programs that are tailor fit to specific organizational contexts. These programs provide more realizable benefits for the corporation and its people since the context of training is specific to their unique requirements. Generic programs offered commercially do not.

The obvious reason behind the choice of programs is that of cost—generic programs cost less. But what companies fail to realize is that they lose out on the intangible benefits of hosting a context specific training program. They lose out on capturing the dynamics that surface when you bring employees together (that share a common and context specific objective) to absorb new information. They lose out on the benefits of serendipity. Due to the fact that the materials are generic, client companies will have difficulty mapping the benefits of new knowledge directly with performance and quality output since they have no way of determining whether the increase or decrease in quality or performance is directly related with the training or with some unrelated event that occurred in the life of their employee. It would be equivocal to try to map benefits directly to program over which they had no control.

In the long run, it costs more for the company to avail of generic commercial programs than if they had made the initial investment to pay for context specific training programs. They either pay for it upfront, or they will end up paying a higher price in the future. Either way, it will cost them.

As a result of the KM movement, there have been several training models that have surfaced. But among these models, I like the model of a Corporate University. From an applied standpoint, most corporations feel that employing such a model would be a waste of their money—nothing could be further from the truth. This is a classic example of the dilemma of mindsets I discussed in previous posts. Corporate officers tend to look at immediate savings and would rather make investments into physical assets than into a creating a culture of learning.

The cost of transforming one’s company into a corporate university involves KM specialists, process specialists, and automation technologies. It usually involves allocating an investment that represents between one to two percent of a company’s operating expenses on the average, to begin its transformation. This share could increase to about 6% if automation technologies are implemented. When we keep matters into perspective, this amount (relative percentage) is miniscule compared to the more expensive and bold investment initiatives that companies make nowadays. The best thing about making this investment is that knowledge will continue to appreciate without having implementation costs increase. The fact is, the more companies invest in knowledge, the less it will cost them in the long run.

In simple terms a corporate university is a system designed to enhance learning within a company. Every activity becomes a learning opportunity that can be captured, stored, shared, and reused throughout the organization, and enhanced by every encounter or application of knowledge. Because it is tailor fit to the specifications and context of a company, it is designed to benefit the company and its employees.

Corporate universities also provide the framework that promotes the propagation of constructive mental models through holistic thinking which company’s that adopt a purely corporate (tangible results only) model completely miss out on. Obviously corporate universities also provide tangible benefits, but this is considered to be “fruits" of a tree planted on fertile ground, in a manner of speaking, and not the "root" itself. Corporate universities considers tangible results only as a consequence but not its primary focus (the primary focus is enhancing their most valuable asset—people). For corporate universities, placing priority on enhancing knowledge in people produces far more sustainable results and higher quality products. Companies that employ a culture of learning and an environment conducive to the creation of new knowledge enjoy much low rates of attrition and turnover and introduce more innovative solutions to market faster than their closest competitor.

If you want to know more about corporate universities or want to know how to become one, send me an email at dennis@dbreyes.com. I can help you develop context specific strategies that will give you an edge over your competition.

Until next time…

How to Maximize Intellectual Capital Investments

The thrust to maximize returns on intellectual capital investments has been a mainstay of business and performance management consultants since the early 80’s. Every corporation in America, was inundated with promises of benefits by an increased investment into understanding and creating value using the intellectual capital route. The 1990’s, or the rise of the dotcom generation largely benefited from this fad. Unfortunately, when the bubble burst, and investors were wanting to understand what had happened to their investments, no one was able to provide an answer good enough to assuage investor loss.

What was largely discovered is that the valuation method used to increase intellectual capital worth employed a huge amount of creative accounting tricks. Valuation was as varied as the number of ice cream flavors available. You all know what happened next.

Intellectual capital investment and human capital investments are considered to be distinct in today’s business environment. But in reality, they are part of the same whole and are tightly coupled to each other. Without the human factor to contribute to the intellectual capital pool, intellectual capital would exist. The dilemma of measuring or quantifying intellectual capital net-worth is that the methods used to quantify material or physical assets (GAAP) cannot capture the value of non-physical assets. (This would require an entire study and discussion). How can a company quantify the value of their intellectual net worth when the systems used to quantify value are limited to that of capturing material or physical value? Most often the value assigned to non-physical assets is arbitrary—it simply depends on the relevance of such an asset in each given context.

