Understanding And Implementing Quality 1st Edition Jiju Anthony
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- 6. Understanding, Managing and Implementing Quality This book considers strategic aspects of Quality Management and self- assessment frameworks, and provides an in-depth and systematic examination of a number of the main quality improvement tools and techniques. Incorporating a critical orientation, the text reviews the implementation of a variety of Quality Management programmes across a range of organizational contexts, including manufacturing, higher education, health care, policing and retailing. With case studies illustrating good practice in all contexts, including manufacturing and service organizations, critiques and further reading, Under- standing, Managing and Implementing Quality is a highly useful resource for students, researchers and those studying for professional qualifications. Jiju Antony is a Senior Teaching Fellow at the International Manufacturing Centre of the University of Warwick. David Preece is Professor of Technology Management and Organization Studies and Head of the Human Resource Management Corporate Strategy Group at the Business School of the University of Teesside.
- 8. Understanding, Managing and Implementing Quality Frameworks, techniques and cases Edited by Jiju Antony and David Preece London and New York
- 9. First published 2002 by Routledge 11 New Fetter Lane, London EC4P 4EE Simultaneously published in the USA and Canada by Routledge 29 West 35th Street, New York NY 10001 Routledge is an imprint of the Taylor & Francis Group © 2002 Jiju Antony and David Preece, selection and editorial matter; individual chapters, the contributors. All rights reserved. No part of this book may be reprinted or reproduced or utilized in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging in Publication Data A catalog record for this book has been requested ISBN 0-415-22271-0 (hbk) ISBN 0-415-22272-9 (pbk) This edition published in the Taylor & Francis e-Library, 2002. ISBN 0-203-46408-7 Master e-book ISBN ISBN 0-203-77232-6 (Glassbook Format)
- 10. This book is dedicated to: Frenie and Evelyn and Maureen, Laura and Jamie
- 12. Contents List of figures xii List of tables xiv List of contributors xv Acknowledgements xvi Glossary xvii Introduction xviii PART I Developing a strategic orientation for Quality Management 1 1 Promoting a strategic approach to TQM using a case-based intelligent system 3 ANDREAS J. FRANGOU Introduction 3 Linking TQM and performance: a strategic perspective 4 The use of intelligent systems to support TQM initiatives 9 Development of the Enterprise Strategic Advisory System 10 ESAS: promoting strategic quality through case-based strategies 13 System evaluation 20 Analysis of the evaluation results 21 Conclusion and future research possibilities 22 Notes 23 References 24
- 13. 2 Self-assessment frameworks for business organizations 29 ASHOK KUMAR AND CEASAR DOUGLAS Introduction 29 TQM vs organization-based self-assessment frameworks 30 Self-assessment in the context of TQM 31 Implementation of self-assessment process 33 Self-assessment frameworks 38 Self-assessment frameworks and models 40 A comparative study of five self-assessment frameworks 49 Concluding remarks 49 Notes 50 References 50 PART II Quality improvement tools and techniques for the twenty-first century 55 3 QFD: customer driven design of products and services 57 GRAEME KNOWLES Introduction 57 Definition of QFD 58 The need for QFD 58 The principles of QFD 58 Who is the customer in QFD? 59 The customer view of quality 60 Implications of the model for QFD 61 Establishing the requirements 62 QFD case study 63 Building the QFD chart 65 Linking customer requirements to product features 66 Interactions between product parameters 68 Ratings and targets for the ‘hows’ and technical difficulty 69 Analysing the chart 71 The expanded QFD process 73 Managing QFD 74 Making QFD successful 74 QFD applications 75 The benefits of QFD 75 Critical review of QFD 76 Conclusion 78 References 78 viii Contents
- 14. 4 Taguchi methods of experimental design for continuous improvement of process effectiveness and product quality 81 JIJU ANTONY Introduction 81 Experimental design using the Taguchi approach 82 Applications and benefits of Taguchi methods in industry 83 The Taguchi’s quality philosophy 85 A systematic methodology for the Taguchi approach to experimental design 87 Case study 95 A critique of the Taguchi approach to experimental design 99 Conclusion 101 Note 101 References 101 5 Statistical process monitoring in the twenty-first century 103 MICHAEL WOOD Introduction 103 The philosophy, purpose and potential benefits of SPC/M 105 An illustrative case study 107 SPC/M in practice: problems and suggested solutions 110 Conclusion 116 Notes 117 References 118 PART III Case studies in Quality Management 121 6 TQM in higher education institutions: a review and case application 123 JAIDEEP MOTWANI AND GLENN MAZUR Introduction 123 Why implement TQM in HEIs? 124 Defining the ‘customer’ in HEIs 125 Classification of literature on TQM in HEI 126 Application of TQM in HEI: a case study 131 Future research directions 137 Conclusion 139 Note 139 References 139 Contents ix
- 15. 7 Do customers know what is best for them?: the use of SERVQUAL in UK policing 143 NICK CAPON AND VIVIEN MILLS Introduction 143 The SERVQUAL method 144 Evaluating SERVQUAL 145 Quality Management in policing 146 SERVQUAL in the Sussex Police Force 150 Data results 151 Conclusion 156 Acknowledgements 158 References 158 Appendices 161 8 Quality in the NHS: can we master the art of ‘conversation’? 166 HARRIET JEFFERSON Introduction 166 Background to quality in healthcare 167 Total Quality Management (TQM) 168 Audit 170 Health outcomes/health gain 173 Evidence-based medicine 174 Current approach to quality in healthcare 174 Evaluating health services 175 An ethnographic approach to service evaluation 178 Conducting the evaluation: a case study 181 Conclusion 189 Acknowledgement 190 References 190 9 Quality Management in public house retailing: a case study 195 DAVID PREECE, VALERIE STEVEN AND GORDON STEVEN Introduction 195 Bass Taverns 196 Change and restructuring in Bass Taverns 198 Quality Management initiatives 201 Conclusion 207 Note 209 References 209 x Contents
- 16. 10 Changing supervisory relations at work: behind the success stories of Quality Management initiatives 211 PATRICK DAWSON Introduction 211 Quality Management: the new enlightenment? 211 Supervision and Quality Management: some critical reflections 214 Quality Management and supervision in the Australian workplace 219 Conclusion 223 References 224 Index 227 Contents xi
- 17. Figures 1.1 CBR process in strategic quality problem-solving 12 1.2 ESAS scope and domain coverage – System Conceptual Framework (SCF) 15 1.3 ESAS structure 16 1.4 Case describing an experience of ‘competitor threat’ via new product release 17 1.5 Symbol hierarchy within ESAS 18 1.6 Form-like user orientated case representation 19 2.1 Determination of variance/gaps between the business excellence and existing model 37 2.2 Self-assessment/TQM models for organizational performance improvement 39 2.3 Malcolm Baldridge Award criteria and their inter-relationship 43 2.4 Business Excellence model 43 2.5 The continuous improvement model for self-assessment 46 2.6 Self-assessed Quality Management systems 47 3.1 The Kano model of quality 60 3.2 Affinity diagram for mountain bike 64 3.3 Customer information in the QFD chart 65 3.4 Linking customer requirements to product features 66 3.5 Adding the correlation matrix 68 3.6 Completed QFD chart 70 3.7 The expanded QFD process 73 4.1 The four phases of the methodology 88 5.1 Mean chart of hospital journey time 106 5.2 Mean chart similar to actual charts used 110 5.3 ‘Correct’ version of the mean chart 111 6.1 Akao’s concept of university evaluators 133 6.2 Affinity diagram of engineering managers’ needs 134 6.3 AHP to prioritize engineering managers’ requirements 135 6.4 Quality table for managers’ needs vs students’ skills 136 7.1 The SERVQUAL model 145
- 18. 7.2 UK police organizational structure 147 7.3 Who assesses the quality of our performance? 150 7.4 What do the police authority think of our performance? 151 7.5 Challenge analysis 152 7.6 What do all customers of our performance? 153 7.7 Revised results using factor analysis 154 7.8 Root causes 155 7.9 Reasons for Gap 2 156 7.10 Scope of quality in Police Service 157 8.1 A history of quality in healthcare 167 8.2 Approach most frequently used in services 176 8.3 Service evaluation framework 180 Figures xiii
- 19. Tables 1.1 Reasons for TQM failures 6 1.2 Advantages of using CBR for Strategic Quality Management 14 1.3 Evaluation results for ESAS 21 2.1 Malcolm Baldridge National Quality Award (2000): criteria for performance excellence 41 2.2 Malcolm Baldridge National Quality Award: criteria score sheet 42 2.3 Scoring criteria for EFQM Business Excellence model 45 2.4 Comparison of self-assessment models 50–1 4.1 A four-trial OA for studying two 2-level factors 83 4.2 Typical applications of Taguchi method in manufacturing sector 84 4.3 List of control factors for the Taguchi experiment 96 4.4 Experimental layout used for the study 96 4.5 Average SNR values 97 4.6 Results of pooled ANOVA on SNR 98 7.1 Use of Quality Management tools in the 43 forces of England and Wales 148 7.2 Sample sizes used for external data collection 151 7.3 Revised dimension clusters using factor analysis 153 7.4 Sample sizes used for internal data collection 154
- 20. Contributors Jiju Antony is a Senior Teaching Fellow at the International Manufacturing Centre of the University of Warwick, Coventry, UK. Nick Capon is a Senior Lecturer in Operations and Quality Management, Portsmouth Business School, University of Portsmouth, UK. Patrick Dawson is a Professor in the Department of Management Studies, University of Aberdeen, Aberdeen, Scotland, UK. Ceasar Douglas is a Professor of the Department of Management, Seidman School of Business, Grand Valley State University, Michigan, USA. Andreas J. Frangou is a Business Modeller within the Modelling Services Group, DHL Worldwide Express, Hounslow, Middlesex, UK. Harriet Jefferson is a Senior Research Fellow in the School of Nursing and Midwifery, University of Southampton, UK. Graeme Knowles is a Senior Teaching Fellow in Quality & Reliability, Warwick Manufacturing Group, University of Warwick, Coventry, UK. Ashok Kumar is an Assistant Professor of the Department of Management, Seidman School of Business, Grand Valley State University, Michigan, USA. Glenn Mazur is an Executive Director of QFD Institute, an adjunct lecturer of TQM and President of Japan Business Consultants Ltd, Michigan, USA. Vivien Mills is a retired Superintendent from Sussex Police. Jaideep Motwani is a Professor in the Department of Management, Seidman School of Business, Grand Valley State University, Michigan, USA. David Preece is Professor of Technology Management and Organization Studies and Head of the Human Resource Management Corporate Strategy Group at the Business School of the University of Teesside. Gordon Steven is the Managing Director of Betting Direct. Valerie Steven is a Senior Lecturer in Human Resource Management of Coventry Business School, Coventry University, UK. Michael Wood is a Principal Lecturer in Portsmouth Business School, Univer- sity of Portsmouth, Portsmouth, UK.
