Management of Technology and Innovation: Competing Through Technological Excellence

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P.N. Rastogi

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    Dedication

    To

    Loving God—SSS

    List of Figures

    • 2.1 X, The Maker of Parts 10
    • 2.2 Y, The Mover of Parts 11
    • 2.3 Z, The Timer of X and Y 11
    • 3.1 Product-Market Matrix: Four Positions 25
    • 4.1 A Two-tier Circle/Team 64
    • 4.2 A Three-tier Circle/Group 65
    • 4.3 Classification of Productivity Teams 66
    • 6.1 Model of a CIM System 98
    • 6.2 The AI Factory 102
    • 6.3 High-speed Peer-to-peer LAN of an AI Smart Plant 103
    • 10.1 The Dynamics of the Technovation Process 154
    • 12.1 Self-reinforcing Focus and Lead Cycle 188
    • 17.1 Lessons from Japan in Organizing for Productivity 272
    • 17.2 Dynamic Structure of the Japanese Innovation System 275
    • 17.3 Cyclic Phases of Ideation in the Japanese Innovation Style 283
    • 18.1 Interactive and Synergistic Spectrum of Technological Excellence 292
    • 19.1 Core Value-orientation of Social Capital 309
    • 19.2 The Self-reinforcing KM Nexus of Wealth Creation 313
    • 19.3 Developing a Shared Cognitive Map 321
    • 19.4 The Pattern of Organizational Transformation 323

    Preface to the Second Edition

    The second edition includes two additional chapters and another appendix. The new chapters highlight the theme of wealth creation through a conceptual framework of technological excellence, human capital, social capital, and knowledge management. The concept of a knowledge management nexus (KMN) provides a powerful insight in this context. The additional appendix outlines some useful methods and approaches towards exploring technology management issues. It is the author's earnest hope that esteemed readers may find the additional content to be ‘different’, thought-provoking, and edifying.

    P.N.Rastogi

    Preface to the First Edition

    Technology is the engine that drives the economies of nations. Technological capabilities constitute the cutting edge of business strategies of enterprises that excel in the intensely competitive global marketplace. Firms which have mastered the management of technology are rewriting the rules of global industrial competition.

    Technology absorption, incremental innovation, research and development (R&D), technovation and technology fusion dominate the contemporary world industry. They are simultaneously the cause and consequences of the increasingly turbulent and volatile environment of trade and technology across the world. An industrial firm under these conditions cannot afford to stand technologically still. To do so would imply stagnation and failure. Continuous development of technology and technovation underlie the competitive success of excellent companies the world over.

    This volume seeks to explicate the nature, significance, dimensions, requirements, concepts, issues, themes, policies, structure and rationale of the management of technology and technovation. It addresses basic questions concerning the ‘what’, ‘why’, ‘how’, and ‘whence’ of managing technology effectively. It is an outgrowth of the writer's earlier volume, Global Competitiveness, with which it shares a few themes in common. It consists of an introduction, five parts, and an appendix. The introductory chapter delineates the salient features, factors, and trends of present-day world industry and global industrial competition. It sets the point of departure for the rest of the volume.

    Part One elucidates the basic concepts and themes pertaining to the nature and dimensions of technology and its management. Chapter 2 delineates the systemic structure of technology in terms of the concepts of axes and atlas. These concepts provide a holistic understanding of technology as a system. Chapter 3 highlights the nature and significance of the strategic management of technology and the requirement or otherwise of a separate corporate R&D unit. The close interrelation between technology management and the competitive strategy of a company is brought out in this context.

    Part Two focuses on manufacturing technology. It elucidates the methods of managing productivity, incremental innovation, and technology absorption in Chapters 4 and 5. Chapter 6 delineates the structure of world class manufacturing as an integrated framework comprising total quality management (TQM), justin-time system of production (JIT), and computer-integrated manufacturing (CIM). Each of the three subsystems, that is, TQM, JIT, and CIM, is elucidated in terms of its nature and rationale. Chapter 7 examines some crucial issues related to the adoption and implementation of computer-integrated manufacturing. They need to be considered explicitly and carefully if a firm is to avoid costly errors in moving over to flexible technology. Chapter 8 focuses on the evaluation requirements of projects involving technological change. Conventional evaluative frameworks like management cost accounting, net present value (NPV), or discounted cash flow (DCF) analyses are seen to be inappropriate for a strategic evaluation of such projects. Alternative approaches to investment decisions in technology on the basis of strategic considerations are presented.