As the intellectual capital trend spread throughout the world, businesses began to deal with the same issues and were confronted with more problems than it was suppose to solve. The support infrastructure that existed in advanced economies such as the US, was non-existent in other parts of the world. Legislation that protected intellectual capital simply did not exist, and where it did exist, the enforceability was insufficient. Confronted with this reality, Asian businesses, in particular, are slowly moving to strengthen local legislation to allow for stricter and more enforceable guidelines to protect intellectual property rights. But much work still remains.

Integral to increasing the intellectual capital pool of organizations is the proportionate increase in human capital investments. The awareness of human capital investments began to catch on in Asia toward the mid-1990’s and has continued to grow since. Consequently, companies began to restructure their specific environments to allow them to maximize their benefit from their human capital pool. But despite the renewed emphasis on the importance of human capital, organizations are still confronted with the challenge of reducing attrition and brain drain.

While companies, focus groups, industry and trade associations have begun to educate the general public on the importance and strategic nature of human capital, there are environmental conditions that prevent organizations to implement and fully realize, much less maximize, on the human capital.

The value of human capital is not measured by the size of an organization’s employee base, but by the quality represented within that employee base. Here again we encounter the dilemma of quantifying value. It is about companies enhancing core competencies, such that their competencies are disproportionately higher than existing market demand. Admittedly, such an ideal outcome is tough to create especially in Asian companies and specifically within Philippine organizations.

The environmental conditions that prevent Philippine companies from maximizing benefits from their human capital investments are systemic in nature. Meaning, these conditions are deeply embedded in individual and collective psyche.

Let’s look into this a little more in detail…

The Philippines in general (private and public) continue to make significant investments into adopting Western management styles, policies, and forms of governance. Such investments are considered necessary for the country to remain globally competitive. Western schooled executives have an established edge over their locally schooled counterparts not because they are less competent or intelligent, but because most progressive corporations hold western schools in higher esteem than local universities and colleges. Board members seem to be more comfortable retaining foreign educated professionals rather than extend the same opportunity to executives with local experience and education. The fact is, expatriates form a larger population of top executives within Philippine companies over naturally born Filipinos. What happens when the economic focus shifts from North America to Asia and Europe (which is imminent)? Will this mean a need for radical change of paradigms on the part of the Philippines?

This reality creates a double standard that inhibits corporations from maximizing benefits from their investments into human capital. While corporations promote western practices, they retain local styles and prejudices.

The cost of labor, for example, within typical Philippine companies are significantly less that any foreign counterpart (with the exception of China). While the workload is relatively similar, the compensation remains inconsistent with the organizations declarations of valuing human assets. Local corporations will spend more on technology, and less on people. Should there be opportunities for training, corporations will typically bind employees to performance contracts or employment bonds while depressing salary levels. It seems that corporations are intent on squeezing every ounce of creative juice from their employees without proportionately increasing the purchasing power of the same. The rationale behind this is usually maintaining competitive advantage by keeping overhead costs to a minimum. The problem is that most corporations lose a lot more by making investment decisions on other areas of their business. It would have been far more cost effective to invest in the lives of their people.

Our actions speak so loudly that our employees fail to hear what we are saying!

When we do find corporations who value their employees and demonstrate this by improving the lifestyles of their employees, we find them taken advantaged of by the very people who benefit from the company. Talk about a vicious cycle!

Labor laws play a significant role in the systemic problem. Labor codes are clearly biased towards laborers. It offers a level of false security that disproportionately disadvantages their employers and the very community it seeks to protect. Current labor laws revolve around the idea of tenure rather than sustainable value. Given this scenario, corporations end up reducing their exposure by depressing the wages of their people just to limit the exposure to financial risk. Just imagine a company that is in financial difficulty. Should the company decide to lay-off people to survive, it will end up killing itself completely. Instead of protecting and providing a means to rehabilitate itself, labor laws place priority on settling salaries over creditors without regarding the condition of its founders or incorporators.