- 21. Acknowledgements As editors and as chapter authors, we have benefited from the advice and help of a number of people in the preparation of this book. At Routledge, the book was conceived during Stuart Hay’s stewardship of the Business and Management list, carried forward by his one-time assistant and subsequent successor, Michelle Gallagher, and the manuscript was submitted to one of her successors, Francesca Lumkin. We thank them for their encouragement and forbearance and we also thank the two reviewers appointed by Routledge to comment upon earlier drafts of the chapters. This collection of ideas on Quality Management and quality engineering was conceived during the year 1998–99 when Jiju had finished writing his book on Experimental Quality. When he took his ideas to David, he foresaw the potential which resulted in the present volume. Jiju’s work on this book reflects his experiences and lessons learned from his previous book as mentioned above. He would like to thank Dr Hefin Rowlands of the University of Wales Newport and Dr Ranjit K. Roy of Nutek, Inc. for their critical comments on the earlier drafts of his chapter. Special thanks also go to the members of the Quality and Relia- bility Group of the University of Warwick for facilitating his work. David’s work on the book was greatly facilitated by the sabbatical he enjoyed during the second semester of the 1999–2000 academic year, and he would like to thank his colleagues in the Department of Business and Management at the University of Portsmouth for their support, particularly Peter Scott who took over most of his teaching for that semester. In addition, a number of people from public house retailing companies were only too pleased to divert their time to responding to questions and observations on Quality Management matters; it is a pity they cannot be mentioned by name for reasons of confidentiality.
- 22. Glossary AHP Analytic Hierarchy Process AI Artificial Intelligence ANOVA Analysis of Variance BEM Business Excellence Model BPR Business Process Re-engineering CA Clinical Audit CBR Case-based Reasoning CEO Chief Executive Officer COQ Cost of Quality EFQM European Foundation for Quality Management EQA European Quality Award ESAS Enterprise Strategic Advisory System HEIs Higher Education Institutions HMIC Her Majesty’s Inspectorate of Constabularies ISO International Organization for Standardization MBNQA Malcolm Baldridge National Quality Award OA Orthogonal Array OFAAT One Factor At A Time QA Quality Assurance QCIM Quality Competitiveness Index Model QFD Quality Function Deployment ROI Return on Investment SERVQUAL Service Quality SNR Signal-to-Noise Ratio SPC Statistical Process Control SPM Statistical Process Monitoring TQM Total Quality Management WPC Worker Participation Committee
- 23. Introduction In the pursuit of continuous improvement of product and service performance, quality is a major focus for contemporary organizations. This book is designed to provide the reader a critical appreciation of key Quality Management tools, techniques and implementation into both manufacturing and service organi- zations through drawing upon the research findings of a range of specialist scholars who have gathered together an extensive range of new data from organizations in the manufacturing, healthcare, higher education, policing, and leisure retailing sectors across a number of countries. Given that the subject of Quality Management has become quite broadly based and generated a considerable number of tools, techniques and frame- works, we have had to be rather selective in the particular tools, techniques and frameworks we have chosen to review and evaluate. All the more so because, in any event, this is not a textbook, but rather is centrally concerned to explore the challenges faced and issues raised when those tools, techniques and frameworks are applied in organizations – and how, if at all, attempts were made to resolve those challenges. What we are arguing, then, is that Quality Management can only really be understood through a critical examination of its implementation, and that this necessitates a research design which incorporates an attempt to ‘get close to the action’ of everyday practice (see also Wilkinson and Willmott, 1995; Wilkinson et al., 1998). This is not to argue or imply that the strategic dimension should or can be ignored in focusing upon implementation for, while we are primarily interested in the latter, we recognize that some at least of this activity takes place within a context which is framed by wider, especially man- agerial, considerations relating to such matters as corporate, business unit, human resource management, and manufacturing/service quality strategies. Hence, we felt it important to begin the book with two chapters which concen- trate upon this strategic dimension of quality and which provide some frame- works and means for developing or extending an organization’s strategic Quality Management capability (that is, by using case-based systems or self-assessment frameworks). There are an extensive number of texts and textbooks on Quality Management (see, for example, Beckford, 2001; Dale, 1994; Oakland, 1993; Kolarik, 1995; Bergman and Klefsjo, 1994). What we are offering here is not another textbook,
- 24. but rather a book which will allow the reader to appreciate some of the complex- ities and problems associated with the implementation of some of the key tools, techniques and frameworks of Quality Management in contemporary organi- zations. Thus, it is assumed that readers are already acquainted with the broad subject matter of Quality Management though having taken an introductory course and/or relevant work experience and reading. The present book is designed to build upon this grounding by offering a more specialist treatment of certain aspects of Quality Management which are either not covered or only summarily covered in the textbooks. This treatment is facilitated through the brief overview which is provided by the chapter author(s), where appropriate, of that particular tool, technique or framework, followed by a critical review and case study application, along with a guide to further reading. The references for each chapter are gathered together, chapter by chapter, at the end of the book, in order that the reader can more readily gain an overview of all the secondary material referred to in the book. The book, then, focuses upon Quality Management implementation issues and challenges. It adopts a critical orientation, one which is based upon an engage- ment with practice through case study research. It also provides a systematic approach for both understanding and assessing the implementation of quality tools and techniques in a variety of business contexts. Many of the texts avail- able in the area adopt a technicist/rationalistic approach: ‘If only people in organizations acted more rationally and followed the tools and techniques to the letter, then most quality problems could be resolved.’ They also commonly have a limited anchorage in the organizational literature and/or make no or only very limited use of primary data. Our view is that this leads to both a poor under- standing of practice and (hence) a weak basis upon which to intervene in or manage Quality Management initiatives. It is intended that the material pre- sented in the first two chapters should provide a strategic orientation of quality. It should be added at this juncture that the data has been gathered from organi- zations in three countries: the United Kingdom (Chapters 1, 3–5, 7–9), the United States (Chapters 2 and 6) and Australia (Chapter 10), although there is, of course, quite a bit of ‘overlapping’ of the countries implied or considered at various points. Given that many of the literature reviews are cross-national, there is, then, an international flavour to the overview and evaluation of Quality Management implementation presented here. The book is carefully designed and presented so that it will be suitable for a wide spectrum of readers, ranging from undergraduates to Quality Management practitioners in the field of Quality Management. To illustrate, we are thinking of courses such as BA/BSc Business/Management Studies/Business Administra- tion, International Management, Mathematics and Statistics, BEng Mechanical, Chemical, Electrical, Electronic, Manufacturing, Engineering, where Quality Management is taught as either a core or optional subject or forms an important part of a wider subject, and covered typically in the final year of the programme, following groundwork studies in earlier years. With respect to postgraduate programmes, we are thinking particularly of Masters/courses in Business Introduction xix
- 25. Administration, Quality Management, Quality and Reliability, Manufacturing Management/Engineering Business Management, Industrial and Systems Engin- eering/Manufacturing Systems Engineering. The book will also be of relevance for people who are studying programmes leading to professional examina- tions/membership in cognate areas such as the Institute of Quality Assurance, Certified Quality/Reliability Engineer/Technician. Provided below is an overview of the chapters which make up the rest of the book. We move from a consideration of some key strategic issues associated with Quality Management, through an in-depth examination of certain key Quality Management tools, techniques and frameworks, to five case study chap- ters which relate, evaluate and comment upon the implementation of Quality Management in a variety of sectors, both public and private: manufacturing, higher education, healthcare, police, and public house retailing. These chapters illustrate many of the challenges and problems which are posed when the various tools and techniques are applied, and how actors in the relevant organi- zations have attempted to overcome them – and whether indeed (and if so in what senses) they can be said to have succeeded. More specifically, then, Part I of the book consists of two chapters: Chapter 1 addresses the strategic issues of Quality Management using the application of AI techniques such as Case-Based Reasoning (CBR) and Chapter 2 provides a com- parative evaluation of self-assessment frameworks for business organizations for developing and facilitating change. Part II consists of three chapters – all of them are arranged in a sequential order for designing quality into products and processes. The contents in these chapters are essential for organizations embark- ing on what we call today Six Sigma Business Improvement Strategy. The tech- niques and tools presented in Part II provide invaluable guidance for designing, optimizing and controlling product and process quality. Part III, which consists of five chapters, centres around the presentation and analysis of case study research into the implementation of some of the tools, techniques and/or frame- works, considered in the previous two main sections of the book, in contempor- ary organizations. While this is also the case in many of the previous chapters, here there is a focus upon a particular sector, such as healthcare or higher educa- tion, and more attention is devoted to the organizational, people and managerial issues and contexts associated with implementation. In other words, while the tools, techniques and/or frameworks are foregrounded in the first two sections, in this last section it is the organizational issues which are foregrounded, with the tools etc., being backgrounded. It is also the case that the majority of the illustrative/primary material presented in Part II is drawn from the manufactur- ing sector, whereas in Part III non-manufacturing sectors are represented much more strongly, in particular policing, leisure retailing, healthcare and higher education. Chapter 1 introduces the reader to general Artificial Intelligence (AI) tech- niques and explores the notion of strategic quality from the perspective of con- tinuous improvement and business performance. The chapter also describes in detail the development and evaluation of a case-based intelligent system to xx Introduction
- 26. encourage the application of case-based reasoning methodology to quality and business. Chapter 2 examines critically the topic of self-assessment in relation to five diverse frameworks: Malcolm Baldridge National Quality Award model, Busi- ness Excellence model, Continuous Improvement model, Quality Management systems model and Quality Competitiveness Index model. A comparative evalu- ation of these five frameworks over several desirable attributes is also presented. Chapter 3 establishes the core principles of Quality Function Deployment (QFD) as a technique to design and develop products or services which is driven by the needs of the customer. The chapter also elucidates the strengths and limitations of the technique, the critical factors for the successful implementa- tion of the technique and also throws light on the issues around the team forma- tion for the application of QFD. Chapter 4 illustrates the importance of experimental design technique in particular Taguchi approach to industrial experimentation. A systematic method- ology for design/process optimization is also presented in order to assist people in organizations with limited skills in experimental design techniques. A case study from a hot forming process is presented. The chapter concludes by reveal- ing a critique of experimental design advocated by Taguchi. Chapter 5 provides a brief overview of Statistical Process Control (SPC) and explains its potential benefits and underlying assumptions. The chapter also looks at the difficulties in the application of SPC (or more accurately SPM – Statistical Process Monitoring) and possible ways of resolving them. A case study from a manufacturing company is presented to illustrate various issues involved in the implementation of SPM. Chapter 6 discusses the implementation of TQM in Higher Education Sector. The chapter fundamentally explains a case application of QFD in designing a new course in TQM at the University of Michigan, USA. Chapter 7 discusses whether a customer centred approach to Quality Manage- ment is appropriate in UK policing. The paper describes the application of SERVQUAL (or the so-called GAP model) in assessing service quality. The chapter concludes that apart from the Gap model, other methods such as process mapping and the Business Excellence model need to be used to improve value quality and technical quality respectively. Chapter 8 introduces the evaluation of quality in the healthcare sector in particular the National Health Service (NHS) in UK. The paper reveals the dif- ficulties in the successful application of TQM principles in the NHS. Chapter 9 focuses upon Quality Management initiatives within the UK public house retailing sector. It was found that QC/QA orientation predominates within the sector and that a TQM project introduced in the early 1990s did not become embedded within the organization, although a number of public house managers were predisposed towards it and were beginning to adopt TQM-type practices within their pubs. Chapter 10 emphasizes the importance of supervisory relations at work in organizations. The chapter highlights the more complex process of supervisory Introduction xxi