    Part Three is devoted to forms and modes of technology development. Chapter 9 elucidates the nature and management of the product development cycle in the current milieu of shorter product changeover cycles. The latter, in turn, involve the integration of design and manufacturing through the methodology of concurrent engineering. Chapter 10 elucidates the nature, requirements, and issues associated with the management of technological innovation. Chapter 11 outlines the nature and dimensions of a new paradigm of R&D based on the refinement and fusion of existing technologies to develop new ‘hybrid’ technologies. Both Chapters 10 and 11 elaborate the generic theme of technovation in an expanded sense. Technovation, however, is by its very nature a disorderly and highly uncertain process. The Appendix presents some approaches towards coping with uncertainty in technovation or in the development of new products. Chapter 12, the last one in this part, explicates the concepts of core technological competencies/capabilities. Their importance lies in imparting a definitive focus to a company's competitive strategy on the one hand and providing a clarity of thrust and direction to its technology management on the other. It also highlights the importance of the commercialization of technology.

    The focus of Part Four is on the support system of organization structure, policies, and requirements for technology management. Chapter 13 outlines the fundamentals of organization structure and its rationale in this context. Chapter 14 elucidates the nature, importance, and requirements for building an organizational culture of productivity, innovation, and excellence.

    Chapter 15 elucidates the important theme of designing an industrial enterprise as a laboratory for learning. Only such an organization, continually engaged in accumulating, enriching, and utilizing knowledge towards developing its capabilities and performance, can hope to master the powerful forces of change. The chapters included in this part together highlight the dimensions and requirements of building and strengthening organizational capabilities.

    Part Five deals with the indispensable requirement of cooperation between government and industry for facilitating the efforts of firms to gain and maintain a position of technological excellence in world industry. Chapter 16 elucidates the role, rationale, and requisites of a national industrial/technology policy. The technology policies of USA and Japan are outlined for comparative evaluation. The parameters for a forward-looking and synergistic national technology policy are delineated. Chapter 17 develops this theme further. It examines the overall structure of the Japanese innovation system to understand its nature, logic, and rationale. The relevance and importance of the Japanese system in the context of technology management stems from its unexcelled capability to not only cope with the challenges of continuous change but also master them through its prowess in productivity and technovation. Technological creativity and strength underlie the emergence of this small resource-poor country as the world's foremost industrial and economic superpower. The Japanese system of productivity and technovation provides valuable lessons for managing technological excellence on the basis of teamwork on a national scale.

    The preparation of this volume was made possible by a financial grant from the Quality Improvement Programme of the Ministry of Human Resources at the Indian Institute of Technology, Kanpur. A work of this type cannot be completed without the help and support of one's associates and students. They are, however, too numerous to be acknowledged here individually. The writer is grateful to them all.

    P.N.Rastogi
  • Appendices

    Appendix I: Methods for Coping with Uncertainty in Technovation and New Product Development

    Technovation is a messy, disorderly, and highly uncertain process. Operating as it does at the frontiers of extant knowledge, it usually tends to be highly unstructured, ill-defined, and poorly understood. Such a situation renders the task of identifying and evolving a promising strategy of R&D exceedingly difficult. In the absence of a clear basis for identifying a problem's nature and structure, a coherent and logical strategy for its investigation, analysis, exploration of alternatives, and solution cannot be worked out properly.

    On the account of the uncertainty surrounding a technovation problem, techniques for the generation of creative ideas are often employed to identify new insights and concepts to cope with the problem. These techniques, though useful, do not provide either a definition of the problem or an elucidation of its structure and scope. Techniques like brainstorming, synectics, or attribute listing may at best only suggest some new ideas and insights. They do not address the lack of definition and approach characterizing a technovation problem. The fuzziness, ambiguity, ill-defined nature, and lack of clarity and direction surrounding a technovation endeavour require ways and means of structuring the problem, conceptually and analytically, so that it may be approached in an intelligent manner. A structuring approach would not by itself reduce the problem's uncertainty, but it may serve to clarify and even elucidate its nature and dimensions, thereby rendering it more manageable.