I can go on and on and on discussing systemic dysfunctions but the objective here is to give the reader insight into the complexity that surrounds the issue of realizing benefits from human capital investments, and what considerations organizations need to be address when it comes to the challenge of realizing those desired benefits.

Given these conditions, how can corporations maximize their investments into human capital?

First, we must qualify what an investment into human capital really means. In simple terms, it is the investment of the company into the intellectual and functional growth of every employee within its domain. This involves creating intelligent policies, a culture conducive to personal and professional growth, functional and theoretical training, mentoring and leadership development, performance incentives, and competitive salaries. The focus of the investment is to create an environment where growth and experimentation are encouraged, an environment that showcases achievement, and environment that molds restrictive mental models into new progressive ones, and an investment in capturing the same for reuse throughout the entire organization.

The following are areas you may want to explore if you intend to maximize benefit from your human capital investments:

1. Modeling Leadership – people will duplicate the attitudes of their designated leaders. Make sure leaders are made accountable and responsible for their own actions, and are willing to do the very things they expect of their people.
2. Intelligent Policy –integrate a reward system into the framework of corporate policy rather than maintaining a purely punitive model. Make sure to integrate the same into performance management activities.
3. Safe Communication – establish “safe communication” systems that will allow people to be heard without fear of reprisals
4. Cross Fertilize Skills – promote a well rounded understanding of operations and functions for every employee by getting people to experience different roles within a department or business unit. This will prevent intellectual or functional atrophy from setting in.
5. Serialized or Organic Promotions – promote from within. Limit the number of outsiders who end up filling leadership positions within the company and make sure that promotions are based on the merit of performance. Don’t promote people to higher levels of incompetence simply because they know, or are associated with, the people at the higher echelons of the organization.
6. Create systems that showcase innovation and knowledge champions – make sure that people are recognized only for performance that goes above and beyond expectations. Remember to be sparing—to much recognition will minimize its impact on the organization.
7. Build systems that promote the reuse and enhancement of knowledge – make sure to build systems and mechanisms that allow knowledge holders to transform tacit knowledge into explicit form. Attrition is a reality that will never leave us as long as choice remains a part of free will. To protect the interests of the company and to prevent the company from being held hostage to the demands of key knowledge holders, it is important that such mechanisms be implemented.

If you wish to know more on this subject please feel free to send me an email at dennis@dbreyes.com. I will be more than happy to be of service.

Until next time...

The Dichotomy of Knowledge: De-Coupling and Integration and the Creation of a Knowledge Creating Organization

At the surface. the concepts of de-coupling and integration seem to be contrasting, mutually exclusive concepts. One deals with inoculation, the other consolidation. But when viewed in holistic terms, these are parts of the same whole—a true dichotomy.

Western thought and practices have largely been governed by Hellenic and Cartesian models. The western scientific worldview has likewise also been governed by Newtonian models. But the more we get to understand how the rest of the world thinks and the more prominent Eastern cultures become, the more we get to appreciate different ways of thinking, and different ways of managing what is known as well as what can be known.

The exclusivity of thought is necessitated by the fact that no knowledge, from an existential standpoint is comprehensive. Philosophers have tried to elaborate on gnosis from the earliest period of recorded history. Chinese philosophers have actually pre-dated much of the discussions of the West by at least a thousand years BCE. But much of these ancient works have only begun to emerge and gain popularity and acceptance as the rest of the world, of necessity, is now compelled to deal with the ever growing influence and importance of Asia in the world economy.

Progress in the areas of systems dynamics and systems thinking has opened up new avenues of thought that were once taken for granted. Studies in the area of systems dynamics have shown minute, and seemingly random changes that occur within a system can result in completely different outcomes while at the same time revealing the inherent nature of boundaries or parameters, once considered to inhibit growth and progress, as essential to growth in organic systems. Current studies in brain physiology have also resulted in a more revealing understanding of how organic systems store memory at the cellular level.

On the one hand, it is essential for systems to be free, but on the other hand it is equally important for the same system to be bound by parameters if growth is to occur. While it is important for teams to work towards an integrated direction, it is equally important for members of the team to work towards achieving individual aspirations. For individuals to achieve mastery over a given subject, mastery of several related areas is also necessitated. Complex systems, too, as another example, consist of multiple simple systems that are not apparently related or relating but form an integral part of the same whole.