- 27. change by drawing longitudinal data from a National Programme of Australian research. The chapter concludes that there are no simple prescriptions for the development of harmonious quality cultures or one-minute recipes for imple- menting new forms of industry democracy at work. References Beckford, J. (2001) Quality: A Critical Introduction, 2nd edn. London: Routledge. Bergman, B. and Klefsjo, B. (1994) Quality – from Customer Needs to Customer Satisfaction. McGraw-Hill, UK. Dale, B. (1994) Managing Quality, 2nd edn. Hemel Hempstead: Prentice Hall. Kolarik, W. (1995), Creating Quality: Concepts, Systems, Strategies and Tools. New York: McGraw-Hill. Oakland, J. (1993) Total Quality Management: The Route to Improving Performance. London: Butterworth-Heinemann. Wilkinson, A. and Willmott, H. (1995) Making Quality Critical: New Perspectives on Organizational Change. London: Routledge. Wilkinson, A., Redman, T., Snape, E. and Marchington, M. (1998) Managing with Total Quality Management: Theory and Practice. Basingstoke: Macmillan. xxii Introduction
- 28. Part I Developing a strategic orientation for Quality Management
- 30. 1 Promoting a strategic approach to TQM using a case-based intelligent system Andreas J. Frangou Introduction Intelligent systems research is an area of artificial intelligence (AI) dedicated to the study and development of machines (notably computers) that can display and replicate human intelligent behaviour such as understanding, learning, reasoning and problem-solving (Michalski and Littman, 1991: 64; Schank, 1990). Traditionally AI research is concerned with the broad study of human intelligence and its replication. This can have more theoretical, technical and philosophical implications for AI research such as the following: • the nature of intelligence itself (i.e. what is intelligence and what are its components); • the development of models of human reasoning, problem-solving, know- ledge representation and cognition; • the development of tools and techniques such as AI programming environ- ments (i.e. LISP and PROLOG) and learning algorithms to assist know- ledge elicitation. The field of intelligent systems is distinct from other areas of AI, only in that it focuses on the advancement of methodologies and tools that can aid in the development, application and evaluation of systems to real world systems. This chapter therefore does not aim to provide a deep theoretical and philosophical understanding of AI, rather, it focuses on the application of intelligent systems to business, by reporting on research into the development and evaluation of a prototype intelligent system called ESAS (Enterprise Strategic Advisory System). ESAS is a case-based intelligent system1 designed to provide support for TQM and competitive advantage. The overall goal of the system is to encourage proactivity and creativity in organizations during strategic quality problem-solving and decision-making. In sharing the experiences of developing and evaluating ESAS, this chapter aims to demonstrate to the reader the potential of AI and intelligent systems for business through the following:
- 31. • an analysis of the strategic significance of quality to firm performance, and the potential benefits of using intelligent systems to promote and encourage strategic thinking within organizations; • an introduction to some of the theoretical and technical issues in developing intelligent systems, including a detailed discussion of the appropriateness of case-based reasoning for TQM applications; • a description of ESAS’s scope and development process, including the systems evaluation; • a summary and conclusion discussing both what has been learnt from ESAS’s development, and the future potential of such systems to business. Linking TQM and performance: a strategic perspective TQM and competitive advantage Quality as a means of creating and sustaining a competitive advantage has been widely adopted by both public and private sector organizations (Frangou et al., 1999). This strategic stance has been fuelled by the growing attention to stra- tegic quality (Leonard and Sasser, 1982; Jacobson and Aaker, 1987; Brown, 1996; Wilkinson and Willmott, 1995) arising from the international successes of Japanese and other South Eastern Asian countries (Powell, 1995) and research that has focused on the link between quality (TQM) and business performance (Reed et al., 1996; Powell, 1995; Buzzell and Gale, 1987; Jacobson and Aaker, 1987; O’Neal and Lafief, 1992; Capon et al., 1990; Curry, 1985). Furthermore as Morgan and Piercy (1996: 231) state ‘Consequently, quality improvement has been widely cited as a basis for achieving sustainable competitive advantage.’ To improve quality, businesses have applied ‘Total Quality Management’ (TQM) to their organizations to help them plan their efforts. The promise of superior performance through continuous quality improvement has attracted a wide spectrum of business to TQM, with applications reported in domains such as: finance (Wilkinson et al., 1996), utilities (Candlin and Day, 1993), federal agencies, healthcare, education and research, environment and manufacturing (Lakhe and Mohanty, 1994). A number of studies have focused on the effectiveness of TQM initiatives (in particular the use of self-assessment frameworks) in improving performance (General Accounting Office (GAO), 1991; Wisner and Eakins, 1994; Davis, 1992; Johnson, 1993). The US General Accounting Office (GAO) in 1991 studied the performance of the twenty highest scoring Baldridge Award appli- cants. It found that organizations had achieved improvements in the following areas: employee relations, quality, costs, market share, profitability, and customer satisfaction. The GAO also identified common features among these organizations which included strong leadership, employee involvement, cus- tomer focus, open cultures, and partnership programmes (Powell, 1995). An International Quality study conducted jointly by the American Quality Founda- tion and Ernst & Young sampled over 500 organizations operating in various 4 Andreas J. Frangou
- 32. industries such as computer, automobile, banking and healthcare (American Quality Foundation, 1991). Their findings showed that process improvement and supplier accreditation practices did improve performance.2 Although evidence exists which supports the effectiveness of TQM initiatives, a large number of studies have shown that between 60 per cent and 80 per cent of TQM initiatives fail, or fail to show significant impact on business perform- ance. Wilkinson et al. (1996), state that a recent survey of 80 major financial institutions conducted by KPMG Management Consulting found that 80 per cent of participants had implemented some form of quality initiative that had little impact on ‘bottom-line profits’. They also point out that another survey con- ducted by Tilson (1989) showed that few initiatives ‘had any significant impact, either on customer perceptions or commercial results’. Wilkinson et al.’s (1996) own survey of quality initiatives within the financial services sector (122 com- panies being surveyed) highlighted the lack of impact on financial benefits with only 35 per cent of respondents reporting that profitability had improved. Knights and McCabe (1997: 38) point out that ‘management may not always understand the implications or appropriateness of the quality initiatives they adopt’. Their study of TQM initiatives within the financial sector also high- lighted the ‘conformance to requirements’ approach taken during quality improvement programmes, which they state is inconsistent with the strategic intentions of the business which should focus on ‘customers’ and ‘culture’. Tatikonda and Tatikonda (1996) report on surveys of quality improvement pro- grammes carried out by the Boston Consulting Co., McKinsey Co. and the Elec- tronic Assembly Association. These surveys highlighted the problems associated with TQM implementations, the high rate of failures and lack of impact on performance. Boston Consulting Co. (Schaffer and Thomson, 1992) found that only one-third of the organizations attributed their improved competitiveness to TQM. Tatikonda and Tatikonda’s (1996) own findings suggest that in many cases TQM programmes lack focus on critical business areas that have a good ‘return on quality’. Tatikonda and Tatikonda’s (1996: 7) argue that organizations must measure the ‘cost of quality’ (COQ), otherwise there is a danger that resources are spent on improvements customers do not care for, and pick projects with only marginal benefits. They also advocate extensive COQ reporting as a means of accurately communicating the impact of quality projects on the business, thus enabling the prioritizing and coordination of valuable resources, and the motiva- tion of personnel. Other commentators also report on the poor rate of quality initiatives, and have suggested the reasons shown in Table 1.1. The suggested reasons for the reported failures summarized in Table 1.1 raise some important issues for TQM. Writers have identified a lack of focus and effective enterprise guidance in targeting critical areas for change during quality improvement programmes. Thus for programmes to be successful, organizations need concise guidance to implement quality improvements effectively. They also need to assess the costs of the programme and its potential outcomes (Tatikonda and Tatikonda, 1996). Furthermore, the lack of strategic focus and integration shown in TQM suggests that quality initiatives are carried out in Promoting a strategic approach to TQM 5
- 33. isolation, and do not involve other departments and functions such as marketing and strategic planning (Schmalensee, 1991). For example, Law and Cousins (1991) claim that marketing and business strategists are usually neglected in quality improvement programmes which are considered to be primarily the concern of manufacturing. This approach may affect whether or not critical/ strategic areas are focused on, where there is the greatest potential for return on investment (ROI) (Tatikonda and Tatikonda, 1996), bearing in mind that it is mainly the marketing function that gathers strategically important market intelli- gence (Butz, 1995). Hubiak and O’Donnell (1996: 20) argue that American organizational ‘mind-sets impose serious constraints on the implementation of TQM’, because they are usually individualist in nature, internally competitive, problem-solving and crisis orientated, linear thinking, and control orientated. Furthermore, they claim that management practices that try to create order through the development of guidelines and procedures constrain the organi- zation’s ability to grow and learn: An organization needs to learn how to anticipate and stay ahead of change. Rules and procedures can rigidify a system, which channels thinking into the most obvious paths and inhibits creativity. The creation of a learning organi- zation demands a proactive, curious, self-directed learner, able to take the perspective of the entire system to address problems or new initiatives. (p. 23) 6 Andreas J. Frangou Table 1.1 Reasons for TQM failures The lack of ‘top management commitment’ (Atkinson, 1990) The implementation of changes that are only internally focused, with little external or customer focus (Foster and Beardon, 1993) ‘Continuous improvement’ did not permeate the strategic process (Gallaher, 1991; Walker, 1992; Boyce, 1992) Lack of focus on critical business processes, no resource support for long term improvement efforts, and a lack of synergy between quality programmes and overall strategy (Erickson, 1992) Poor timing and pacing of TQM initiatives, that are generally crisis led (Brown et al., 1994) Lack of measurement in all key areas, but particularly at a strategic level (Dyason and Kaye, 1996) TQM concepts and terminology are barriers to success, because there is no consensus on their meaning (Foster and Whittle, 1989) No supporting infrastructure for cultural change and people issues (Seddon, 1992) Managerial or organizational ‘mind-sets’ that are inconsistent with the TQM philosophy (Hubiak and O’Donnell, 1996)
- 34. Strategic quality, focus and dynamism: the missing links in TQM Porter (1996) claims that quality improvement programmes usually focus on improving operational effectiveness. This, and the ability to satisfy both cus- tomers and stakeholders, is an important factor in the battle for competitive advantage. However, improvements in these areas are not enough to make an organization competitive. Furthermore, ‘few companies have competed success- fully on the basis of operational effectiveness over an extended period, and staying ahead of rivals gets harder every day’ (1996: 63). The reasons for these long-term failures are that ‘competitors can quickly imitate management tech- niques, new technologies, input improvements and superior ways of meeting customer needs’ (p. 63). Porter argues that the missing link in quality improve- ment programmes is strategy. Butz (1995) also takes this view, suggesting that the root cause of many TQM failures is the limited integration of TQM pro- grammes with the fundamental strategies of the business. This view is consistent with other researchers within the TQM field who have also identified the lack of a strategic focus in quality initiatives as a main cause of failures (Foster and Beardon, 1993; Atkinson, 1990; Gallaher, 1991; Erickson, 1992; Dyason and Kaye, 1996). Self-assessment frameworks (and their associated models) can be key drivers of TQM initiatives, and useful tools for guiding organizations through the process of quality improvement, as they provide a structured approach to developing a philosophy of continuous improvement (Davis et al., 1996). However, issues have been raised about their validity, and their real effectiveness in improving the performance of organizations (Black and Porter, 1996; Wiele et al., 1995). Conti (1997) also expressed concerns regard- ing their lack of a strategic focus, suggesting that company mission, goals and objectives should be systematically considered more within the frameworks. Quality Management researchers have found that quality initiatives are generally too introspective and internally focused (Foster and Beardon, 1993). Wiele et al.’s (1995: 15) own study of self-assessment in European organizations con- firms this view, in that the highest ranking reason for starting self-assessment is ‘internal issues’. The above discussion has raised some important issues relating to the lack of strategic and market focus in many TQM initiatives. This lack of strategic and marketing activity in quality improvements provides the key proposition focus- ing on the notion of strategic quality: Promoting a strategic approach to TQM 7 1 Requirement for Strategic Quality – i.e. initiatives, quality improve- ment programmes, product and service developments that are market-led, continually satisfy the requirements and expectations of the external environment, and thus create and sustain a competitive advantage.
