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Sunrise in the Catskills (Thomas Cole,
1826)
K-STREAM™ and The New Knowledge Management
(Co-authored with Mark W. McElroy)
"The New Knowledge Management" (TNKM) is about managing Knowledge
Production and Integration and their outcomes. Its primary focus,
however, is not on policies and programs that directly create and
integrate knowledge, but rather on policies and programs that reinforce
the self-organizing tendencies of agents in organizations to perform
the sub-processes of Knowledge Production and Integration. So
that leads to the first dictum of TNKM practice:
- Don’t
try to cause Knowledge Creation. Instead create and maintain
policies and programs that enable people to do their own Knowledge
Creation in response to Knowledge Gaps (knowledge problems) that are
preventing them from reaching their objectives.
Next, how does one create and maintain such policies and
programs? TNKM’s answer is that this should be done using the
K-STREAM™ Methodology, which provides a comprehensive outline of how to
practice TNKM and to implement knowledge processing policies and
programs. The phases of K-STREAM™, however, are not executed
using a “waterfall” model of workflow. Rather, K-STREAM™
specifies a “recursive methodology” with many opportunities to return
to previous errors and correct them, and with a workflow pattern that
is ”iterative and incremental.” A view of the phases of K-STREAM™
is illustrated in Figure 1
Figure 1: The Phases of K-STREAM™
Here are some of the key highlights of K-STREAM™ practice, expressed in the form of steps:
1. The objectives of a KM project or program and any Knowledge Problems
to be solved in reaching it must be defined. A variety of methods
may be used to do this. But K-STREAM™ favors Problem
Specification workshops to do so. 2. Once the objective of new policies and/or programs are specified,
all phases of an intervention project are planned. Plans are
adjusted in response to changing conditions throughout the process. 3. An Ontology Model is defined for the project. This model is
the basis of a variety of modeling, descriptive, analytical, and
evaluation tasks and is the beginning of a cognitive map for the
project or program. KMCI has developed an ontology template that
provides a physical expression of its conceptual frameworks, including
the CAS (complex adaptive systems) framework to use as a starting
point. The template can then be modified using facilitation
sessions, exchanges in communities of inquiry, knowledge cafes, expert
interactions facilitated by expertise location applications, and other
interactive and/or mind-mapping techniques. 4. A Measurement Model structure is created using the Ontology Model to
produce ratio scales of all the key criterion and indicator variables
in the model. Facilitation sessions are used to perform the
measurement modeling, assisted by software for supporting such sessions
and post-session modeling and analysis. 5. We then set about to describe the Current Environment, the Target
Environment, and the gap between them. In developing the Target
Environment description, K-STREAM™ uses the TNKM normative model of The
Open Enterprise (OE), which is provided to K-STREAM™ licensees by KMCI,
as a benchmark template, and also facilitation sessions. 6. Beginning with the Ontology Model, and referencing the Measurement
Model, we begin to get at cause, policy and program impact, and
dynamics by first selecting key variables for an Impact Model
specifying causal relationships, and then by specifying competing
structures of causal relationships envisioning policy and program
impact. A variety of tools may be used in initially laying out
the model, and communities of inquiry, social network analysis, value
network analysis, story-telling, mind-mapping, IT tools for searching
out relevant information, and facilitation can also assist the modeling
task. 7. What is key in terms of practice, however, is to develop cause-and
effect relations among a relatively small set of variables that can
then be used as inputs into simulation and data analysis tools.
It’s important in understanding this kind of activity, to realize that
alternative policy and program alternatives are included in this
modeling effort. One of its primary purposes is to provide a
basis for both planning the likely impact of these alternatives, and
for evaluating their impact after policies and programs are implemented. 8. In developing the Impact Model described earlier in step 6, and
consistent with the first TNKM dictum mentioned above, it is crucial to
TNKM that KM practitioners seek to create and maintain causal
structures that are aimed at reinforcing the self-organizing tendencies
of people to perform Knowledge Processing in particular ways.