In the same light, decoupling knowledge and integrating knowledge are both essential to the progression of knowledge.

These are important concepts to consider as it relates to information architecture and business intelligence. Key to information architecture is understanding and mapping key contextual and relational attributes between data elements. This provides the framework for establishing a rudimentary, multi-dimensional understanding of data as whole entities and provides a way for systems to deal with unstructured data (meta-metadata layer). It is a way for non-organic systems to handle what organic systems have little difficulty managing. Metadata provides, in simplistic terms, a way for non-organic systems to deal with information that are not necessarily related to any one specific entity in the same way organic or human beings handle perception, culture, intuition, etc. It provides data with rudimentary context.

Knowledge decoupling is reductionist in nature. Meaning, it breaks down entities in its simplest form. Knowledge integration, on the other hand, is holistic. But you cannot have one without the other. Unless you understand entity at its simplest form, you won’t be able to integrate the same into an holistic framework (or can you?).

One of the biggest challenges facing business intelligence initiatives is inherent in the scope and dimensions of the information they wish to store and re-use. Unless a key relationship can be established, critical information (often unknown) is left out of the equation. Too much emphasis is given to the details and not enough on context—a largely Newtonian approach. Metadata, due to its non-structured form remain in the periphery and is also limited in that metadata in the way it is currently implemented has no way of improving by itself.

An added challenge is the degree of relevance the information represents on the human side. Most advanced applications provide online analytical processing capabilities (OLAP), but the data used to create multiple contexts are limited to the predetermined dimensions of the data warehousing system. Further, these systems tend to overwhelm the end user with insufficient context to help in creating or enhancing knowledge. The assumption that every person who uses the system shares a common understanding and interpretation of common data sets, which most advanced applications are designed, is a misnomer. Systems either provide users with bits of information, or they overwhelm users with too much. Either extreme is not conducive to a knowledge creating environment.

While business intelligence systems are created as a means of establishing a common basis for understanding data, it must not limit the way data is, or can be, interpreted. Further, for business intelligence systems to remain valuable, it must be built with the inherent capacity to “learn”, or to append on each data entity on its own and extend meaning and relevance based on every context each entity was used and will be used. Each entity will literally take a life of its own. But it must also provide the function to allow it to filter what is offered to the user based on that specific user’s context—every time.

Context and relevance are bound in time. What is usually relevant today, was not necessarily relevant the previous week or the previous month, or the previous year. In reality today’s context may no longer be applicable tomorrow. Context and relevance will naturally scale and extend itself into new contexts and relevant relationships. It is in this regard that knowledge decoupling and knowledge integration play a significant role in managing knowledge repositories. Knowledge decoupling filters and creates relevance, while knowledge integration creates context and meaning—in between, serendipity occurs.

In what areas can we apply these concepts? Here are a few suggestions:

First, to begin towards the path of creating a knowledge creating environment that builds upon the awareness of this dichotomy, you need to carefully assess the readiness of your environment. It would be best to create micro communities of practice. These micro-communities need not launch a formal project. (I have built a specific methodology to help organizations develop such communities).

Second, it would also be prudent to assess the architecture of your technology infrastructure with a special emphasis on the data and application architectures implemented within your context to determine how you can incrementally move towards a service oriented framework (SOA). SOA will allow your organization to benefit from tight-coupling and loose coupling methodologies in application design and deployment, and allow you to re-use applications as services at the same time (software as services or SaS).

Third, the best places to start are the areas where functional domains intersect. These areas are usually a rich source of knowledge and opportunity but it can also present the highest level of complexity. Pick an area, then begin the conversation. Remember context is important.

Fourth, showcase learning and spread the word. Creating a knowledge creating environment means that you must allow knowledge to grow and evolve. Much like seeds, you need to sow it in every place throughout your organization, and beyond. Seeds will always germinate in fertile ground and the more seeds germinate, the higher the promise of a bountiful harvest.

If you need help, or you need to understand how to implement applied knowledge management within your organization, please feel free to contact me. I would be delighted to help you get on the path towards execution.