    Heuristic Structuring Methods

    This appendix outlines some methods for a tentative conceptualization and structuring of a technovation problem. These methods may jointly and severally serve to clarify the various facets of a given problem, and the issues involved therein, in a preliminary manner. They may help in identifying the nature and requirements of a research design and investigation. They may also be seen to be useful in elucidating the nature, contexts, and sources of the problem's uncertainty. These methods are based on concepts and paradigms drawn from artificial intelligence, cognitive science, technological forecasting, and management science. They may be listed as follows:

    • Morphological matrix analysis.
    • Relevance tree analysis.
    • Problem state-space method.
    • Knowledge classification matrix.
    • Network of information.
    • Sequence specification procedure.
    Morphological Matrix Analysis

    This method directs efforts towards seeking potential means of accomplishing specified technological capabilities. Its procedure may be briefly described as below:

    • A problem is disaggregated into distinct parts or parameters. The latter are treated individually; they have no hierarchic relationships.
    • For each parameter, several possible alternative solutions are identified and listed. The listing should be as complete as possible.
    • Overall solutions to the given problem are then obtained by taking one of the possible alternative solutions to each part and viewing them together. Solutions to each part must be compatible and feasible, that is, match with the corresponding solutions to other parts, in their assemblage or combination. Such an assemblage represents a potential solution frame.
    • The best overall solution is then selected from the possible combinations of mutually consistent solutions to each of all the parts of the problem, on the basis of selected criteria.

    This procedure thus involves a systematic examination of all possible and realizable combinations of alternative solutions for the separate parts of the problem.

    Relevance Tree Analysis

    A relevance tree arranges in a hierarchical order the objectives, sub-objectives, methods, techniques, tasks, projects, and subtasks, and so on, pertaining to a problem domain in sufficiently disaggregated detail. It seeks to ensure that all possible ways of achieving the objectives have been found and placed at appropriate levels in an inverted tree structure. The relevance of individual subtasks, tasks, projects, techniques, and sub-objectives, and so on, to the overall objectives is then evaluated.

    The broad pattern of analysis under this method may be represented as in Figure AI-1. A path or route towards realizing a given goal or specified objectives consists of goals, sub-goals, sub–sub-goals, and so on, at progressively lower levels. The goals at a higher level can be addressed only when each of the subgoals at its lower levels has been met.

    FIGURE AI-1 Pattern of Analysis in Relevance Tree
    Problem State–Space Method

    In this method the goal is represented in the form of a desired situation consisting of an object or list of objects. Problem-solving consists of attempting to change the current object (situation) into the desired one. Three main types of operational goals are defined as follows:

    • Transform an object A into an object B.
    • Reduce a difference between object A and object B by modifying object A.
    • Apply an operator Q to object A for modifying it.

    Associated with the operational goal types are methods or procedures for achieving the goals. These methods can be understood as problem-reduction operators.

    The analysis here assumes that the differences between a current object and a desired object can be defined and classified into types. The operators can also be classified according to the kinds of differences they might reduce. The problem-solving effort focuses on selecting a relevant operator to be applied to the current object. The essence of the method is to identify a sequence of operators (and operations) along a path that appears to be promising. Backup is tried if a current path becomes unpromising, that is, if the elimination of a difference introduces a new one that is more difficult to eliminate.

    A goal state or object may also be viewed as the end node in a state-space graph. A solution to a state-space problem is then a finite sequence of applications of operators that changes an initial state into a goal state. A state-space problem is then the triple (O, S, G), where the complete specification of a state-space problem has the following three components:

    • a set [O] of operators or operator schemata;
    • a set [S] of one or more initial states; and
    • a set [G] of goal states.

    Several operators can be applied at any given point, or the same operator can be applied in different ways. A problem space is a concept area that is defined by all the possible states that could be generated by the elements and operators of a particular domain. It is also visualized as a graph in which the nodes represent all possible states of partial or complete solution of a problem, and arcs represent operators that transform one state to another. Finding a solution to the problem under consideration is represented by the isomorphic problem of finding a path from the node representing an initial state to a node representing a goal state.

    Knowledge Classification Matrix

    This approach first attempts to classify all the relevant available or possible knowledge about a technovation problem into two broad categories:

    • State-of-the-art
    • Zone of uncertainty

    Each of these categories is further classified into two sub-categories. State-of-the-art knowledge, for example, is divided into (a) the known, and (b) the knowable. The known category refers to the knowledge that is available for use by the technovator. The knowable category refers to the knowledge that is not available to the technovator at the moment, but which can be obtained from professional sources, or from routine investigation and testing.

