Overproduction


Overproduction is regarded as the most serious waste as it discourages a smooth flow of goods or services and is likely to  inhibit  quality and productivity. Such overproduction also tends to lead to excessive lead and storage times. As a result defects may not be detected early, products may deteriorate and artificial pressures on work rate may be generated. In addition, overproduction leads to excessive work-in-progress stocks which result in the  physical dislocation of operations with consequent poorer communication. This state of affairs is often encouraged by bonus systems that encourage the push of unwanted goods. The pull or Kanban system was employed by Toyota as a way of overcoming this problem.

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 www.asifjmir.com, and my Lectures.

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Psychological Pricing


Psychological pricing encourages purchases based on emotional rather than rational responses to the price. The assumption behind symbolic/prestige pricing is that high prices connote high quality. Thus the price of certain fragrances are set artificially high to give the impression of superior quality.

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 www.asifjmir.com, and my Lectures.

Pure Competition


The term competition is used ambiguously not only in ordinary conversation but in economic literature as well. Its common meaning is rivalry, but in economics when used along with the word pure, it carries a different meaning. Following are necessary conditions for pure competition:

  1. Homogeneity of the product: For competition to exist in a market all sellers of the product being exchanged sell homogeneous units of the product, or at least the buyers of that product believe that this is so.
  2. Smallness of each buyer or seller relative to the market: Each buyer and each seller of the product under consideration is too small in relation to the entire market for the product to influence significantly the price of the product that is being bought or sold.
  3. Absence of artificial restraints: There are no artificial restrictions on the demands for, the supplies of, and the prices of whatever is being exchanged. No government price fixing nor any institutional fixing or administering of price by producers’ associations, labor unions, or other private agencies. There is no supply restriction enforced by the government or by organized producer groups. Control of demand through governmental rationing is nonexistent.
  4. Mobility: There is mobility of goods and services of resources in the economy. New firms are free to enter any desired industry, and resources are free to move among alternative uses to those where they desire employment. Sellers are able to dispose of their goods and services where the price is highest. Resources are able to secure employment in their highest paid uses.

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 www.asifjmir.com, and my Lectures.

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 www.asifjmir.com, Line of Sight

Knowledge-oriented computing systems


Popular management literature focuses on the application of artificial intelligence technology to the solution of management problems. Most discussions have addressed either the technology of various programming techniques or success stories of large-scale corporate profitmaking through their application.

Several interacting factors contribute to corporate interest in this technology. First, what were once remote, artificial intelligence programming techniques have been significantly redesigned and presented to the business computing market in the form of applications development tools. Advances in computing hardware have provided a suitable foundation for the delivery of these tools on new generations of mainstream business computers. These hardware and software technologies promise the kinds of power and ease of use that have been so successful in other applications development environments like spreadsheet modeling and data base management systems. The potential of such tools to open broad new territories to computing applications is very exciting and has captured management’s attention.

Second, there’s a developing perception of both information and knowledge as corporate assets. New computing technologies promise to make knowledge that has been implicit in the behavior of decision makers explicit in machine-usable form. By codifying knowledge, managers make it a manageable asset, continuously available to their organization. The potential integration of machine-usable knowledge with machine-readable information promises to carry the information age into the era of knowledge management.

Finally, the role of information technology is being redefined as a competitive weapon. This is in sharp contrast to internal applications of technology to gain increased efficiencies. As business planning looks to technology to help differentiate product offerings, new technologies like expert systems take on added significance. An interesting series of transitions has taken place in the perception of the role of computing as it has moved from data processing to information systems to management information systems and to strategic information systems.

The cumulative effect of these forces has created an atmosphere responsive to the promise of knowledge-oriented computing systems. The promise appears to be quite real, and the challenge, of course, is to exploit it to advantage.

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.