Research

This article introduces a novel mathematical model to quantify the Skill-Challenge Balance, essential for achieving a Flow state, through the lens of information theory. It contrasts with existing models this approach addresses the balance between an individual's perceived capabilities (prior knowledge) and task challenges (knowledge to be discovered), offering a refined method for identifying Flow states.

The model uses mutual information (I(X;Y)) and conditional missing information (H(Y|X)) to define the balance essential for flow. The balance function, governed by the Knowledge Discovery Efficiency (KEDE), quantifies the alignment between a person's capabilities and task complexity. An optimal KEDE value of 1/2 suggests a perfect balance, indicative of flow, while values deviating from this point suggest tendencies towards anxiety or boredom.

This model not only enriches our theoretical understanding of Flow but also holds practical implications for enhancing workplace productivity and well-being. It paves the way for future research and practical applications, encouraging the development of strategies and tools to help individuals and organizations better achieve and sustain flow states. Ultimately, this work contributes to a deeper appreciation of the psychological and informational dynamics at play in achieving optimal experiences in professional settings.

We show how to operationalize the Multi-Scale Law of Requisite Variety as a multi-scale knowledge-matching problem by defining a scale-dependent “knowledge gap” H(X|Y)n and its corresponding Knowledge-Discovery Efficiency (KEDE) profile. KEDE provides an operational way to quantify how efficiently a system converts prior knowledge into effective responses, both globally and across scales, making it possible to diagnose where regulation fails, where knowledge is missing, and why success at one scale cannot compensate for failure at another.

We address Real-world applications of Ashby's Law by adopting Ashby's strict black-box perspective: only external behaviour is observable. First we define the multi-staged selection process of narrowing down and selecting the appropriate response from the set of alternative responses as the Knowledge Discovery Process. We then label H(X|Y) as the knowledge to be discovered, which is the gap in internal variety that had to be compensated by selection. This quantifies how much disorder the regulator still permits and, conversely, how close the system comes to meeting Ashby's requisite-variety condition. In information-theoretic terms, perfect regulation requires H(X|Y) = 0. Then we quantify the knowledge to be discovered H(X|Y) based on the observable outcomes E. Building on this result, we generalize Knowledge-Discovery Efficiency (KEDE) - scalar metric that quantifies how efficiently a system closes the gap between the variety demanded by its environment and the variety embodied in its prior knowledge. KEDE operationalises requisite variety when internal mechanisms remain opaque, offering a diagnostic tool for evaluating whether biological, artificial, or organisational systems absorb environmental complexity at a rate sufficient for effective regulation. Finally we present applications of KEDE in diverse domains, including typing the longest English word, measuring software development, testing intelligence, basketball game, assembling furniture, and speed of light in medium.

We discuss problem for the quantification of the productivity of knowledge workers. We introduce a measure of this productivity called KEDE (Knowl-edgE Discovery Efficiency). The main application of KEDE can be for performance improvement. Then KEDE is extended to account for errors in knowledge discov-ery and for the lost time in a working day. Characteristic features of KEDE are discussed.

Within one generation, software has become one of the principal sources of wealth in the world. The development and use of software has grown faster than for any artifact in the history of the world. Probably no topic or subject in history has accelerated in its rate of practice as software has. Software development now needs to mature into a disciplined activity to overcome the difficulties that have traditionally plagued it. Software developers, engineers, and project managers need a reference that describes the evolution of software: where it has been, and where it is going. The Laws of Software Process: A New Model for the Production and Management of Software reveals a novel and compelling structure for development that redefines the very nature and purpose of software. The author explains how, in the modern "knowledge economy," software systems are not "products" in the classical sense, but is the modern medium for the conveyance of information. Literally, software is the currency of the knowledge basis of wealth in today's society. From this definition flows a new assessment of the basics of software development: the purpose of methods and processes; a comparison of programming languages; and an analysis of quality management, cost estimation, and project management and completion. The groundbreaking perspective outlined in this book serves as an expert guide for successful planning and execution of development projects.

This paper proposes a fundamental change in the way we view software development and the role of software in our society. We argue that the conventional understanding of software as a vehicle for automation is responsible for some of the most serious problems in the industry. As an alternative, we present a view of software as knowledge, and software development as knowledge creation. This shift in understanding can help to unsettle many deeply ingrained beliefs that have contributed to the software crisis; it points the way to alternative processes based on the goals of inquiry, discovery, and knowledge sharing.