Mark McElroy, Steve Cavaleri, and Joseph Firestone (all long-time
principals of KMCI) have developed a patent-pending method called The
Policy Synchronization Method™ (PSM). PSM, under license from
Macroinnovation, LLC, is used in K-STREAM™ to guide causal and dynamic
modeling and to help guide the transition from the Current Environment
to the preferred Target Environment of the Open Enterprise (OE). 9. Once step 6 has produced some alternative causal structures (Impact
Models), these are used as starting points in simulation studies that
compare competing KM interventions both before and after the fact, that
more easily accommodate the introduction of feedback relationships into
our models, and that facilitate measuring impact. The key
practice element here is to use simulation to understand and measure
the dynamics and impact of KM interventions intended to enhance
Knowledge Production and Integration. 10. Another element of K-STREAM™ practice is to go beyond process or
financial impact to measure non-monetary ROI. This is done by
developing value interpretive benefit and cost models. The models
allow comparison of monetary and non-monetary impacts of KM
interventions on the same ratio scale of intrinsic value.
Facilitation techniques, along with communities of inquiry and
supporting software, are useful here in eliciting the priority
judgements needed for the models. 11. An important continuing element of K-STREAM™ practice is Knowledge
Claim Evaluation. All the knowledge-producing tasks listed above:
problem recognition, ontology modeling, measurement modeling, gap
assessment, causal/impact modeling, and measuring benefits and costs of
KM impact, involve both Knowledge Claim Formulation and Knowledge Claim
Evaluation (KCE). We perform KCE using the framework presented in
Chapter 5 of “Key Issues in The New Knowledge Management,” by Firestone
and McElroy (Butterworth-Heinemann, 2003). The KCE framework
offers a number of evaluation criteria and also recognizes that other
criteria may be added at any time if they seem appropriate to a
particular need. The concept underlying KCE (i.e., the one
favored in TNKM) is “Fair Comparison” of competing alternatives.
Value judgments and risk analysis and measurement are built into the
KCE process (again, see Chapter 5 of “Key Issues…”). 12. After an intervention is implemented, K-STREAM™ prescribes
continuous monitoring of impact, benefits, and costs traceable to the
intervention. To do this we use measurement tools including
business performance metrics specified in the Measurement Model.
In addition, TNKM practice also requires that a content analysis tool
capable of mapping out changes in the artifact portion of an
organization’s Distributed Organizational Knowledge Base (DOKB) be used
to help in measuring the impact of KM interventions. 13. Lastly, this summary of K-STREAM™ practice is admittedly
sparse. We have not said much about IT tools and have only
indicated in a sketchy way where a number of the most recognizable KM
techniques would fit into this picture. Even more, however, we’ve
not included discussion of the full range of possibilities of practice
that can enter K-STREAM™. Indeed, TNKM practice is an open
structure and any of the classical techniques of the social sciences or
of Quality Management may prove useful in KM projects using K-STREAM™. TNKM does specify a pattern of practice for KM, and certainly advocates
a heavy emphasis on frameworks, measurement, modeling, impact, value,
and risk analysis, and the Knowledge Life Cycle, including “Fair
Comparison”-based KCE for Knowledge Production and Integration.
But, it is fundamentally open as to which KM intervention techniques or
combinations of techniques are keys to TNKM. They may or
may not be key practices in a particular project, policy and program
context; but Communities of Practice, Social Network Analysis, Value
Network Analysis, Storytelling, Knowledge Cafes, Facilitation
Sessions, Teams, Portal Systems, Best Practices Systems (when properly
constructed to include meta-claims), Mind Mapping, Expertise Locators,
and other popular interventions are all legitimate elements in a
K-STREAM™ toolbox.
K-STREAM™ is the only methodology for practicing The New Knowledge Management. It is also:
-
The only comprehensive KM methodology that addresses Knowledge
Production, Knowledge Integration, and processes at the KM-Level itself
-
The only KM Methodology that explicitly recognizes the role of
self-organization in Knowledge Processing and Knowledge Management and
does it through a patent-pending method
-
The only KM Methodology that provides both a comprehensive conceptual
framework and an Ontology Software Template for applying it to
measurement, causal, dynamic, and impact modeling, and measuring costs
and benefits of KM interventions
-
The only KM Methodology that both recommends a set of core tools for
tasks common to all KM projects, and at the same time provides an open
tool box in that it allows the use of a the wide variety of methods,
techniques, tools, and procedures that have been developed in the
Social Sciences, Operations Research And Management Science, Quality
Management, and KM itself.
For More InformationHere is specific information about KMCI's K-STREAM™ Certificate Program
in Knowledge Management Strategy and Methodology. If you're interested
in KM practice, you'll want to look carefully at this workshop,
team-taught by the authors of this post. It provides specific
instruction in implementing programs and projects in The New Knowledge
Management. We believe that K-STREAM™ is the most comprehensive
one-week face-to-face workshop in KM Methodology available today. But
you will evaluate that for yourself by looking at comparable offerings.
