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Wednesday, May 12, 2004

Sunrise in the Catskills (Thomas Cole, 1826)

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 Information

Here 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:,, and 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    comment []

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:

  • Planning

(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

  • Acting

(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

  • Planning and Acting

(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:,, and 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    comment []

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).


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:,, and 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    comment []

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