- 35. A lack of focus, and integration of quality improvement initiatives with an organization’s management practices, is another key deficiency of quality efforts aiming to achieve tangible business objectives. If the market does not want or need these improvements, or if no real enhancement to the business can be achieved, then the initiative is not viable (Iacobucci, 1996). Too many quality improvement programmes fail to focus on critical, strategic business processes, which provide a good return on investment (ROI) (Tatikonda and Tatikonda’s, 1996; Erickson, 1992). Brown et al. (1994) raise questions about the timing and pacing of TQM programmes, suggesting that the prioritizing of critical areas for change is the key to successful implementation. This leads to the second main proposition, that there is a requirement for prioritized and focused quality initiatives: 8 Andreas J. Frangou An organization’s ability to change continually and learn to innovate in relation to the changing marketplace is also a key issue for TQM programmes. As Hubiak and O’Donnell (1996) claim, the process of developing organizational procedures, guidelines or rules can constrain learning, creativity and innovation. Organizations engaged in quality improvement programmes typically operate in an introspective manner (Foster and Beardon, 1993; Hubiak and O’Donnell, 1996), and non-critical or non-strategic areas are focused on (Tatikonda and Tatikonda, 1996). Hubiak and O’Donnell found that most organizations engaged in quality improvements (including the Malcolm Baldridge National Quality Award (MBNQA) winners) were mainly involved in problem-solving, and product development was generally ‘reactive, responding to rather than antici- pating customer demands’ (p. 25). This leads to the third and final proposition – that organizations and their programmes must be dynamic: 2 Prioritized and Focused Quality Initiatives that are focused on areas or processes that add value to: • the customer, who sees and appreciates this value and is willing to pay for it, over competitors products and services; • the organization in terms of profit, market share, reputation and position, and to all its stakeholders including the community. 3 Dynamism: Organizations and their quality improvement programmes must be dynamic. They must have the ability to drive, respond and anticipate the continually changing forces, requirements and expecta- tions of both the external and internal environment.
- 36. These three propositions provide the structure and focus of the chapter. The next section introduces the concept of an intelligent system for addressing the above issues. The use of intelligent systems to support TQM initiatives The above discussion and analysis has raised important issues for TQM implementation: (1) it has identified the three issues that are the key strategic factors in the reported failures of TQM programmes; (2) the discussion has highlighted the need for strategic support and guidance during quality improve- ment programmes; it is important for businesses to know what changes need implementing and why, and what impact they will have on their perform- ance; (3) once a key business area has been identified, how should the organi- zation go about implementing the change – what techniques, methods or resources will it allocate and use? Expert advice or knowledge about the problem domain – TQM and competitive advantage would be highly useful to the organization when making such important strategic decisions. Consultants provide expert support in solving difficult problems, and can be cost effective if they are internally sourced and the organization is sufficiently sized and resourced to employ such experts. If, however, an organization is not in this position and seeks outside consultants, the cost incurred could therefore be pro- hibitive (Bird, 1997). An alternative solution is to use an intelligent system that stores and uses domain expertise and knowledge required to support the problem-solving or decision-making process. This overcomes the expense of ‘buying-in’ expertise to support strategic decisions, which is often a short-term solution to the problem. Furthermore, if an organization does employ an internal expert, their knowledge and skills can be stored within an intelligent system. This has the following benefits for the organization (Guida and Tasso, 1995: 119): • the intelligent system could support decision-making tasks that are more general in nature, thus allowing the expert to deal with more strategic or critical tasks; • it allows an organization to capture and store their valuable expertise which otherwise could be lost due to employee turnover or retirement; • it enables an organization to effectively distribute and exploit knowledge throughout the organization, and thus proliferate a consistently high level of expertise across a number of sites; • it makes knowledge explicit, promoting organizational learning. The application of intelligent systems technology to the TQM and competitive advantage domains can yield similar ‘knowledge-based’ benefits for organi- zations implementing quality improvement programmes. Furthermore, it could store and utilize knowledge and expertise that would both highlight the need for, and provide support for, strategic quality, prioritized and focused quality Promoting a strategic approach to TQM 9
- 37. initiatives and dynamism. There is growing interest in the use of intelligent systems in business, in particular for enhancing financial and marketing activ- ities, improving decision-making procedures at strategic levels, and for support- ing TQM initiatives (Mockler and Dologite, 1992; Guida and Tasso, 1995; Edgell and Kochhar, 1992; Bird, 1997). However, the concept of using an intel- ligent system to encourage a strategic and market-led approach to quality improvement programmes, is novel. The research project proposes the develop- ment of an intelligent system called ESAS – Enterprise Strategic Advisory System which is designed to address the domain/research issues identified above. In addition, ESAS has been designed in the spirit of TQM frameworks and models such as ISO 9000, EFQM and MBNQA; in that the system will be generic in nature and designed to provide advice that can be considered useful by most organizations, private and public. The design, development and evalu- ation of the ESAS prototype essentially represents a feasibility study, which assesses the potential of applying intelligent system technology to the domains of TQM and competitive advantage. Development of the Enterprise Strategic Advisory System As discussed earlier, intelligent systems are designed to display the qualities inherent in human intelligent behaviour for a particular task or problem domain, a major component being the simulation of human reasoning (Jackson, 1990). This basically involves an attempt to emulate a human’s problem-solving or task performing abilities, which can include: diagnosis, monitoring, control, predic- tion, design and planning. The selection of an appropriate method or reasoning paradigm for a system will depend greatly on the application domain (Kolodoner, 1993). Michalski and Littman (1991) state that AI research has two general paradigm options to choose from: the symbolic paradigm and the connectionist paradigm. The sym- bolic paradigm focuses attention on the manipulation of symbolic representa- tions to derive inferences. Symbolic representations are essentially; rules, objects, frames, scripts, semantic nets and cases.3 The connectionist paradigm focuses on the ‘non-distributed perspicuous knowledge representations, and their modification through changing weights of their interconnections’ such as Neural Networks (NN) (Michalski and Littman, 1991: 66). The latter state that the chosen paradigm not only depends on the characteristics of the application domain, but also on the researcher’s own view of human cognition. General techniques currently being used within symbolic and connectionist methodolo- gies are Rule-Based Reasoning (RBR),4 Model-Based Reasoning (MBR),5 and Case-Based Reasoning (CBR) (Symbolic) and Neural Networks (NN)6 (Connec- tionist). As stated earlier, ESAS is a case-based intelligent system, and thus uti- lizes CBR as its AI technique. The rationale for this is based on the complexity of the application domain of TQM and the systems requirement for dealing with dynamism and change. The following section discusses in detail the rationale for adopting CBR over other AI techniques such as RBR, MBR and NN. 10 Andreas J. Frangou
- 38. Case-based reasoning: the appropriate technique? Case-based reasoning (CBR) is based on the proposition that human experi- ences are stored in the human brain in the form of previous cases, rather than a set of rules (Riesbeck and Schank, 1989). This implies that experts solve prob- lems through the application of their experience, whereas novices solve prob- lems by applying rules (Watson and Abdullah, 1994). CBR represents knowledge in the form of cases. Each case represents an experience or episode of an event or task within a domain. Problem-solving and reasoning for CBR are therefore a process of remembering a case or experience which is similar to a new situation, and using the solution within this retrieved case to derive a solution for the new situation. Because CBR represents its domain knowledge by a store of cases, it does not require an explicit domain model as in RBR and MBR, so knowledge acquisition simply becomes a task of gathering case histories to build-up a case-library (Watson, 1995).7 Dynamism is a key feature of the application domain. Since CBR is not con- strained to a model, it allows the addition and subtraction of new cases or experience as they arise (i.e. from activities or changes in the environment) without the need of complex debugging as in rule-based reasoning (RBR). In addition, researchers studying TQM and its implications for competitive advant- age have stated that no empirically proven model or theory exists that can accu- rately and confidently represent the domain (Black and Porter, 1996; Matter et al., 1986). Therefore it must be assumed that these theories and models are weak, and that AI approaches that require extensive modelling are not appropri- ate for ESAS. Research carried out by Dreyfus (1982) that examined the human process of knowledge acquisition for business experts concluded that experts have a superior perceptual ability to grasp or understand a problem quickly, compared to novices. This form of knowledge or intuition allows experts to perform a detailed situation assessment of the new problem, and then use past concrete situations as paradigms, which leads them to the relevant part of the problem, without wasting time deliberating over irrelevant options (Benner, 1984). These findings of expert problem-solving substantiate the work carried out by Schank and Abelson (1977), Schank (1982) and Riesbeck and Schank (1989) in reminding and problem-solving through cases. In addition, an initial investigation into the nature of problem-solving in the domain of study has shown that when addressing strategic quality problems and creating strategies for competitive advantage, managers and strategists do so in a case-based way.8 When asked how they approach strategic quality problems, they stated that they would search for past problems that have been solved for guidance on how to solve the new problem (see footnote 3). This would involve using information about the new situation (i.e. a problem description) to guide the search for similar cases. Depending on the type and nature of the problem, searching would be carried out on either a store of cases on file (e.g. filing system, wordprocessor files, databases, Quality Management systems), or from Promoting a strategic approach to TQM 11
- 39. memory. The ‘best match’ case will then be retrieved, adapted, evaluated and repaired until it fits the new situation (Figure 1.1). Asked why a case-based approach was used during strategic quality problems, the interviewees stated that using past cases avoided the need to return to first principles and bypassed options that have or will fail to produce desired out- comes. As one of the interviewees stated, ‘we haven’t got the time to start solving problems from scratch’. However, CBR does have its drawbacks. By its nature it can only provide approximate, or partial solutions to problems,9 and when a best-match past case has been retrieved, its solution almost always needs adaptation to fit the new situation (Kolodoner, 1996; Wan, 1996). Adaptation is an important issue for CBR, and can sometimes be a difficult and complex problem depending on the level of automation of the intelligent system.10 Rule- based systems on the other hand overcome the issue of adaptation, because they provide users with exact matches to problems and their solutions are usually accepted verbatim. RBR systems are also well suited to domains that are well understood, because the rule-base can be developed much more quickly, and the domain can be represented more deeply (Althoff et al., 1995; Kolodoner, 1993). The negative side to these attributes is that any problem outside the rule-base will receive no output and thus no guidance. MBR also overcomes the problems associated with adaptation, because they hold knowledge about the validation and evaluation of solutions. They do not, however, offer any guidance for construction of solutions to problems (Kolodoner, 1993). Adaptation is not an issue for NN, but their solutions and 12 Andreas J. Frangou Mkt-led quality EST MEA Case-library of strategies Search Retrieve best match case Adapt Evaluate Repair Accept case and store Until case fits new situation “New problem requirements” Figure 1.1 CBR process in strategic quality problem-solving. Source: adapted from Frangou, 1997.