Learning Laboratories: Bridging the Knowledge Gap

The fundamental problem that persists in the Philippine educational system is not rooted in the materials or courseware used for education but the relative immaturity of its students and lack of real-world experience among its faculty.

While it is unclear how the Philippines ended up adopting the current model, or what the objectives were for doing so, what is clear and evident is that it needs to change. But changing an entire educational system is much more easily said than done. This would mean having to undo five decades of tradition deeply rooted in current educators, and having to challenge mental models that have been built on the existing model. In order to catch up with the rest of the world, we need to employ a level of innovation that would allow both models to coexist.

Unlike other western or eastern counterparts, Filipino students fall behind by a minimum of two years in their educational program. While most children begin schooling as early as the age of three, they complete their education in a relatively young age than their foreign counterparts. It seems that this model was designed to allow for a younger workforce, to equip the same with tertiary degrees at a very young age to make them more competitive than their global contemporaries allowing them to contribute to rebuilding the national economy as quickly as possible. While this intent is novel, it is riddled with assumptions that have been since proven false and, is replete with more problems that ultimately diminishes the value of its original intent.

Over the past 2 decades, the Philippines has been on a march towards economic recovery. Both public and private entities have been aggressively promoting the Philippines as a prime destination for business investments. But those that have ended up with a huge problem with their resource pool. The problem is two-fold: Mass and Competency.

The issue of mass (population) is further aggravated by the problem of emigration which induces brain-drain. The problem of competency can be traced back to the educational program in general. It seems to be the classic problem of short-term goals conflicting with long term objectives. The short-term goals keep the country from achieving its long term objectives.

Due to the depressed economic condition that pervades every layer of society, a huge part of the country’s youth are forced to take on vocational type programs just so they could minimize their costs and land a job within a couple of years. Upon closer examination however, this model presents more problems than it solves. The vocational model contributes to a higher rate of unemployment in the long term simply because there are too many vocational graduates that are filling limited vocational, low-paying opportunities. With a huge supply of vocational workers and a limited number of opportunities, employers tend to depress wages which limits the purchasing power of workers, ultimately affecting the economy’s health as a whole.

Moreover, due to the lack of university graduates (as most have opted to take the vocation path), investors end up eliminating the country as a place to establish high paying opportunities. To make things worse, it increases the level of frustration of those who completed college compelling them to seek employment abroad. This is a vicious cycle that benefits only a few (unscrupulous entrepreneurs who put up all sorts of vocational schools to deepen their personal pockets).

If we try to implement changes at the policy and regulatory levels, bureaucracy becomes the problem. Due to the lack of a system of belief, regulators are often suspicious of the motives of their counterparts.

The fact remains: unless we arrest this problem, a bright economic future for the Philippines is only a false promise. So, what can we do?

To solve the problem, a logical, left-brained approach would be to take a reductionist approach and isolate a problem area that could yield long term benefits when solved. This area would be to first bridge the maturity gap in education.

My premise is simple: if we are able to solve the maturity gap we will be able to present an experience and more knowledgeable workforce to investors who intend to bring in opportunities that provide high-paying jobs.

The solution: Learning Laboratories.

To implement learning laboratories as part of the program of universities will bring in the following benefits:

First, it will address the issue of maturity by exposing students to a real-world environment without having to forego critical areas of study. We can’t immediately change the age of graduating students or change the length of educational programs. But what we can immediately change is the substance of the program allowing schools to produce higher quality graduates within the same amount of time.

Second, it will establish subject matter relevance on the part of the students. A majority of students find it difficult to understand how Algebra, Geometry, Physics, English, History, or Social Studies are important. By employing the Learning Laboratory model, students will immediately realize its importance and find it irresistible to know more about those subjects. The difference lies in the employed model. A strict lecture based learning environment, without immediate application does not help create relevance. Memorization is not crucial to intelligence, it is knowing where to find the information you need and how to apply the information in a constructive and progressive manner that is.

Third, it will create a professional environment that not only benefits the students but also the instructors and professors. Almost 98% of the existing faculty base have no real-world business experience in employing the subjects they teach. This is especially true of computer science instructors. A learning laboratory will compel faculty to become functional experts in their respective fields.

