Knowledge Engineering

In the traditional approach to systems design, a system analyst, together with the ultimate end-users, or clients, for the project, will complete a functional specification of the system. At that point, the project is essentially in the hands of professional project management and programming staff, because that group possesses the knowledge and skill required to deliver the agreed upon features and functions. In the development of knowledge systems, this is simply not the case. Following the specification of function, a new problem arises. This is because it is not an algorithm that is being developed but knowledge that is being encoded for machine use.


The immediate problem is that traditional applications developers do not have sufficient knowledge of the applications area to complete the project from the starting point of a functional specification. This information generally exists in a variety of forms, depending on the application area. In some cases an individual or group of individuals may uniquely possess the relevant knowledge. In other cases, the knowledge may exist in the form of published materials like manuals or textbooks. In still other cases, the knowledge does not presently exist at all, and must be created and developed along with the system itself. This is an extremely difficult circumstance. Further compounding this problem is a critical factor: Regardless of the form in which the knowledge currently exists, it is not in a form that is ready for use by a knowledge system. Someone must decide what knowledge is relevant and desirable for inclusion, acquire the knowledge, and represent it in a form suitable for a knowledge system to apply. In all but trivial applications the task of representing the knowledge requires not only coding individual “chunks” of knowledge, but also organizing and structuring these individual components.


Historically, owing to the remoteness and enigmatic quality of artificial intelligence technologies, the person doing the actual systems development and the “expert,” or source of knowledge, were not the same. The availability of tools, in place of enigmatic technologies, has had an impact on reducing this problem. Even if one can imagine the case in which the “expert” whose knowledge is to be modeled is also an “expert” with the use of artificial intelligence development tools, there still remains a sizable problem.


In case where knowledge resides with some practitioner or expert, it does not exist explicitly as a series of IF …THEN rules, ready to be encoded. Most practitioners and experts find it difficult to explain explicitly what they are doing while solving problems. They are not cognizant of the underlying rules they are applying. Their expertise has been developed from numerous experiences and involves highly developed pattern recognition skills and heuristics.


In the case where the knowledge to be included is contained in text material like manuals, regulations, procedures, and the like, the information is still not in a form ready for inclusion in an expert system. It must be remembered that one of the most often cited advantages of expert systems is that they make explicit the knowledge that is most often implicit and unavailable for review, evaluation, dissemination, and modification. The task of making knowledge both explicit and available for systems application is that of knowledge engineering. Most literature on the development and application of knowledge systems has identified the need for individuals skilled in knowledge engineering as a critical factor to widespread use of technology.


Knowledge engineering involves acquiring, representing, and coding knowledge. The representation and coding aspects of systems development have been greatly impacted by these newly available tools. The speed with which prototyping can be accomplished has also helped reduce some of the difficulty in acquiring or refining knowledge. The knowledge engineer now finds it much less costly in time and effort to represent, code, and test early approaches to systems development, providing a more efficient feedback loop. This feedback loop is critical in the development of knowledge systems. The end-user/client for the project is, by nature, going to be much more involved in the systems design process. The “programmer” often is incapable of deciding if the system is behaving properly, owing to a lack of fundamental knowledge about the application area. This is simply not as strong a factor, where the programmer is capable of evaluating the accuracy and efficiency of algorithms. When the product is actionable knowledge rather than algorithms, the ability to evaluate project progress shifts to the end-user/client. This creates the increased emphasis on the feedback loop.


My Consultancy–Asif J. Mir – Management Consultant–transforms organizations where people have the freedom to be creative, a place that brings out the best in everybody–an open, fair place where people have a sense that what they do matters. For details please visit, Line of Sight

Locking Customers in

Winners care about their clients’ businesses. They take specific steps to become more intimately involved. They share information and knowledge and pass on leads. They are always on the look out for ways of ‘adding value’ or helping customers to solve their problems.