You’ll find more information on TNKM at three web sites: www.dkms.com,
www.macroinnovation.com, and www.kmci.org. Many papers on the New
Knowledge Management are available for downloading there. Our Excerpt from The Open Enterprise . . . may also be purchased there. Our print books: Mark W. McElroy, The New Knowledge Management, my Enterprise Information Portals and Knowledge Management, and our Key Issues in The New Knowledge Management, are available at Amazon, Barnes and Noble, or KMCI Press.
6:51:53 PM 
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Stonehenge (J. W. M. Turner, 1828)
Are There Core Tools and Techniques of Knowledge
Management?
(Co-authored with Mark W. McElroy)
Where is the Core of KM Practice?
The goal of Knowledge Management is to enhance Knowledge Processing and
indirectly to improve the quality of knowledge claims, beliefs, and
ultimately business decision making.
Sometimes it is said that KM includes a concern with how knowledge in organizations is used
in business processes and business decision making. But knowledge is
used in every decision we make, and in every process we execute. So it
seems that if we designated knowledge use as a concern of Knowledge
Management, we would be saying that KM extends into all operational
areas of managerial concern. This is an untenable, rather
imperialistic, position that makes KM overlap substantially with the
areas of responsibility of other forms of management, and denies that
operational business managers, as opposed to Knowledge Managers, have
the responsibility for the effective use of knowledge in operational
business domains.
To accomplish the goal of KM, Knowledge Managers make policies and then
implement them through programs, procedures, and activities. So KM is
about:
(1) Determining the current state of Knowledge Processing
(2) Visualizing a target environment characterized by multiple objectives
(3) Determining the gap between (1) and (2)
(4) Planning policies, programs, procedures and activities to close the gap
(5) Implementing the outcomes of (4)
- Monitoring and Evaluating
(6) Measuring and evaluating the impact of (5) on (3) and on aspects of the enterprise through time
(7) Adjusting (4) and (5)
- Monitoring and Evaluating
(8) Measuring and evaluating impact again
- Planning, Acting, Monitoring, and Evaluating
(9) Adjusting again, and so on until the cycle starts again with a reformulation of (2) through (4)
What does the above suggest for KM practice? Most generally, we think,
it suggests that KM may, indeed, have a family of core techniques and
tools that are needed to execute the above pattern that should be used
in nearly every KM intervention.
Current practice in KM is not focused on such a central core, but
rather on implementing specific solutions that are thought to be worth
trying to bring benefits to the enterprise. Interventions such as
enterprise information portals, communities of practice, knowledge
cafés, social network analysis, and story-telling projects, however
helpful they may be in developing KM solutions, are not at the core of
KM. That is,
they are not necessarily part of any KM project implementing an
intervention designed to enhance knowledge processing and to evaluate
the results of such an intervention. Rather, they are knowledge
processing solutions that Knowledge Managers sometimes implement, quite
separate and apart from the tools used by Knowledge Managers in support
of their own activities and interventions, more generally.
What are some of the techniques and tools that are, or at least should
be, part of every KM intervention, because they are indispensable in
implementing the above pattern of KM intervention?
Planning and Implementing: Project Management and PM Tools
Everyday Knowledge Management activity is about:
- Symbolic Representation (of the KM function to others),
- Building External Relationships with Others Practicing KM
- Leadership
- KM-level Knowledge Production
- KM level Knowledge Integration
- Crisis Handling
- Changing Knowledge Processing Rules
- Negotiating for Resources with Representatives of Other Organizational Processes, and
- Resource Allocation for knowledge processes and for other KM processes
But one or more of these types of activities are often combined in
making policies, and initiating, implementing, and evaluating programs
and in planning and implementing projects for doing these things. Most
large organizations perform projects to make KM interventions and use
project management tools. Knowledge of them is so common we won’t even
bother to mention any. Suffice it to say that project management
software is one of the core tools of KM and this fact is forgotten all
too frequently in discussions of KM tools and techniques.
Planning: Visualization and Business Drawing Applications
KM interventions require visualization of static and dynamic relations
in the enterprise, including hierarchical relations among entities and
among attributes. A good way to begin such visualization is to use
vector-based business drawing software such as SmartDraw, Visio, Micrographix, or Flowcharter.
Such programs can produce flow charts, business process diagrams,
network diagrams, UML diagrams, tree diagrams, cause-and-effect
(fishbone) diagrams and many other types.