Fourth, it will stimulate the needed integration between industry and academe. Learning laboratories create a substantial foundation for research and development. The moment industry determines that the fields of research benefit their own interests, integration will follow. But until industry can be convinced that the faculty base of universities are experienced and respected in their fields of study, they will largely be ignored.

Finally, by the time a student graduates from university studies, he or she would have had 3 years of applied experience in their chosen field. Meaning, not only will they know their area of specialization, they would have also developed critical soft-skills, would have experience working in teams, understand the value of collaboration, understand stress management, and applied their knowledge to solve real-world business problems. It will also pave the groundwork for them to desire higher education built on knowledge and experience.

Learning laboratories will allow the old and the emerging to coexist in the short term. As progress is achieved, programs will be enhanced and upgraded. Such an upgrade or enhancement would only mean higher quality graduates. So in the long term, learning laboratories will benefit everyone for the long term.

It has the potential to solve funding issues that are commonly used as an excuse not to improve the quality of education. It will give students a strong reason to learn more, and colleges to invest in highly qualified professionals, for parents and guardians to invest in good and longer term education since the promise of opportunity in the future would really be a “true promise” and not a false one.

Until next time...

Applied KM: On Making Informed Decisions

Applied knowledge management is a constantly evolving discipline and practice. Although everyone employs some form of knowledge to make informed decisions on a daily basis, the unique characteristic of KM practitioners is that they are constantly looking at ways to improve the way information is structured to form relevant knowledge to help others make informed decisions.

Informed decisions have a limited scope. Most of the time, it is based exclusively on historical information and limited to a forecast of how the future might look like. This is due to the fact that human beings do not possess omniscience and immutability (the two attributes that would definitely help us make informed decisions). Those of us who have had to make critical decisions have also had the experience of being dead wrong about our assumptions, most of us have had to live with bad decisions which looked, at the time they were made, like the best course of action to take, only to find that we missed a crucial element in the process.

What makes us so averse to making important decisions is the realization that we really don't know what we don't know. We try to build mechanisms that will innoculate us from the effects of our decisions as there are literally hundreds of factors that can cause those decisions to result in negative consequences that we did not consider.

This aversion results in increased stress levels especially when confronted with the need to make immediate decisions where you simply do not have the time to think things through well enough to make an informed choice.

Technology offers alternatives or solutions that help us make informed decisions quickly. Upon closer examination, however, it is a well-dressed facade that neatly clusters information into structures that fit how we want to see the information and not necessarily what we need to know.

How can we ensure that the choices we make today will not result in negative consequences in the near or distant future? The answer? We can't.

This is where the merits of applied KM comes into play. Applied KM is all about building systems and mechanisms that will allow members within a knowledge ecology to learn, grow, evolve, and share experiences that provides participants with a workable framework to turn negative consequences into constructive experiences.

As technology advances, as processing speeds increase, as storage becomes cheaper, and as communications become more affordable, the more people will be subject to the pressure of time. Instead of using the time to think (as technology helps us shorten the time required to gather data), most will almost certainly try to match processing speeds in making their choices. We must remember, that technology allows us to gather data quickly so that we can spend the time to apply our knoweldge to create new knowledge from the data technology provides us with.

Computers could have the potential of matching the processing power of the human brain, but it can never replace the human "being". "Being" is key to knowledge. Computers lack the capability of experience. The data fed into computers result from the experiences of another. As such, they are limited in nature.

Applied KM brings value back to the human being. Experience, culture, learning, communication, altruism, context, worldview, religion, family, perception, doubt, community, failure, emotion, intuition. All of these make human beings far more superior than the most advanced of computer systems.

Let us take the events that led up to the infamous 9/11 experience as an example. Every US official will agree that what failed was not the computer systems (and the US employs the best of the best in terms of technology) but the human side of intelligence. In my view, the real failure was in depending too much on technology and minimizing the value of the human side of intelligence. It is not human intelligence that failed. The failure is the result of too much dependence on technology.

This is true of most corporations around the world. They have developed a convoluted dependence on technology. Why? To reduce complexity. This perception is counter-intuitive. Human interactions will always be complex so allowing simple systems (even the most complex of mathematical equations are still simple when compared to how human beings think) to handle complex situations is simply un-intelligent and complacent. There are literally hundreds of thousands of potential contexts that any individual can choose to create and employ.

