Abstract
Currently, and with almost light speed, new advances in both human-centered and technology- driven efforts have led to new methods in obtaining and using organizational knowledge. For the purposes of this Chapter, Organizational Knowledge will be seen as the different knowledge and skill sets that the employees of a large company or organization have, and how these can be used and shared to make the organization more effective. The Chapter's emphasis will be on how to elicit those knowledges and skill sets, then how to both use and evaluate their usage. The author's goal is to explicate a new model for eliciting and using Organizational Knowledge. This new paradigm uses many components in a blended Delphi. Advantages of using these components are that they are all content-area neutral and, in a real sense, generic in application. Collectively, the resultant paradigm for developing and using organizational knowledge points the way to try the new procedures and validate (or not) them and, to future research on an organizational level.
TopBackground
The Delphi method was developed by the now USAF’s Project RAND during the 1950-1960s. and derived its name from a contraction of the term research and development (Research ANd Development). The Delpi technique has long been used for eliciting knowledge from subject matter experts (SMEs) and has become a common methodology/methologies for eliciting analyses, expert opinions and evaluations on a variety of topics. Delphi techniques, a subset of CE/KE, have a goal at arriving at something closer to expert consensus. The Delphi method has been widely adapted to work problems and is still in use today. It has changed over the years from SME anonymity to allowing face-to-face groups (estimate-talk-estimate; ETE) of SMEs. Meister (1985) noted “The (Delphi) methodology is by no means fixed…[it] is still evolving and being researched.” This is as true now as it was when Meister stated it. In point of fact, with the leaps in communication methods and related computer technology, this is even more true today as Delphi techniques have recently begun to look at and attempt to take full advantage of these advances.
One also finds that an expansion in the the field called cognitive/knowledge engineering (CE/KE) has occured and is still in progress. KE was defined in 1983 by Edward Feigenbaum and Pamela McCorduck as follows: “KE is an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise.” For a more complete overview and discussion on KE, differing views and uses, the reader is referred to Studer, Benjamins and Fensel (1998).
There is a new emphasis on a related discipline: knowledge management (KM). The field of KE has recently expanded to encompass KM as a subset. KM has been defined as “...the practice of selectively applying knowledge from previous experiences….with the express purpose of improving the organization's effectiveness.” (Jannex, 2014). For works on KM, Amazon's web site has 50 or more, including the ubiquitious The Complete Idiot's Guide to Knowledge Management (Rumizen, 2001).
Pareto Analysis has a long history of being used processes to focus on selecting the best course of action for dealing with issues/problems. Pareto analysis is a formal technique useful where many courses of action are possible. In essence, an estimate or criticality rating is done that allows for selection of effective action (s) that deliver a total benefit to an organization or other entity. Pareto analysis is a creative way of looking at causes/”cures” of organizational problems as it helps stimulate thinking and organize thoughts
The newest sub-set/direction of knowledge elicitation and management is knowledge management success, KMS. KMS is “...a multidimensional concept defined by capturing the right knowledge, getting the right knowledge to the right user and using this knowledge to improve organizational and/or individual performance...” (Jennex, 2012 citing himself, Smolinik and Croasdell, 2009). Thus, KMS evaluates the success of the processes and knowledge generated as the organization develops and uses knowledge about itself. KMS today places emphasis on the success of using a KM process in organization-wide endeavors.
Key Terms in this Chapter
Group dynamics: The interactions that influence the attitudes and behavior of people when they are grouped with others through either choice or accidental circumstances. Social psychologist Kurt Lewin coined the term group dynamics to describe the positive and negative forces within groups of people.
Real-Time Delphi (RTD): An advanced form of the Delphi method. The advanced method “is a consultative process that uses computer technology” to increase efficiency of the Delphi process .
Consensus: Consensus is the state achieved when, if any group participant is asked, alone and outside of the group's hearing, about the consensus/results achieved by the group: their response is that they can support the consensus arrived at, no reservations.
Flight Simulator: A flight simulator (FS) is a system designed to “imitate” the functions of another system (an airplane) in a real operational environment; to be a realistic substitute that responds realistically to flight crew inputs. A FS is a training device whose primary functions are 1.To present information like that which the real system would present, for the purpose of training and, 2. To provide a practice environment that facilitates and enhances the skills and knowledge of the pilot, and thus provides learning which enhances performance in the real system, the airplane.There are several types of flight simulators.
Ontology: A term that comes from philosophy. In KE/KM, an ontology is a formal naming and definition of the types, properties, and interrelationships of the entities that really or fundamentally exist for a particular domain of discourse. It is thus a practical application of philosophical ontology, with a taxonomy A KE/KM ontology compartmentalizes the variables needed for some set of computations and establishes the relationships between them; thus, an ontology is used to limit complexity and to organize and structure information.
United States Federal Aviation Administration (FAA) Regulations (FAR): All are in the Combined Federal Regulations (CFR), Title 14, Aeronautics and Space; each a descriptive title and number; they are legally binding.
United States National Transportation Safety Board (NTSB): An independent Federal agency charged by Congress with investigating every civil aviation accident the United States and significant accidents in other modes of transportation – railroad, highway, marine and pipeline. The NTSB determines the probable cause of the accidents and issues safety recommendations aimed at preventing future accidents.
United States Federal Aviation Administration (FAA): Is the national aviation authority of the United States. As an agency of the United States Department of Transportation, it has authority to regulate and oversee all aspects of American civil aviation.
Facilitator: A person that helps to bring about an outcome (as learning, productivity, or communication) by providing indirect or unobtrusive assistance, guidance, or supervision. At times, the facilitator can provide initial instruction and, at times again, be more proactive as to direction.
United States Federal Aviation Administration (FAA) Advisory Circulars (AC): The FAA normally published these which are designed to provide assistance and guidelines in complying with FARs; they serve as a “how to” template. The AC’s are titled and numbered and are not legally binding as are the FAR's.
Subject Matter Expert (SME): An individual who exhibits the highest level of expertise in performing a specialized job, task, or skill within the organization.