    Knowledge perceived as relevant but coming in the zone of uncertainty is also similarly divided into two subcategories: (c) the partially or inadequately known, and (d) the unknown. Subcategory (e) refers to the areas of relevant knowledge that are currently under investigation or development at various laboratories or R&D centres in the world. The reported research findings are, however, piecemeal, sketchy and essentially incomplete. Subcategory (f) on the other hand, refers to that perceived body of knowledge that is deemed to be necessary for problem-solving but is currently assessed as unknown or unavailable.

    The schema of this method may be depicted as in Figure AI-2. The problem-solving effort in this method is then directed towards identifying, designing and using methods, techniques and experimental approaches, that is, new research routes, to progressively reduce the problem's zone of uncertainty.

    FIGURE AI-2 Knowledge Classification Matrix
    Network of Information

    In this method, the techno-scientific data and information are searched for, systematized and organized in terms of the following four categories:

    • Recent research results.
    • Techno-scientific capabilities possible through (a).
    • Technical components possible on the basis of (b).
    • Resultant systems possible through configuring (c).

    Recent research results (r1, r2, ….rk) refer to published or available R&D findings in the technovator's domain of interest. They are combined to depict potential techno-scientific capabilities becoming available, that is, those capabilities which can be generated or created on the basis of recent research findings. Techno-scientific capabilities, potential as well as actual (s1, s2, …sj), can then be combined to visualize possible technical components (t1, t2, ….tm). Technical components, both possible and extant, can then be joined or configured to produce possible resultant end-systems (ES1, ES2, ….ESn). The nature of this method may be represented as in Figure AI-3.

    FIGURE AI-3 Network Analysis Technique

    In terms of its information categories and their underlying assumptions, this method can be used to provide two types of structuring assistance for technovation efforts:

    • By exploring the possible techno-scientific capabilities and the potentially realizable end-systems that might result from extensions and combinations of recent research results, the route towards realizing possible relevant technologies may be indicated. This type of structuring assistance is exploratory.
    • Proceeding in a reverse direction, that is, by determining what research results are required to achieve a desired capability and end-system, a prescriptive route of R&D may be indicated. The method then serves to specify what needs to be accomplished in terms of R&D results, to facilitate the process of technovation.
    Sequence Specification Procedure

    This procedure focuses on identifying and organizing a set of steps towards reaching a specified technological objective in an ordered sequence. The steps may consist of the following:

    • Necessary prerequisites in terms of structural elements, processes, or functions.
    • Breakthroughs or innovative developments needed for meeting the above prerequisites.
    • The alternatives that are available or possible in the context of needed and innovative developments.

    The technological developments necessary, that is, the prerequisites and innovative breakthroughs to achieve the specified objective, need to be listed and described in detail. The details must also include the subsystems and hardware, the equipment and devices, the software and instruments, the materials and components. Each subsystem should be envisioned in sufficient detail to identify the actions that need to be taken immediately and in the near future. The nature of this method may be indicated as in Figure AI-4.

    FIGURE AI-4 Sequence Specification Procedure

    The sequence specification procedure thus serves to map and indicate the promising routes of research in an ordered but flexible manner.

    Conclusion

    The foregoing methods differ in their thrust and approach. Together, however, they provide complementary and convergent ways of coping with the fuzziness and uncertainty of the technovation process. Technovation is basically an idea and an act of creation. What these methods do is to provide platforms for the disciplined exercise of creativity and imagination. They amplify the scope for gaining creative insights into the nature of a problem by providing plural perspectives towards its structuring and conceptualization. As such, they may have a useful role to play in facilitating the process of technological innovation.

    Note

    1. The primary focus of discussion here is on coping with uncertainty in technological innovation. The methods outlined here are, however, also applicable in dealing with technical uncertainty associated with the development of new products. In the latter case, the magnitude of uncertainty is apt to be much less than in the technovation effort. In the development of radically new products, the distinction between technovation and product development dissolves.

    Appendix II: Some Useful Methods and Approaches

    Management of technology and technovation are beset with numerous uncertainties, existing and unforeseen difficulties, and a highly dynamic context. There is no set, fixed, or algorithmic methods and techniques to deal with them effectively. On the basis of experience, heuristic practices, and creative thinking, new methods and approaches to address complex managerial issues, however, continue to be evolved. A few of them are outlined briefly in what follows.

    Identifying Priorities of Technology Initiatives

    An enterprise at any given point of time may be considering a number of significant technological initiatives. It cannot implement all or most of them simultaneously owing to various resource constraints. The process of establishing their priorities may be problematic owing to differing perceptions and views of the stakeholders involved. A way to address this problem is to seek their individual informed judgments concerning two core issues:

    • How important is a given technological initiative for the organization's viability?
    • What is the status of the organization's capabilities and resources to implement the initiative?