Planning: Modeling Means-ends Connections, The Analytic Hierarchy Process (AHP), and Decision Tree Tools
Planning KM interventions involves specifying a set of tasks that, when
implemented, one expects will enhance some aspect of knowledge
processing. We arrive at these tasks by thinking through strategies and
tactics that we think will close the gap between the current state of
knowledge processing and the future state we desire. The set of tasks
are the means to various sub-objectives, objectives and finally the
goal state of knowledge processing. Software tools that can help us to
visualize this sort of task, objective, sub-objective, and goal
hierarchy include software that specifies decision trees or analytical
hierarchies such as Expert Choice, InfoHarvest, and Ergo.
These applications are very good at specifying measurement relations,
means-ends connections and at assembling them into hierarchies, but
they are not formidable simulation tools for exploring the consequences
of analytic hierarchy theory structures.
Planning: Simulation Modeling Techniques and Tools
There are, however, other simulation tools we can use to build and
simulate models based on inputs from the results of analytic hierarchy
modeling. Simulation tools are available exhibiting a great range of
power and capabilities. For KM, however, we favor System Dynamics tools
because they are relatively simple to use and support visualization and
understanding of models. The leading toolsets in this area at present
are ithink and Stella (High Performance Systems), Vensim (Ventana), and Powersim (Powersim Software).
Planning: Balanced Scorecards and Business Performance Measurement Tools
The field of Business Performance Measurement (BPM) is burgeoning.
Balanced Scorecard (BSC) vendors are now plentiful and business
performance measurement and monitoring software is becoming
commonplace. BPM and BSC tools are important for KM because we need to
both plan and evaluate the impact of KM on the organization generally,
and business performance metrics are essential to these tasks. BSC/BPM
tools must be used with care. Sucess is dependent on carefully relating
good conceptual frameworks to good descriptors and indicators. The
tools themselves don't guarantee the quality of the underlying
measurement modeling associated with using them. Vendors
include: Cognos, Crystal Decisions, Dialog Strategy, Open Ratings, Active Strategy, Corvu, Ergometrics, QPR Software, SAS, and others.
Impact Analysis (Monitoring and Evaluating): Model Testing Techniques and Tools
Once plans are implemented, the results of interventions must be
monitored and evaluated and the impact of intervention measured. A
range of techniques are useful for impact measurement and evaluation.
First, techniques and tools used in planning, such as AHP, System
Dynamics, and BPM/BSC tools, are all relevant here, as well. In
addition, however, techniques and software tools of statistics and
Artificial Intelligence (AI) must be used to analyze results and test
previously formulated models. The four primary statistical analysis
vendors, SAS, SPSS, Statistica, and Insightful,
all provide a range of indispensable tools of data transformation and
multivariate analysis as well as more recently developed capabilities
in neural networks and tree analysis. Products from smaller companies
such as (a) Ward Systems, Inc. and Neurosolutions, Inc. specializing in neural network, fuzzy, and genetic algorithmic modeling, (b) Salford Systems, Inc. specializing in tree analysis and Multi-Attribute Regression Splines (MARS) predictive analysis, and (c) Megaputer inc., specializing in a range of the newer AI-based techniques of analysis, are also important.
Tracking (Monitoring and Evaluating): Semantic Analysis and Networking Techniques and Tools
The primary application of these tools is in monitoring and evaluating
the continuing impact of KM interventions. Specifically, we must
measure the continuing impact of interventions on quality of Knowledge
processing and knowledge outcomes, by tracking patterns of knowledge
production and distinguishing knowledge from information in order to
measure whether our interventions are effective in producing knowledge
and integrating it into business processes over time. In order to do
this, we need a tool that models and tracks both knowledge claims and
the meta-claims appearing in text content that describe their
performance. Two products with at least some of the capability needed
to do this are Semagix and Clear Forest, making them alternative candidate core tools of KM.
Conclusion: What about “KM” Techniques and Tools?
With the possible exception of semantic analysis techniques and tools,
none of the other categories identified are normally associated with
KM. Instead, KM publications, conferences, e-mail list serves, and
books most often focus on: Communities of Practice, Story-Telling, Best
Practices Databases, Enterprise Information and "Knowledge" Portals,
Social Network Analysis, “Open Spaces”, Knowledge Cafés, and others.