- 40. internal workings lack transparency, and the resulting system cannot be easily validated by domain experts (Althoff et al., 1995). Table 1.2 summarizes the applicability and advantages of using CBR in stra- tegic Quality Management implementation (Frangou, 1997; Frangou et al., 1998; 1999). ESAS: promoting strategic quality through case-based strategies The Enterprise Strategic Advisory System is a case-based prototype intelligent system designed to encourage Quality Management specialists to behave more dynamically and strategically with regards to quality improvements. In essence, ESAS acts as a teaching and learning tool, presenting users with case-based strategies that describe both successful and unsuccessful attempts at improving an organization’s performance through quality. It is hoped that through this process of case-based consultation, the user is exposed to a broad range of cases from differing industries that emphasize the strategic significance of quality. This heightened strategic awareness, will in turn filter through to quality improvement programmes, where a more innovative approach to quality at a strategic level will be adopted. The scope and structure of ESAS ESAS has been implemented on a personal computer (PC) windows platform using a CBR development shell called ReMind™ (Cognitive Systems, 1992). The system has been designed with both public and private sector organizations in mind. ESAS’s case-library (case memory) stores over 100 cases that have been collected from a broad range of organizations. Collaborating organizations included those operating in healthcare, manufacturing, higher education, finance and insurance, information systems, and the judicial system. Case data was sourced from senior managers and two directors with specific responsibility for influencing and developing quality policies. Cases were collected through inter- views and postal surveys. The case collection process focused on episodical data that described how managers went about addressing strategic quality problems and decision-making. Specific emphasis was placed on the key driving issues raised, i.e. strategic quality, focus and dynamism. From this perspective past case data that described the process of market environmental analysis (MEA) and enterprise strategy (EST), and their importance and impact on quality policy was targeted (Frangou et al., 1999). The scope of ESAS is based around these two business tasks as illustrated in Figure 1.2. Figure 1.2 illustrates ESAS’s system conceptual framework (SCF), which specifies the boundaries of the system and the proportion of the problem domain it covers. The SCF also highlights the type and nature of the cases that need to be stored within the systems case-library. It is the product of a detailed problem domain task analysis that examined the business tasks outlined above, i.e. MEA Promoting a strategic approach to TQM 13
- 41. 14 Andreas J. Frangou Table 1.2 Advantages of using CBR for Strategic Quality Management (SQM) No explicit domain model exists, and current modelling techniques are inadequate as the market environment is ever changing and so complex. CBR does not require an explicit model, so knowledge elicitation is achieved by acquiring cases (Watson, 1995) ‘Strategic planning is heuristic and judgmental in nature with knowledge not being as structured as in the form of production rules’ (Arunkumar and Janakiram, 1992). Studies into the nature of business expertise and problem-solving show that it is case-based (Dreyfus, 1982). This suggests that the problem domain is more suited to CBR techniques than MBR or RBR CBR systems have the ability to grow and learn as new knowledge becomes available. This feature is relevant to the problem domain, because as market changes are experienced, these new cases can be simply inputted into the system. This would not be easy for rule or model base systems, because the updating process would require complex debugging for the inclusion of new knowledge. Therefore CBR systems are easier to maintain (Frangou et al., 1997) Inexperienced users who lack in-depth domain knowledge, may find CBR more user- friendly since they have the ability to retrieve cases, whether or not the user has inputted all the necessary problem situation data (Watson, 1995; Wan, 1996) CBR systems are less expensive and time consuming to build than model or rule-based systems. It is claimed that RBR systems are around eight times more costly to build than CBR systems (Simoudis and Miller, 1991; Simoudis, 1992). This is because the cost of knowledge acquisition and knowledge-base validation is low Experts find it difficult to articulate the domain rules involved in their problem-solving, finding it easier to talk about their experiences, or tell stories that describe their experience. CBR is an approach that can support this form of case collection (Slator and Riesbeck, 1992) In CBR every new problem solved can be stored within the case-library thus enabling it to grow with the user and organization. It can also store both ‘successful’ and ‘unsuccessful’ cases which facilitates learning. RBR systems waste problem-solving interactions because there is no way for the experience to be stored (Leake, 1996; Slator and Riesbeck, 1992) Confidence in the advice given by CBR systems is higher than RBR or NN because the retrieved solutions are based on actual transparent cases. In RBR decisions are based on a chain of rules, which may have no meaning to the user. Also, if a RBR system provides incorrect solutions, it will do so until the chain of rules are corrected. Worst still in NN the solutions lack transparency completely (Riesbeck, 1988) The quality of solutions from CBR systems is higher than RBR systems because ‘cases reflect what really happens in a given set of circumstances’ (Leake, 1996). Furthermore, the latest up-to-date evidence or knowledge within a domain can be stored as cases even though it has not been formalized (Hunter, 1986)
- 42. and EST within a TQM context (see page 7). The SCF is further underpinned by the Malcolm Baldridge National Quality Award (NIST, 1997), the strategic and marketing concepts and processes as defined by Porter (1982; 1985), Johnson and Scholes (1997), Bhide (1994), Mintzberg (1994), Hamel and Prahalad (1994), and the strategic quality perspective as described by Garvin (1988) and Bounds et al. (1994). In addition the SCF was also validated using input from the project’s collaborators as referred to earlier. The structure of ESAS is based around the SCF and is modular in form to aid user consultation. In addition, the modular structure allows greater flexibility when searching for task specific problems. Thus quality improvement efforts can be prioritized and focused. The initial structure of ESAS consisted of two main task modules as described by the SCF. However, initial collaborator feed- back highlighted the need to broaden ESAS’s appeal by focusing on the market- led quality condition alluded to earlier. This enables users to search for specific case examples relating to market-led quality problems, but not to necessitate system redesign; rather selective case collection as directed by the MEA SCF task. In addition, a fourth module has been implemented to assist with general problem-solving sessions associated with novice users. These four domain task modules have been implemented to guide the search process during strategic quality problem-solving and decision-making as illustrated in Figure 1.3. Promoting a strategic approach to TQM 15 Strategic stance? Innovator, market leader/ follower etc. Plan for short med. and long term market expansion Sustain customer portfolio through cont. improvements Define enterprise mission and set goals, objectives Target customer, market niche and trend anticipation Competitor advantage analysis Assess capability and define resources, processes, systems to deliver goals and objectives Assess supplier capability to meet enterprise req's and work with suppliers to help them fit con't Assess impact on environment and stakeholders Identify competitive forces Political, social, economic and technological analysis Market supplier assessment Market Environmental Analysis Market requirement analysis present and future Assess market stability Competitive benchmarking and own market performance Enterprise Strategy ? ? ? Figure 1.2 ESAS scope and domain coverage – System Conceptual Framework (SCF). Source: adapted from Frangou, 1997.
- 43. Case data analysis This SCF formed the basis of a case collection questionnaire that was used in both the interview process and the postal surveys. Collected case data was analysed using (1) the case analysis (Patton, 1990) approach as described by Bell and Hardiman (1989), and (2) the guidelines as described by Kolodoner (1993). Kolodoner (1993: 13) states ‘a case is a contextualized piece of know- ledge representing an experience that teaches a lesson fundamental to achieving the goals of the reasoner’, that has three main parts; a problem description, a solution and an outcome. In the context of this research, a case would have the following components: • Problem description: provides a problem situation assessment by describing the problem at hand – i.e. ‘We have experienced a drop in sales through increased competition. . .’, • Solution: describes the strategy taken to solve the problem, i.e. ‘To over- come this increase in competition we. . .’, • Outcome: describes the state of the world, after the solution has been imple- mented, i.e. ‘Our strategy was successful, we were able to reverse our loss in sales, and recover our market position. . .’. The above framework was applied to the case data, to elicit cases suitable for ESAS. An example stored case is presented in Figure 1.4. 16 Andreas J. Frangou New problem requirements Retrieval ESAS Retrieval Modules Mkt Env Analysis (MEA) Ent’ Strategy (ES) Market-Led Quality General ESAS Module Strategist Market intelligence Market and organisational constraints Adaptation Evaluation Repair Accept new case strategy Case-library a n d S t o r e S t r a t e g y Figure 1.3 ESAS structure. Source: adapted from Frangou et al., 1999.
- 44. Case-library development CBR falls within the symbolic paradigm of AI, in that it uses symbolic representations to derive inferences, where cases are used to represent domain knowledge in the form described in Figure 1.4. However, case representation within a system requires careful consideration, in that a cases’ structure must include the following: (1) some form of symbolic representation for computa- tional purposes (i.e. what the system uses to index, match and retrieve with), and (2) some form of user-orientated representation that is required by the user to reach their decision-making goal. ReMind addresses case representation issues in two ways. (1) for symbolic representation, it allows developers to generate symbol hierarchies which graphically represent the concepts, relations, facts and principles that define the problem domain (Sowa, 1984). This is used to under- pin the case representation and operationalize case indexing and retrieval. Figure 1.5 illustrates the symbol hierarchy which essentially represents gener- alizations and specializations within the problem domain, and defines issues that can influence the ability of an organization to create a competitive advantage through strategic quality (Frangou et al., 1999). In all, eleven main symbol classifications have been derived from the case data. These are all related to an organizations structure, capabilities, perform- ance and strategic options for strategic quality improvements, and includes the Promoting a strategic approach to TQM 17 Problem description Competitors have introduced a new product/service that has threatened our current business. We have subsequently lost ground in the market, because it is considered more positively by the market. This is because our competitor’s product uses new technology, which is perceived to be far superior to ours. Subsequently, our products are now perceived as ‘out- dated’, the result being that our position in the marketplace has been seriously damaged. Solution: Consumers have been attracted to the new product/service, because they perceive it to be ‘modern’ and thus superior.We embarked on a comparative advertising campaign to highlight the benefit of our product over the competitions. The aim of this campaign was to inform consumers of the benefits of our technology, so that its advantages are understood. Various mediums were used such as TV, trade magazines, newspapers, posters etc to raise the profile of both the product range and company. We were able to change the consumers’ perception of products available and their associated technology. Attention was placed on the quality and ease of use of our product in comparison to competitors. Outcome: The campaign was successful from a strategic aspect, in that it took our competitor by surprise.We were able to undermine current myths about the technologies used, by educating the consumer of the certain aspects of our product and the service that it delivers.Subsequently our company experienced a 50% increase in sales. Figure 1.4 Case describing an experience of ‘competitor threat’ via new product release. Source: adapted from Frangou, 1997.