    For the sake of clarity and simplicity, the respondents are enjoined to express their judgments as a numerical figure between 0 and 100. The numbers are then summed up and averaged to arrive at collective figures for the issues (1) and (2). Dividing (1) by (2), then yields a number deemed to represent the relative priority of any given technology initiative. This procedure may be hypothetically illustrated as in the following table.

    This procedure is by no means flawless. It, however, enables decision makers to organize their thinking and carry it forward.

    Evaluation and Selection of Technology Initiatives

    Evaluation and selection of technology initiatives may be attempted along two major dimensions: viability and fit. Viability denotes the perceived potential pay off from an initiative. Fit denotes an initiative's compatibility and consistency with the organization's existing processes, capabilities and culture. A procedure to evaluate and select technology initiatives along these two dimensions has been outlined by Tjan (2001).

    Viability is defined in terms of four metrics: (a) market value potential, (b) time to positive cash flow, (c) personnel requirement, and (d) funding requirement. Each metric is assessed on a scale of 0 to 100. Assessments for all the four metrics are summed up. Their arithmetic average denotes the viability of an initiative. Fit is conceptualized along five qualitative metrics: (a) alignment with core capabilities, (b) alignment with other company initiatives, (c) fit with organizational structure, (d) fit with company's culture and values, and (e) ease of technical implementation. These metrics are assessed as H (high), M (medium), and L (low). The overall fit is assessed in terms of three or more metrics assessed as H, M, or L.

    Viability and fit are then represented as Y and X axes respectively of a graph. The scores of each initiative are depicted on this graph is one of the four segments as in Figure AII-1:

    FIGURE AII-1 Evaluation and Selection Map for Technology Initiatives

    The above figure shows that only those initiatives that score high on both dimensions (Segment II), qualify for investment. Those high on viability, but low on fit (Segment I), should be spun out of the organization as a separate entity. Those initiatives which are high on fit, but low on viability (Segment IV), should be so redesigned or reframed as to improve their viability; while those low along both dimensions (Segment III) should be discarded.

    An Electronic Market for Radical Ideas

    An electronic market for ideas is focused on making it easy, interesting and rewarding for employees to offer new ideas, solve problems, and improve their company's products and services. Any employee can post or ‘toss’ his/her creative idea to an online market for radical ideas. An ‘innovation editor’ may group similar ideas together, and post them on the company's intranet. This, in turn, enables real time online discussions for ideas that attract attention and thoughtful inputs. Participants post their comments and reasoning in favour/against ideas and projects including suggestions and modifications. Individuals across the company may also highlight their interest in working on particular ideas/projects. The management monitors this process and makes necessary resources available for pursuing highly promising ideas. Ideas/projects eliciting the largest number of participants win management funding for further exploration, appraisals, and learning. A company needs to build an efficient electronic market for ideas, talents and capital in order to institutionalize and accelerate pay-off from opportunities based on nonlinear innovation.

    Another variation of the above approach treats ideas as ‘stocks’ to be traded with winning ideas commanding highest share prices. This procedure works as follows:

    • A website is set up where engineers, technologists, managers, researchers, and others put forth innovative ideas which are treated as stocks.
    • ‘Players’ enter their ideas with Rs 50,000 (or any other amount) in play money, and buy stock in their favourite ideas.
    • Trading proceeds with prices of stocks moving up or down based on the strengths of players' views and evaluation of ideas.
    • After a specified period, the stocks (or ideas) with highest share prices are declared as winners.
    Creating an Ideas Bank

    Companies may create an inventory of promising ideas concerning technology and product development, reconfiguration of capabilities and skills, new sources of product/service differentiation, new competencies, radical redesign of processes, dynamic options for future ventures, and so on. These ideas may be expanded, combined, pruned, refined, or replenished from time to time in an ongoing manner.

    Some firms like Honda, Toyota, Canon, and Schlumberger among others also maintain a database of pretested technological ideas. This helps them speed up their product development projects on the one hand, and solve unforeseen technical or customer problems on the other. An ideas bank may also generate opportunities in terms of copying or extending a known idea into new geographic locations, or taking up an idea from one industry and applying it to another. The concept of JIT system, for example, was triggered by the observation of shelf replenishment of food items in supermarkets. The concept of hub-and-spoke system for package delivery by air was similarly sparked off by observing the procedure of clearance of cheques by banks. The idea of branding in a similar manner has been extended to unbranded fields like computer chips, pens, washing powder, flour, and salt.