All of these can be useful KM interventions or components of
interventions. But all of them are optional, and none of them
essential, in every KM project, because the interventions chosen are
likely to vary with the problems Knowledge Managers are trying to
solve.
The moral of the story we are telling in this paper is that there are techniques and tools, not unique to KM, but nevertheless essential for nearly every KM project
that all KM practitioners should be exposed to. These tools and
techniques are not directly focused on KM interventions, but on
planning them, evaluating them, and tracking their consequences. These
tools and techniques include Project Management, Visualization and
Drawing tools, Analytic Hierarchy Process, System Dynamics and
simulation tools more generally, Balanced Scorecard and Business
Performance Measurement, Statistical and AI analytical tools, and
finally Semantic Analysis and Networking techniques and tools. They are
essential because they always support implementing key steps in KM
project interventions. It is remarkable that they are not front and
center in KM discussions. They should be, and hopefully this paper will
go some way toward securing them their proper place in the
constellation of KM practice and education.
For More Information
Specific Information about the core tools in KM is available in KMCI's K-STREAM™ Certificate Program
in Knowledge Management Strategy and Methodology. If you're interested
in KM practice, you'll want to look carefully at this workshop,
team-taught by the authors of this post. It provides specific
instruction in implementing programs and projects in The New Knowledge
Management. We believe that K-STREAM™ is the most comprehensive
one-week face-to-face workshop in KM Methodology available today. But
you will evaluate that for yourself by looking at comparable offerings.
You’ll find more information on TNKM at three web sites: www.dkms.com,
www.macroinnovation.com, and www.kmci.org. Many papers on the New
Knowledge Management are available for downloading there. Our Excerpt from The Open Enterprise . . . may also be purchased there. Our print books: Mark W. McElroy, The New Knowledge Management, my Enterprise Information Portals and Knowledge Management, and our Key Issues in The New Knowledge Management, are available at Amazon, Barnes and Noble, or KMCI Press.
4:20:36 PM
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Evening of the Deluge (J. W. M. Turner, 1843)
Knowledge Management: Taking It From the Top
Elsewhere (in Key Issues . . ., Ch. 3) Mark
McElroy and I have provided a critical commentary on a variety of
definitions of KM. Frankly, I think they are mostly unclear about the
"knowledge" component, and equally unclear about the "management"
component of the phrase that names our field. But since there is such
disagreement over this key definition, I think it's useful for me to
state the view of "The New Knowledge Management" (TNKM) on KM itself.
Knowledge: the Unified Theory
Human systems produce knowledge to help them adapt to their
environment. Knowledge is used in decision making and as an enabler of
actions that follow decisions. Knowledge is an outcome
of some of the system behavioral processes I've written about in
previous posts, but it is not the behavioral processes, themselves.
Instead, it is an encoded, tested, evaluated, and surviving structure
of information (e.g. DNA instructions, beliefs, and linguistic claims)
whose biological function is to help the system creating it to adapt.
In the TNKM view, there are three types of knowledge that fit this definition:
- Encoded structures in physical systems allowing those objects to adapt to their environment (genetic and neural knowledge);
- Tested, evaluated, and surviving beliefs (in minds) about the
world (mental knowledge), the good, the right, and the beautiful; and
- Tested, evaluated, and surviving, sharable (objective),
linguistic formulations about the world (artifact-based or cultural
knowledge).
Following Popper's account ( Popper and Eccles, 1977, Pp. 120-147),
evolution begins within material/physical structures. When biological
creatures evolve, they first develop genetic structures (material knowledge)
that allow them to achieve their goals through limited adaptive and
learning capabilities. They have brains, but do not have minds. Minds (mental processes) evolve as “control mechanisms for the brain.” And as we have seen, minds allow agents to develop beliefs for tracking reality (mental knowledge)
and enhancing adaptation. However, the beliefs created by mind cannot
incorporate an objective shared perspective on reality. Therefore,
their fit with external conditions is less than ideal.
So evolution proceeds further. It creates creatures that not only have
brains, minds, and consciousness, but also creatures that have language and culture.
These creatures can use language and culture to create knowledge claims
that incorporate a sharable perspective on reality, and this
perspective, in turn, with continued inquiry, can produce knowledge
claims that benefit from this shared perspective and that can even
correspond closely with reality. In other words, the creation of language and culture creates more objective formulations (structures or networks of knowledge claims)
that place constraints on the personal, subjective beliefs of the mind.
These subjective beliefs, in turn, help it to better understand
reality, which it must do if it is to fulfill its role as the
controller of behavior.