Organisations are increasingly turning their attention to the creation and use of knowledge as a strategic resource. Too often however, knowledge management initiatives fail to deliver the competitive advantage expected from a strategic resource. The knowledge management literature is characterised by frameworks for knowledge management implementation which tend to prescribe best-practice methods to a large range of companies. Although useful, a key weakness of these frameworks is their inability to account for contextual differences. Consequently many organisations attempt to apply a knowledge management framework that simply doesn’t fit the organisational context resulting in little or no benefit from their efforts. A shift in focus from best practice to best fit is necessary to account for the difference in organisational contexts. Systems thinking emphasises context as an important element in understanding a system, and five concepts from systems theory are used to define the criteria for establishing a best-fit approach. A social constructionist approach to the research further affords the opportunity to identify areas of significant variation in knowledge management context and practices within knowledge-centric organisations. A multi-method research strategy, comprising cluster analysis and case study research, is proposed to develop insight into the emergence of different configurations of knowledge management capabilities within different organisational contexts. The proposed conceptual framework forms the foundation for building a typology of knowledge-centric organisations which will enable organisations to choose the most appropriate approach to knowledge management based on their specific context which varies along the dimensions of their knowledge-orientation, knowledge management intent and knowledge management enactment.

The importance of knowledge to an organization’s competitive performance is widely recognized. A knowledge-centric organization is one within which the creation and management of knowledge are at the heart of its strategic thinking, operations, and activities. Knowledge-centricity can only be achieved if knowledge, and the behaviors and systems associated with its creation and management, are deeply embedded within the organization. In fact, given the dynamism of organizations and their environments, knowledge-centricity is likely to be a holy grail that organizations seek but may never find. Similarly, knowledge-centricity will evolve as a concept, as knowledge of the processes of learning, knowledge creation, and management develops over time. This chapter, therefore, represents a snapshot of the current status of the concept and offers advice on how organizations can begin to make progress towards becoming knowledge-centric. On the basis of research, the chapter identifies the primary characteristics of a knowledge-centric organization, and the tools and techniques necessary for knowledge-centric organizational development. Termed the "knowledge journey", the framework identifies and defines five stages of a pathway to knowledge-centricity, with each stage building on the other. These stage are: 1. Knowledge-chaotic: The organization has not recognized the importance of knowledge; poor leadership and a lack of vision are apparent; 2. Knowledge-aware: The organization recognizes the value of knowledge and some systematic approaches have been taken. However, no efforts are made to use knowledge as an organizational resource; 3. Knowledge-enabled: The organization is using tools and processes to build knowledge. However, technical and cultural barriers exist; 4. Knowledge-managed: The organization has the processes in place to create and manage information and knowledge; processes are regularly reviewed and improved though knowledge typically remains only with senior leadership; 5. Knowledge-centric: The organization integrates the creation and use of knowledge into its mission and strategies; the leadership, culture, and infrastructure fully support the creation and management of knowledge.

Given assumptions about the characteristics of knowledge and the knowledge requirements of production, the firm is conceptualized as an institution for integrating knowledge. The primary contribution of the paper is in exploring the coordination mechanisms through which firms integrate the specialist knowledge of their members. In contrast to earlier literature, knowledge is viewed as residing within the individual, and the primary role of the organization is knowledge application rather than knowledge creation. The resulting theory has implications for the basis of organizational capability, the principles of organization design (in particular, the analysis of hierarchy and the distribution of decision-making authority), and the determinants of the horizontal and vertical boundaries of the firm. More generally, the knowledge-based approach sheds new light upon current organizational innovations and trends and has farreaching implications for management practice

The most important, and indeed the truly unique, contribution of management in the 20th century was the fifty-fold increase in the productivity of the manual worker in manufacturing. The most important contribution management needs to make in the 21st century is similarly to increase the productivity of knowledge work and knowledge workers. The most valuable assets of a 20th-century company was its production equipment. The most valuable asset of a 21st-century institution (whether business or nonbusiness) will be its knowledge workers and their productivity.

We must show how a solution is produced by the interactions of people each of whom possesses only partial knowledge. To assume all the knowledge to be given to a single mind in the same manner in which we assume it to be given to us as the explaining economists is to assume the problem away and to disregard everything that is important and significant in the real world.