They lock out competitors by integrating their own systems and processes with those of their customers. They may become involved in joint planning and the development of their client’s services. Relationships they forge grow into formal partnerships with joint and mutual objectives, shared rewards and savings, commitments to specific and measurable performance improvements, open book accounting and simple, quick, low-level dispute resolution procedures.


My Consultancy–Asif J. Mir – Management Consultant–transforms organizations where people have the freedom to be creative, a place that brings out the best in everybody–an open, fair place where people have a sense that what they do matters. For details please visit, Line of Sight

Plagiarism and Copyright Violation

Plagiarism and copyright violation are complicated issues, especially in modern technical writing.

Plagiarism is the practice of using someone else’s words or ideas without crediting the source. Many organizations treat authorship of internal documents, such as memos and most reports, casually; that is, if the organization asks you to update an internal procedures manual, it expects you to use any material from the existing manual, even if you cannot determine the original author.

Organizations tend to treat the authorship of published documents, such as external manuals or journal articles, more seriously. Although the authors of some kinds of published technical documents are not listed, many documents such as user’s guides do acknowledge their authors. However, what constitutes authorship can be a complicated question, because most large technical documents are produced collaboratively, with several persons contributing text, another doing the graphics, still another reviewing for technical accuracy, and finally someone reviewing for legal concerns. Problems are compounded when a document goes into revision, and parts of original text or graphics are combined with new material.

The best way to determine authorship is to discuss it openly with everyone who contributed to the document. Some persons might deserve to be listed as authors; others, only credited in an acknowledgment section. To prevent changes of plagiarism, the wisest course is to be very conservative: if there is any question about whether to cite a source, cite it.

A related problem involves copyright violation. Copyright law provides legal protection to the author of any document, whether it be published or unpublished, and whether the author be an individual or a corporation. Unfortunately, some companies will take whole sections of another company’s product information or manual, make cosmetic changes, and publish it themselves. This, of course is stealing.

But the difference between stealing and learning from your competitors can be subtle. Words are protected by copyright, but ideas aren’t. Rare is the manufacturer who doesn’t study the competitor’s users’ guides to see how a feature or task is described. Inevitably, a good idea spreads from one document to another, and then to another. If one manual contains a particularly useful kind of troubleshooting guide, pretty soon a lot of others will contain similar ones. Even though this process of imitation tends to produce a dull uniformity, it can improve the overall quality of the document. Under no circumstances, however, should you violate copyright by using another organization’s words.

My Consultancy–Asif J. Mir – Management Consultant–transforms organizations where people have the freedom to be creative, a place that brings out the best in everybody–an open, fair place where people have a sense that what they do matters. For details please contact, Line of Sight

Political Feasibility of Strategy

The guiding principles for developing the tools and techniques derive from seeking the political feasibility of strategy by focusing on process management and design as much as on content management. To gain political feasibility the wisdom and experience and therefore the ideas and views of each member of the strategy-making team are attended to. The processes introduced pay attention to the need for strategy to be negotiated product of a group process that is designed to gain a sufficient degree of consensus for strategy delivery to follow. Power, politics, procedures, psychology, social psychology, group behavior and negotiation are key background concepts that guide the process management and content management. My Consultancy–Asif J. Mir – Management Consultant–transforms organizations where people have the freedom to be creative, a place that brings out the best in everybody–an open, fair place where people have a sense that what they do matters. For details please contact Asif J. Mir.

Implementing Strategy

There are five tasks:

  1. Reallocating resources to match the budgetary and staffing requirements of the new strategy.
  2. Establishing strategy-supportive policies and procedures.
  3. Instituting best practices and mechanisms for continuous improvement.
  4. Installing support systems that enable company prsonnel to carry out their strategic roles day in and day out.
  5. Employing motivational practices and incentive compensation methods that enhance commitment to good strategy execution.

My Consultancy–Asif J. Mir – Management Consultant–transforms organizations, makes them relevant, and suggests solutions for succes. For details please contact Asif J. Mir