How then could you make informed decisions? Here are some principles:

First, embrace complexity. Complexity is part of life. The less we try to minimize it, the more we learn how to progressively deal with it. For example, have you ever been in a software development project where you found your team dealing with increased scope? This is due to knowledge progression. The more people learn, the more questions arise; the more questions arise, the higher the levels of complexity is introduced. Circumventing this process will only result in short-circuits.

Second, form a collaborative team. If two heads are better than one, five heads are still more effective than a terrabyte of data. Listen to experiences, entertain opinions, value intuition. Value being human.

Third, take the time to learn. Try not to pressure yourself to make decisions without an adequate understanding of context (or what has been coined as a 360 degree view) in multiple dimensions. Remember that the reason why you are being forced into making a quick decision is most likely due to a quick decision that generated the situation you are trying to solve. Never try to solve the problem with the same behavior or thinking that created it in the first place.

Fourth, when employing technology, design systems that are able to provide relevance through context at the user level and processes that will allow these contexts to evolve through collaboration and sharing.

Fifth, constantly subject yourself to new methods of learning. Unless the person analyzing information is capable of interpreting the same information in multiple ways, data will remain non-relevant and useless.

Remember, learners prepare the world for tomorrow.

Until next time.

Chaos of Thought and Complexity of Action...

The transition between order to a higher form of order is chaos.

This is quite evident in the way we communicate with others. Let's explore this further using the assumption that participants in a coversation speak the same language and are familiar with the same customs and culture, and are of the same gender.

The framework we use to communicate with the world around us is a learned framework. We were initially exposed to this as early as birth. As our brains developed we slowly build upon those experiences over time. By the time we say our first word, we would have developed simple concepts and a simple dictionary. Most of the words toddlers first say have to do with something directly relating to food, pain, and relationships (mama, papa, etc.). Over time, as our brains develop, we begin to absorb every facet of our environment which triggers specific responses that elicit a wide range of emotions. By the time we reach the teen years, the things we have learned from our childhood are suddenly challenged by a world of contradiction. It is at this stage where we begin to test out new things, experience new things, entertain ideas, and learn new skills that will eventually make up the adult we are today.

Everytime we talk to someone else, we are going from order-to-chaos-to-order. How so? The speaker verbalizes ideas in a way that is most organized for him. However, the listener would still have to sort through what was said, match this against how he has understood the subject, organize it according to how he wants it before he can provide a response to it. Responses will vary.

The amazing thing is that a word, upon leaving the lips of the speaker, enters a world of chaos. It cannot be organized or framed in such a way so that those who will end up listening and receiving can simply store the same word in its current form. It has to be filtered and contextualized. This fact relates to abstracts and absolutes. It is only when the listener receives the word, matches it with what he knows it means, puts it into context, and only then will he determine how to respond. The point at which the listener responds to the speaker is the moment where order has been achieved on the part of the listener.

Tacit order is subjective. Explicit order is relative.

Tacit order is as unique as a fingerprint mark or DNA sequence. But unlike the latter, the former is subject to constant change without losing its uniqueness. It evolves, mutates, shifts, assimilates in forms that will stall even the most powerful of Alpha computers. And here we are only beginning to describe in albeit simplistic terms how human beings process information available in their environment.

Tacit conclusions form dispositions that rationalize action. It is this fact that makes human activity inherently complex. Action merges personality, world view, customs, understanding, personal style, character, social parameters, etc. into the entire mix. The more complex a social activity becomes, the more chaotic individual thought becomes. But the more we adopt to the chaos of thought, the more likely are we able to gain advances in understanding each other and prevent us from adding an additional layer of complexity to the way we think and process information.

Scientist have been hard at work to help us further understand the physiology of thought. Advances in the field of applied synaptics have help us form what could be the minute beginning of understanding, but we are definitely a long way from true comprehension.

So, the next time you talk to someone, remember what may seem simple for you to understand is not necessarily true for others. So make sure you become much more accomodating and patient if you really wish to be understood by others.