    An ideas bank calls for a new type of role of knowledge brokers. The latter are charged with seeking ideas from a wide variety of internal and external sources, and bringing together ideas from disparate contexts. This role and approach engenders a knowledge-brokering cycle. The cycle consists of four highly interrelated work practices: (a) capturing good ideas, (b) keeping ideas alive, (c) imagining new uses for old ideas, and (d) testing promising concepts. Old ideas after suitable refinements may sometimes provide creative solutions to new problems. Testing promising ideas shows whether a possible opportunity has significant technological and/or commercial potential.

    Identification of New Areas of Technological Opportunities and Innovation

    Identifying new areas of technological opportunities and innovation is a perennial issue in the management of technology. An interesting and relatively sample approach to do so may be visualized in the form of three intersecting circles as in Figure AII-2:

    FIGURE AII-2 Identifying the Space of New Possibilities

    Circle I is concerned with delineating the major social, economic, ecological, and technological trends, developments, events, and situations in a firm's global and national business environments. Circle II is concerned with assessing the nature and strength of the firm's knowledge spectrum, human capital, material, and financial resources. Circle III is focused on the firm's informed understanding of what it can do meaningfully to address the people's and community's needs and constraints arising from an ever-changing environment. Areas of opportunity and innovation at the intersection of three circles would differ according to firm's lines of business. Monsanto, an agro-chemical company, for example, identified a revolutionary growth opportunity in the development of pest and drought resistant genetically modified seeds of corn, cotton, and soybean. Auto-makers like Toyota are focusing on the development of hydrogen-powered cars owing to rising petroleum prices, and concerns over growing pollution of air. Similarly, owing to scarcity of clean drinking water and pollution of water resources, many firms are entering the new business of water purification systems. Expanding development and use of nuclear energy may similarly be seen in the context of growing energy crisis engendered by ever-rising prices and demand for petroleum.

    Establishing a Nodal Centre for Radical Innovation

    A nodal centre for radical innovation is a structural device to organize competencies for idea generation, recognition of opportunities, and their evaluation. A large company may need a network of such nodal centres. A radical innovation nodal centre is meant to link hunters, gatherers, and creators of radical innovation ideas with opportunity recognizers and evaluators. The role and functions of such a centre may be visualized as follows:

    • Aligning a firm's strategic thrust and direction with its management of radical innovation.
    • Implementing creativity techniques and supportive processes to foster generation of innovative ideas, approaches, initiatives, and ventures.
    • Serving as a homebase for radical innovation proposals, projects, and as a receiver of breakthrough ideas, concepts, and developments from internal and external sources.
    • Helping potential inventors, innovators, and entrepreneurs articulate opportunities envisioned by them.
    • Undertaking initial evaluation and organizing further more detailed evaluation of promising proposals.
    • Serving as a repository of promising but unripe ideas and concepts.

    The role of the manager of such a nodal centre is both crucial and highly challenging. He/she must have access to internal networks of scientists, engineers, technologists, sales personnel, and business unit managers. Such an access is vital for his/her being regularly posted with relevant news and developments. The manager serves as a central information node, and as a link between emerging technologies and existing and potential markets. The manager may also publicly display information concerning a company's ongoing projects, the markets in which the company competes, and the competitive challenges faced by the company.

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    About the Author

    P.N. Rastogi was professor at IIM Lucknow and IIT Kanpur. He has been a post-doctoral Fellow at Massachusetts Institute of Technology (MIT); Nuffield Fellow at the London School of Economics; National Fellow at the Centre for Policy Research and Senior Fellow of the Indian Council of Social Science Research. He is well-known for his work in the field of social and management cybernetics, computer simulation of systems, dynamics of conflict, rural development, societal systems, organizational design and development, management of productivity and technovation, technology policy, and policy analysis and problem-solving methodology for complex real-world problems.

    He has developed numerous state-of-the-art course modules on management themes for both managers and engineers. He has authored Social and Management Cybernetics (1979); Intelligent Management Systems (1987); Productivity, Innovation, Management and Development (1988); Quality Circles (1990); Managing New Technology (1991); World Class Manufacturing (1992); Total Quality Management: Theory and Practise (1993); Policy Analysis for Complex and Unstructured Problems (1992); Managing Constant Change (2005) among others.


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