- 45. following: business type, market environment description, measure of market performance, supplier performance, strategic stance, organizational structure, relative strategic time-scales, acceptable risk-level for strategic options, evalu- ation of strategic option, case source, and ESAS consultation mode (to prioritize case retrieval) (Frangou et al., 1999). (2) for user-orientated representation ReMind uses a form-like representation consisting of 42 case fields slots that define the various features that make up a case11 as shown in Figure 1.6. Case indexing and retrieval Case indexes are essentially important weightings that are applied to key fea- tures so that cases can be stored effectively within the case memory, and so that they can easily be retrieved when required. During nearest neighbour (NNR) case retrieval,12 a numerical evaluation function is used to search and find a best case match between the new problem case and a stored solved case. In practice, the user inputs a new problem case using the form-like case editor shown in Figure 1.6, by describing the case via the defined case features. The consultation process and thus case retrieval involves the assessment of similarity between the 18 Andreas J. Frangou Figure 1.5 Symbol hierarchy within ESAS. Source: adapted from Frangou et al., 1998.
- 46. new case and stored cases, by comparing the weighted case features in the new case to those of the case-memory, the scale of case match being determined by these weights. The product of retrieval is a presentation of the best matching cases ranked according to their match aggregate score (Frangou et al., 1999). Case adaptation, evaluation and repair One of the disadvantages of CBR is that retrieved cases very rarely provide an exact match to the new problem case. Case adaptation is a process which addresses this problem by allowing the user to make the necessary changes to the retrieved case so that it can fit the situation described within the new problem case. In practice, adaptation effects key ESAS case features associated with the business context of each problem. These include features that describe conditions or constraints that are associated with the type of industry in which the problem has arisen, or the range of business goals available or acceptable to the industry. In addition, these changes will also affect a retrieved case’s pro- posed solution and related features. These may include both symbolic or textual features that describe strategies for addressing the problem. For example, if ESAS’s response to a pharmaceutical problem relating to an increase in drug development was a retrieved case proposing a rapid product development Promoting a strategic approach to TQM 19 Figure 1.6 Form-like user oriented case representation. Source: adapted from Frangou, 1997.
- 47. strategy as in the PC market, some elements of the case may be unacceptable due to industry regulatory forces enforcing lengthy R&D life-cycles and clinical trials (Frangou et al., 1999). In this instance case features relating to time scales and new product testing will require modification. Case evaluation and repair is an iterative process which governs case adapta- tion to ensure that changes are legal or acceptable to the industry (see Figure 1.1). In the context of the pharmaceutical example above, evaluation will ensure that adaptations to proposed time scales and strategies for market testing are in line with current industry regulation. If they are not, further repairs to the case will be actioned and then evaluated until all the conditions of the new case are met, and the case accepted. System implementation of case adaptation, evaluation and repair is at present manual. This is due to the complexity of the application domain, the lack of any robust domain model, and the nature of strategic decision-making (which is intu- itive and judgmental in nature). Furthermore, as strategic quality planning is a high risk process performed by humans, it is advisable that case adaptation remain a manual process. In addition, leaving adaptation to users will both encourage system utilization and trust, and enhance the interactive problem and learning process that is a key feature of the system (Frangou et al., 1999). System evaluation Intelligent systems evaluation has generally taken the verification and validation (V&V) route. In principle V&V is concerned with system quality from the perspective of design specification and correctness (Sharma and Conrath, 1992). Its emergence as a technique has coincided with the growing complexities of AI systems. In particular V&V techniques are commonly used to determine the cor- rectness, completeness and consistency of inference rules that form the chains of reasoning within rule-based systems (Klein and Methlie, 1995). Critics of tradi- tional evaluation techniques argue that V&V is only part of the evaluation equation, as it ignores the function and role of intelligent systems in the decision-making environment (Hollnagel, 1989). Therefore, system quality must be concerned with more than just the quality of the decisions or advice its giving, or whether or not its knowledge-base is a faithful representation of the problem domain. Sharma and Conrath (1992) propose a social-technical model of system evalu- ation, in which a holistic view of ‘total quality’ is a key consideration. This approach provides the foundation for ESAS’s evaluation programme. Using a global definition of quality such as the British Standards BS4778 (1991), and the guidelines given by Sharma and Conrath (1992), a holistic approach was taken to identify key system performance criteria. These were described in terms of ‘fit’ (Curet and Jackson, 1995) and included the following (Frangou et al., 1999): • Task-fit: How well does the system support the task it is designed to support? Does the system provide clear, concise advice on the major task components? Is the system effective? 20 Andreas J. Frangou
- 48. • Domain-fit: Does the systems approach, range of cases in memory, or case vocabulary represent the problem domain effectively? • User-fit: Does the system support the type of decision-making and problem- solving tasks carried out by the target user? System-user interaction is the main focus, effective presentation of case information, ease of use, opera- tional and interface problems and issues etc. • Organizational-fit: How well does ESAS fit the target implementation environment? What about the technology’s acceptance, and confidence between its users and sponsors? What impact will the system have on train- ing and overall firm performance? ESAS was evaluated by senior managers from a variety of organizations representing healthcare, manufacturing, education, IT, and the judicial system. The above four evaluation criteria were used to generate a questionnaire that provided the basis of the test. The system evaluation procedure followed a ‘hands-on’ approach in an interactive interview setting using five evaluators13 (Frangou et al., 1999). The first stage of the evaluation centred mainly on the system’s ability to retrieve a ‘good’ or match cases given a randomly selected set of test cases. This test was based on Goodman’s (1989) 10/90 test that uses 10 per cent of the case-libraries as test cases. System performance was catego- rized as hits, misses or not-sure by evaluators. The systems ability to provide advice for a real world problem was also assessed using a known marketing strategy case-study.14 Analysis of the evaluation results The results of the systems evaluation for the four main criteria are displayed in Table 1.3. In addition, ESAS achieved the scores in Table 1.3 which represent critical measures for the following: Promoting a strategic approach to TQM 21 Table 1.3 Evaluation results for ESAS Main test criteria Percentage score ( per cent) Task-fit 72.2 Domain-fit 79.8 Organizational-fit 67 User-fit 70.2 Sub-test criteria Percentage score ( per cent) 10/90 test 60.3 Case-study test 76 Problem-solving capability 68.6 Teaching and learning capability 86.3 Total system performance score 71.4 per cent
- 49. • 10/90 and real world case-study retrieval tests, part of the task-fit criteria; • systems problem-solving and teaching and learning capabilities rating, part of the organizational-fit; • the systems ability to satisfy its main objectives and its potential business goals; • overall system performance. In general, feedback from evaluators indicated that the system’s case retrieval modules were performing well in the tests. However, the 10/90 score of 60.3 per cent indicates only an above average performance for case retrieval. Further analysis showed that evaluators had difficulty in assessing the degree of match in some cases, where 7.7 per cent of retrieved cases were categorized as ‘not- sure’. This was due to some cases lacking sufficient detail to make a full assess- ment.15 ESAS faired better in the real world case-study test scoring 76 per cent. The reason for this improvement in performance was the addition of company specific information in the test case, which made assessment of case match easier. As a tool designed to support both problem-solving and teaching and learning within organizations, ESAS scored 68.6 per cent and 86.3 per cent respectively. This result in one respect substantiates the view that a system designed to promote ‘good practice’ or encourage a change in behaviour is more acceptable than a system that prescribes finite solutions (see earlier). Conclusion and future research possibilities This chapter has attempted to highlight the potential of intelligent systems technology, notably case-based reasoning (CBR) in relation to business and stra- tegic quality applications. By reviewing the concept of case-based intelligent systems, and discussing the major development and evaluation issues in building ESAS, it is hoped that managers will be encouraged to consider the potential of such systems for supporting strategic business processes. ESAS’s principal aim is to challenge how organizations go about implement- ing quality improvements, by emphasizing the strategic significance of quality for competitive advantage. The system achieves this by engaging the user in a case-based consultation process, where they are presented with a range of real- world strategies that describe how a broad range of organizations have attempted to create an advantage through quality. This generic capability is crucial to the proactive and lateral approach prescribed by the ESAS concept. An example of this is the initial reluctance of one senior manager, who could not see the benefit of using case-based quality strategies originating from a different industry. However, through the consultation process, this evaluator was pre- sented with a case solution from a different industry that provided a good match to a current strategic quality problem in his/her organization. In addition, ESAS also stores both good and bad examples of practice (Frangou et al., 1999). This is an essential teaching and learning feature that benefits users in terms of 22 Andreas J. Frangou
- 50. professional and skill-base growth. Furthermore, in terms of organizational learning and knowledge management issues, case-based systems such as ESAS can help to ensure that valuable expertise is not lost, and is used effectively and efficiently company-wide for competitive leverage. In terms of performance, ESAS has produced positive results. Most evaluators found the system easy to use and efficient, and practical in its approach in sup- porting problem-solving and decision-making processes. But most of all, ESAS was able to encourage lateral thinking in problem-solving and decision-making, which is a fundamental objective of the system. Weaknesses were raised about the system’s interface, which is outdated and sometimes hindered case presenta- tion and system navigation. Also, in some instances stored cases lacked enough depth to provide detailed advice on certain problems. Evaluators also pointed out that the generic capabilities of the system, may cause some inexperienced users problems in terms of industry terminology – here a glossary of terms would help. Current efforts are being made to address the limitations highlighted by ESAS’s evaluation. Various CBR development shells such as KATE, ESTEEM, ART*Enterprise and KnowMan are readily available that enable both graphical user interface construction and multimedia integration. Redeveloping ESAS around these tools will go some way to rectify its current interface limitations, and improve its teaching and learning capabilities through the use of interactive multimedia. Efforts are also being made at increasing the depth of advice that cases provide. This includes storing more cases from the public domain, and the addition of more company/industry specific data. An emerging key theme from this research is the apparent lack of case-based intelligent systems applications in business and management. This is a point clearly made by ESAS’s evaluators, and in particular the potential of developing case-based intelligent systems for supporting a range of business processes. Such applications present great extensive opportunities for business and acade- mia, both in terms of competitive enhancement and contribution to knowledge (Frangou et al., 1999). Notes 1 A case-based intelligent system emulates human problem-solving via the uses of past case examples of problem-solving. The associated technology will be explained in detail later on in the chapter. 2 In terms of a reduction in customer complaints and increase in new customer orders. 3 These representations are symbolic in nature for computational purposes. Symbol and symbol structures can be construed as standing for various concepts and relation- ships within the problem domain (Jackson, 1990). 4 In rule-based reasoning (RBR) systems, knowledge is represented as a production system or a set of production rules. These rules take the form of condition-action pairs: ‘IF this condition occurs, THEN . . . will occur’ (Turban, 1993). RBR is AI’s traditional view of human cognition, which suggests that intelligent behaviour is generally rule-governed (Jackson, 1990) and is founded on Newell and Simon’s (1972) model of human cognition. 5 Model-based reasoning (MBR) is similar to CBR in that both techniques use large Promoting a strategic approach to TQM 23