The notion that the mind is “a control mechanism for the brain” is part
of Popper’s more general formulation of the evolutionary development of
a system of “plastic controls” for any organism. The basic idea is that
higher order control systems emerge out of lower order ones and
exercise a regulative function on them through “downward causation”
involving selection of lower level functional activities. Thus, mental
self-consciousness allows us to regulate and affect, without
determining, impulses in the brain. And language-moderated social
interactions and cultural products, in their turn, have a regulative
effect on what we believe and more generally on states of mind. For
more detail, see Popper (1972, pp. 235-255).
Management
Since the beginning of the 20th Century, definitions and views of
management have proliferated, as has the use of the term "management"
to describe any activity that seems to involve organizing anybody or
anything. In the human area, the general trend is from
command-and-control forms of management, that assume a deterministic
view of the world with command as the cause and everything else as an
effect; to management that emphasizes motivating, leading, and enabling
workers who cannot be commanded if one wants good results, because both
they and management are part of a complex adaptive system whose
behavioral properties emerge as a result of self-organizing patterns of
interaction.
These days, students of management tend to view it as what managers do.
The classic work in that area is Henry Mintzberg's. He categorized
management activity as: interpersonal, including figurehead or symbolic
representing activity, leading, building external relations,
information processing, including monitoring and describing events and
occurrences, and disseminating information, and decision processing
activity including entrepreneurial, crisis handling, resource
allocating, and negotiating activity. I accept Mintzberg's viewpoint in
general and believe that it provides the outlines of a theoretical
framework for describing KM activity (See Key Issues . . ., Ch. 3).
Organizational Knowledge Management: What is it?
The three types of knowledge distinguished in the unified theory are
used in decisions and ultimately in organizational and group behavioral
processes. New mental and cultural knowledge are both outcomes of the
interaction of such processes with individual processes. And even
though organizational processes can't create new genetic knowledge,
they can influence the neural-based aspect of organizations directly
through recruitment processes, and changes in neural knowledge
indirectly through their effects on cultural and mental knowledge,
which in turn has an impact on neural patterning.
Are all or most of the processes affecting knowledge, management
processes? TNKM says no. New but routine perceptual knowledge is
produced in operational business and business management processes (See
Organizational Problem Solving or Key Issues in the New Knowledge
Management, Ch. 2). New problem-solving knowledge, including general
knowledge, is produced in knowledge processes, which involve doing knowledge production and integration, but not managing them (See the three-tier model).
There are other processes existing in organizations that affect
knowledge, apart from operational business, management, and knowledge
processes. These are comprised of activities of the sort identified by
Mintzberg and listed earlier. They are the organization's KM processes.
That is, they are what knowledge management is.
Of course, KM processes differ a bit from Mintzberg's categorization.
For one thing, they are not targeted on the organizational system, but
on its knowledge processes. For another, instead of information
processing, they include knowledge production and knowledge integration
directed at solving problems of Knowledge Management and, lastly,
entrepreneurial KM processes are those that change the rules governing
knowledge processing.
The organizational function, or, if you like, the
core value proposition of KM processes is to maximize the quality of
available problem solving knowledge in organizations in a sustainable
way. That can't be done directly, but only by management activity targeted on enhancing knowledge processing itself.
It also can't be done through command-and-control management of such
processing, because knowledge processing is an emergent that results
from self-organizing activity directed at problems. To enhance
knowledge processing, KM has to enable it by reinforcing the
self-organizing activities comprising it. These self-organizing
activities integrate in organizations to form the sub-processes of
knowledge production and integration, the targets of KM. I've talked
about these in a number of earlier posts and will continue to talk
about them in future posts.
KM: The Discipline
So far, I've characterized Knowledge Management as an activity-based
process phenomenon. But the term can also be used to refer to a
discipline. In that case, the TNKM view, consistent with the process
use of the term, is that KM is a management discipline that focuses on
enhancing Knowledge processing.
For More Information
You’ll find more information on TNKM at three web sites: www.dkms.com,
www.macroinnovation.com, and www.kmci.org. Many papers on the New
Knowledge Management are available for downloading there. Our Excerpt from The Open Enterprise . . . may also be purchased there. Our print books: Mark W. McElroy, The New Knowledge Management, my Enterprise Information Portals and Knowledge Management, and our Key Issues in The New Knowledge Management, are available at Amazon, Barnes and Noble, or KMCI Press.
2:54:14 PM
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