- 51. chunks of knowledge to base decisions on, rather than reasoning from scratch as in RBR. They differ in the type of knowledge used during reasoning – in MBR casual models represent general domain knowledge, whereas CBR uses cases that represent specific knowledge (Kolodoner, 1993: 97). 6 Neural networks (NN) are based on a ‘connectionist’ theory which suggests a model of human behaviour based on the structure of the human brain (Kluytmans et al., 1993). A NN is a network of highly interconnected parallel processing elements called artificial neurons (or nodes), which simulate the neurons in the human brain (Mockler and Dologite, 1992; Freeman and Skapura, 1991). 7 This has obvious benefits for the knowledge engineer (KE) in that CBR overcomes the disadvantages associated with traditional knowledge acquisition such as the ‘the bottleneck’ of AI systems development which includes: the formulizing of rules within weak-theory domains, the difficulty of experts articulating rules governing problem-solving, validation and verification of the rule-base, and human expert time and access constraints. 8 A pilot survey of senior managers and specialists responsible for strategic quality who represented IT, process, manufacturing, computer, healthcare, finance, insur- ance, judicial and HE sectors was conducted to assess the suitability of a CBR approach. 9 However, this gap is minimized through adaptation. 10 In order for adaptation to work efficiently adaptation methods that are consistent with the domain have to be implemented. Both heuristics and commonsense techniques can be used for adaptation depending on the system being built. These issues will be explored further later. 11 To derive associated case features and domain symbols a combination of conceptual analysis (Sowa, 1984) and case analysis (Patton, 1990) was used. 12 Inductive retrieval (IR) is another technique that can be used within CBR. It involves the clustering of cases according to specified indexes. Clustering creates a hierarchi- cal structure in the form of a discrimination network. Cases that are similar to one another are clustered together to form a tree. Case retrieval is achieved by traversing across the tree and comparing the new case against those stored in the tree. This speeds up retrieval because unlike NNM, only those cases stored in the tree are matched against. IR is best suited to applications that use very large case-libraries and speed. However, because IR does not search the whole library important cases could be missed. This, together with the fact that speed is not an issue for ESAS, means that NNM is the most suitable technique. 13 Five evaluators were involved in the system testing – these specialists represented the following sectors: Judicial System, IT, NHS, Manufacturing and Higher Education. 14 A test case describing a real world situation was used to test ESAS’s ability to solve a strategic problem. This test case focused on a competitive battle between two companies producing bulldozers – Caterpillar and Komatsu, and the loss of competitive advantage. 15 To maintain confidentiality among case data sources, company names were not included in each case. References Althoff, K-D., Auriol, E., Barletta, R. and Manago, M. (1995) A Review of Industrial Case-Based Reasoning Tools. Oxford: AI Intelligence. American Quality Foundation and Ernst & Young (1991) International Quality Study: The Definitive Study of the Best International Quality Management Practices. Cleve- land, OH: Ernst & Young. Atkinson, P. (1990) Creating Culture Change: The Key to Successful Total Quality Man- agement. Bedford: IFS Publications. 24 Andreas J. Frangou
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- 56. Shotgun in hand, he'd spent a fair portion of yesterday tracking a bobcat on the snow. It was a proved fact that a man on foot cannot catch up with a bobcat that is also on foot. But it was not to be denied that all bobcats have a touch of moon madness. They knew when they were being tracked, but they also knew when the tracker ceased following, and that kindled a fire in their heads. As long as they were tracked they were comfortable in the knowledge that they had only to keep running. When the tracker stopped, it threw the bobcat's whole plan out of gear. They imagined all sorts of ambushes, and cunning traps, and finally they worked themselves into such a frenzy that they just had to come back along their own tracks and find out what was happening. It followed that the hunter had nothing to do except rile the bobcat into a lather and then sit down and wait. Harky had waited. But he must have done something wrong, or perhaps the bobcat he followed had not been sufficiently moonstruck. Though it had come back, it had not been so anxious to find Harky that it forgot everything else. Harky had glimpsed it across a gully, two hundred yards away and hopelessly beyond shotgun range. If only he had a rifle— He hadn't any, and the last time he'd sneaked Mun's out his father had caught him coming back with it. The hiding that followed—Mun used a hickory gad instead of the flat of his hand—was something a man wouldn't forget if he lived to be older than the rocks on Dewberry Knob. Harky lost himself in a beautiful dream. Walking along Willow Brook, he accidentally kicked and overturned a rock. Beneath it, shiny-bright as they had been the day the forgotten bandit buried them, was a whole sack full of gold pieces. At once Harky hurried into town and bought a rifle, not an old 38-55 like his father's but a sleek new bolt action with fancy carving on breech and forearm. When he brought it home, Mun asked, rather timidly, if he might use it. No, Pa, Harky heard himself saying. It's not that I care to slight you but this rifle is for a hunter like me.
- 57. The shining dream was shattered by Mun's, "You done, Harky?" Harky looked hastily up to see his father beside him. "Yes, Pa," he said. "Lemme see." Mun sat down beside Old Brindle and Harky sighed with relief. When Mun Mundee could not get the last squirt from a cow, it followed that the cow was indeed stripped. But Mun, conditioned by experience, never completely approved of anything Harky did. "We'll close up for the night," he said. Harky scooted out of the barn ahead of his father and gulped lungfuls of the softening wind. It seemed that a man could never get enough
- 58. of that kind of air. Mun closed and latched the barn door and Harky turned to him. "It's a thaw wind!" he said rapturously. "Yep." "Not the big thaw, though." "Nope." "Do you reckon," Harky asked, "it will fetch the coons out?" Mun deliberated. A subject as serious as coons called for deliberation. "I don't rightly know," he said finally. "I figger some will go on the prowl an' some won't." It was, Harky decided, a not unreasonable answer even though it lacked the elements of true drama. Harky gulped another lungful of air and almost, but not quite, loosed the reins of his own imagination. Even seasoned hunters did not argue coon lore with Mun Mundee, but on an evening such as this it was impossible to think in prosaic terms. They lingered near the barn and faced into the wind. Presently Harky stood there in body only. His spirit took him to Heaven. Heaven, as translated at the moment, was the summit of a mountain ten times as high as Dewberry Knob. From his lofty eminence, Harky looked at a great forest that stretched as far as his eyes could see. Each tree was hollow and each hollow contained a coon. As though every coon had received the same signal at the same time, all came out. There were more coons than a man could hunt if he hunted every night for the next thousand years. At exactly the right moment, this entrancing scene became perfection. Deep in the great forest, Precious Sue lifted her voice to announce that she had a coon up.
- 59. Harky made his way among the great trees toward the sound. He found Precious Sue doing her best to climb a sycamore so massive that ten men, holding each others' hands, could not come even close to encircling the trunk. When Harky shined his light into the tree he saw, not just a coon, but the king of coons. Sitting on a branch, staring down with eyes big as a locomotive's headlight, was Old Joe himself. The fancy faded, but Harky was left with no sense of frustration because fact replaced it. Somewhere out in the Creeping Hills—the aura that surrounded him considerably enhanced by the fact that no human being knew exactly where—Old Joe really was sleeping the winter away. Suppose that he really came prowling tonight? Suppose Precious Sue really did run him up that big sycamore in the wood lot? Suppose Harky really—? Harky could no longer be silent. "Pa," he asked, "how long has Old Joe been prowling these hills?" A man who would speak of coons must think before he spoke. For a full ninety seconds Mun did not answer. Then he said seriously: "A right smart time, Harky. There's them'll tell you that even if a coon don't get trapped, or shot, or dog kil't, or die no death 'fore his time, he'll live only about ten years anyhow. I reckon that may be so if you mean just ordinary coons. Old Joe, he ain't no ordinary coon. My grandpa hunted him, an' my pa, an' me, an' you've hunted him. Old Joe, he's jest about as much of a fixture in these hills as us Mundees." Harky pondered this information. When he went to school down at the Crossroads, which he did whenever he couldn't get out of it, he had acquired some education. But he had also acquired some disturbing information. Miss Cathby, who taught all eight grades, was a very earnest soul dedicated to the proposition that the children in her care must not grow up to wallow in the same morass of mingled ignorance and superstition that surrounded their fathers and mothers.
- 60. Miss Cathby had pointed out, and produced scientific statistics to prove, that the moon was nothing more than a satellite of the earth. As such, its influence over earth dwellers was strictly limited. The moon was responsible for tides and other things about which Miss Cathby had been very vague because she didn't know. But she did know that the moon could not affect birth, death, or destiny. Old Joe had been the subject of another of Miss Cathby's lectures. He was just a big coon, she said, though she mispronounced it "raccoon." It was absurd even to think that he had been living in the Creeping Hills forever. Old Joe's predecessor had also been just a big raccoon. Since Old Joe was mortal, and like all mortals must eventually pass to his everlasting reward, his successor would be in all probability the next biggest raccoon. Harky conceded that she had something to offer. But it also seemed that Mun had much on his side, and on the whole, Mun's conception of the real and earnest life was far more interesting than Miss Cathby's. She got her information from books that were all right but sort of small. Mun took his lore from the limitless woods. "How long have us Mundees been here?" Harky asked. "My grandpa, your great-grandpa, settled this very farm fifty-one years past come April nineteen," Mun said proudly. "Where did he come from?" "He never did say," Mun admitted. "Didn't nobody ask?" "'Twas thought best not to ask," Mun said. "Blast it, Harky! What's chewin' on you? Ain't it enough to know where your grandpa come from?" "Why—why yes." Confused for the moment, Harky went back to fundamentals. His great-grandfather had settled the Mundee farm fifty-one years ago.
- 61. He was thirteen. Thirteen from fifty-one left thirty-eight years that Mundees had lived on the farm before Harky was even born. Confusion gave way to mingled awe and pride. Old Joe was not the only tradition in the Creeping Hills. The Mundees were fully as famous and had as much right to call themselves old-timers. For that matter, so did Precious Sue. The last of a line of hounds brought to the Creeping Hills by Mun's grandfather, her breed was doomed unless Mun found a suitable mate for her. But better to let the breed die than to offer Precious Sue an unworthy mate. Mun said, "Reckon we'd best get in." "Yes, Pa." Side by side they started down the soggy path toward the house. Precious Sue left her bed on the porch and came to meet them. She was medium-sized, and her dark undercoat was dappled with bluish spots, or ticks. Shredded ears bore mute testimony to her many battles with coons. Though she ate prodigious meals, every slatted rib showed, her paunch was lean, and knobby hip bones thrust over her back. Outwardly, Precious Sue resembled nothing so much as an emaciated alligator. For all the coon hunters of the Creeping Hills cared she could have been an alligator, as long as she continued to perform with such consummate artistry on a coon's track. Though a casual observer might have deduced that Precious Sue had trouble just holding herself up, she had once disappeared for forty-eight hours. Mun finally found her under the same tree, and holding the same coon, that she must have run up two hours after starting. She was one of the very few hounds that had ever forced Old Joe to seek a refuge in his magic sycamore, and no hound could do more. Unfortunately, she lived under a curse. The only pup of what should have been an abundant litter, a bad enough thing if considered by itself, Precious Sue had been born on a wild night at the wrong time of the moon. Therefore, she had a streak of wildness that must
- 62. assert itself whenever the moon was dark. If she were run at such times, she must surely meet disaster. But as Precious Sue met and fell in beside them, Harky thought only of his dream. "Do you think Old Joe will prowl tonight?" he asked his father. "What you drivin' at, Harky?" "I was thinking Old Joe might prowl, and come here, and Sue will run him up that sycamore in the woodlot, and—" "Harky!" Mun thundered. "Heed what you say!" "Huh?" Harky asked bewilderedly. Mun shook a puzzled head. "I can't figger you, Harky. I can't figger you a'tall. This is the dark of the moon!" "I forgot," Harky said humbly. "I reckon you ain't allus at fault for what runs on in that head of yours." "Hadn't you ought to tie her up?" Harky questioned. "Sue can't abide ties and no coon'll come here tonight," Mun said decisively. "Least of all, Old Joe." "But if he does—" Harky began. "Harky!" Mun thundered. "He won't!" "Yes, Pa." Long after he was supposedly in bed, Harky stood before his open window listening to the song of the south wind. Sometimes he couldn't even figure himself. There'd been last fall, when they jumped the big buck out of Garson's slashing. Mun and Mellie Garson had taken its trail, but Harky had a feeling about that buck. He'd felt that it would head for the rhododendron thicket on Hoot Owl Ridge, and that in getting there it
- 63. would pass Split Rock. Harky went to sit on Split Rock. Not twenty minutes later, the buck passed beside him. It was an easy shot. Old Joe would not come tonight because Mun said he wouldn't. But Harky was unable to rid himself of a feeling that he would, and he was uneasy when he finally went to bed. He slept soundly, but Harky had never been able to figure his sleep either. Often he awakened with a feeling that something was due to happen, and it always did. When the wild geese flew north or south, or a thunder storm was due to break, Harky knew before he heard anything. This night he sat up in bed with a feeling that he would hear something very soon. He heard it, the muffled squawk of a hen. On a backwoods farm, at night, a squawking hen means just one thing. Harky jumped out of bed and padded to the door of his father's bedroom. "Pa." "What ya want?" "I heard a hen squawk." "Be right with ya." Harky was dressed and ready, with his shotgun in his hands, when Mun came into the kitchen. Mun lighted a lantern, took his own shotgun from its rack, and led the way to the chicken house. He knelt beside the little door by which the chickens left and entered and his muffled word ripped the air. "Look!" Harky looked. Seeming to begin and end at the little door, the biggest coon tracks in the world were plain in the soft snow. Ten thousand butterflies churned in his stomach. It was almost as though the whole thing were his fault. He said, "Old Joe."
- 64. Mun glanced queerly at his son, but he made no reply as he held his lantern so it lighted the tracks. Harky trotted behind his father and noted with miserable eyes where Sue's tracks joined Old Joe's. They came to the flood surging over Willow Brook, and just at the edge a whole section of ice had already caved in. Both sets of tracks ended there.
- 65. SUE After Mun and Harky entered the house, Precious Sue crawled into her nest on the porch. The nest was an upended wooden packing case with a door cut in front and a strip of horse blanket hanging over the door to keep the wind out. The nest was carpeted with other strips of discarded horse blanket. On cold nights, Sue shoved the dangling strip over the door aside with her nose, went all the way in, let the horse blanket drop, and cared little how the wind blew. Tonight, after due observance of the canine tradition that calls for turning around three times before lying down, she stuck her nose under the blanket, lifted it, and went to sleep with her body inside but her head out. Her blissful sigh just before she dozed off was her way of offering thanks for such a comfortable home. It was not for Sue to understand that in more ways than one the dog's life might well be the envy of many a human. She had never wondered why she'd been born or if life was worth living; she'd been born to hunt coons, and every coon hunter, whether biped or quadruped, found life eminently worth living. Though she often dreamed of her yesterdays, they were always pleasant dreams, and she never fretted about her tomorrows. Five seconds after she went to sleep, Sue was reliving one of her yesterdays. She was hot after a coon, a big old boar that was having a merry time raiding Mun Mundee's shocked corn until Sue rudely interrupted. The coon was a wanderer from far across the hills, and last night, with three hounds on his trail, he had wandered unusually fast. When
- 66. he finally came to Mun's corn, he was hungry enough to throw caution to the winds. And he knew nothing about Precious Sue. He did know how to react when she burst upon him suddenly. Running as though he had nothing on his mind except the distance he might put between Sue and himself, the coon shifted abruptly from full flight to full stop. It was a new maneuver to Sue. She jumped clear over the coon and rolled three times before she was able to recover. By the time she was ready to resume battle, the coon was making fast tracks toward a little pond near the cornfield. With a six-foot lead on Sue, he jumped into the pond. When Sue promptly jumped in behind him, the coon executed a time-hallowed maneuver, sacred to all experienced coons that are able to entice dogs into the water. He swam to and sat on Sue's head. Amateur hounds, and some that were not amateurs, nearly always drowned when the battle took this turn, but to Sue it was kindergarten stuff. Rather than struggle to surface for a breath of air, she yielded and let herself sink. The coon, no doubt congratulating himself on an absurdly easy victory, let go. Sue came up beneath him, nudged him with her nose to lift him clear of the water, clamped her jaws on his neck, and marked another star on her private scoreboard. Of such heady stuff were her dreams made, and dreams sustained her throughout the long winter, spring, and summer, when as a rule she did not hunt. She could have hunted. There were bears, foxes, bobcats, and a variety of other game animals in the Creeping Hills. All were beneath the notice of a born coon hound who knew as much about coons as any mortal creature can and who didn't want to know anything else. The squawking chicken brought her instantly awake. The wind was blowing from the house toward Willow Brook, so that she could get no scent. But she pin-pointed the sound, and she'd heard too many
- 67. chickens squawk in the night not to know exactly what they meant. Seconds later she was on Old Joe's trail. She knew the scent, for she had been actively hunting for the past five years and had run Old Joe an average of six times a year. But she saw him in a different light from the glow in which he was bathed by Mun and Harky Mundee. To them he was part coon and part legend. To Sue, though he was the biggest, craftiest, and most dangerous she had ever trailed, he was all coon and it was a point of honor to run him up a tree. When she came to Willow Brook, she saw the flood surging over the ice and recognized it for the hazard it was. But except when they climbed trees or went to earth in dens too small for her to enter, Sue had never hesitated to follow where any coon led. She jumped in behind Old Joe, and fate, in the form of the south wind, decided to play a prank. Ice over which Old Joe had passed safely a couple of seconds before cracked beneath Sue. The snarling current broke the one big piece into four smaller cakes and one of them, rising on end, fell to scrape the side of Sue's head. Had it landed squarely it would have killed her. Glancing, it left her dazed, but not so dazed that she was bereft of all wit. Sue had swum too many creeks and ponds, and fought too many coons in the water, not to know exactly how to handle herself there. Impulse bade her surrender to the not at all unpleasant half dream in which she found herself. Instinct made her fight on. Swept against unbroken ice, she hooked both front paws over it. Then she scraped with her hind paws and, exerting an effort born of desperation, fought her way back to the overflow surging on top of the ice. Once there, still dazed and exhausted by the battle to save herself, she could do nothing except keep her head above flood water that carried her more than two miles downstream and finally cast her up on the bank.
- 68. For an hour and a half, too weak even to stand, Sue lay where the water had left her. Then, warned by half-heard but fully sensed rumblings and grindings, she alternately walked and crawled a hundred yards farther back into the forest and collapsed at the base of a giant pine. With morning she felt better. Still shaky, but able to walk, she stood and remembered. Last night Old Joe had come raiding. She had followed him to Willow Brook and lost the trail there, thus leaving unfinished business that by everything a coon hound knew must be finished. Sue returned to Willow Brook and sat perplexedly down with her tail curled about her rear legs. During the night, while she slept, the ice had gone out as she'd been warned by its first rumblings. She had heard nothing else, but she saw ice cakes that weighed from a few pounds to a few tons thrown far up on either bank. The moving ice had jammed a half mile downstream, and in effect had created a temporary but massive dam. Harky Mundee could toss a stone across Willow Brook's widest pool in summer, but a beaver would think twice before trying to swim it now. With some idea that she had been carried downstream, Sue put her nose to the ground and sniffed hopefully for five hundred yards upstream. It was no use. Everything that normally had business along Willow Brook had fled from the breaking ice. Sue had no idea as to how she would find Old Joe's trail or even what she should do next. She whined lonesomely. Old Joe had eluded her again, which was no special disgrace because there'd always be a next time. Since she could not hunt, it would be ideal if she could return to the Mundee farm, but she was afraid to try swimming the flood. Nosing about, Sue found a two-pound brown trout that had been caught and crushed in the grinding ice and cast up on the bank. She ate the fish, and with food her strength returned. With strength came a return of hound philosophy.
- 69. Since there was little point in fighting the unbeatable, and because flooded Willow Brook held no charms, Sue wandered back into the forest. Ordinarily she would have stayed there, eating whatever she could find and returning to the Mundee farm after the flood subsided. But again fate, or nature, or whatever it may be that plays with the lives of human beings and coon hounds, saw fit to intervene. Sue had been born to hunt coons and she was dedicated to her birthright, but the All-Wise Being who put the moon in the sky did so in the interests of all romance. Sue yearned to meet a handsome boy friend. To conceive a notion was to execute it, and Sue began her search. She had often hunted this area. For miles in any direction, on the far side of Willow Brook, was wilderness. She did not know of any farmer, or even any trapper, who might have a dog. But she had a sublime faith that if only she kept going, she would find her heart's desire. Three days later, after passing up three farms that unfortunately were staffed with lady dogs, Sue approached a fourth. It was little better than a wilderness clearing, with a tiny barn, a couple of sheds, and a one-room house. But Sue was not interested in the elite side of human living, and the great black and tan hound that came roaring toward her was handsome enough to make any girl's heart miss a beat.
- 70. Sue waited coyly, for though to all outward appearances the huge hound was intent only on tearing her to pieces, she knew when she was being courted. They met, touched noses, wagged tails, and Sue became aware of the man who appeared on the scene. He was a young man built on the same general proportions as a Percheron stallion, and he hadn't had a haircut for about six months or a shave for at least three years. But he knew a good hound when he saw one and he had long since mastered the art of putting hounds at ease. His voice was laden with magic when he called, "Here, girl. Come on, girl. Come on over." Because she was hungry, and saw nothing to distrust in the shaggy young giant, but largely because the great black and tan hound
- 71. paced amiably beside her, Sue obeyed. She buried her nose in the dish of food the young man offered her and started gobbling it up. So wholeheartedly did Sue give herself to satisfying her hunger that the rope was about her neck and she was tied before she was even aware of what had happened. Paying not the least attention to the big bluebottle fly that buzzed her nose, Sue stretched full-length and dozed in the sun. Trees that had been bare when she came to Rafe Bradley's were full-leafed. Flowers bloomed beneath them. Birds had long since ceased chirping threats to each other and had settled down to the serious business of building nests and raising families. First impressions of Rafe Bradley's farm were more than borne out by subsequent developments. Rafe kept a good horse, but it was for riding rather than plowing. Besides the horse, Rafe's domestic livestock consisted of some pigs that ran wild in the woods until Rafe wanted pork, which he collected with his rifle. Rafe, his horse, and his big hound had left early this morning to take care of some important business in the woods. Since Rafe's only important business was hunting something or other, it followed that he was hunting now. Sue raised her head and blinked at the green border around the clearing. Mun Mundee had told Harky that Sue could not abide a rope, and she couldn't. But the rope was there, it had not been off since the day Rafe put it there, and Sue could choose between giving herself a permanently sore neck by fighting the rope and submitting. She did what a sensible hound would do. If Rafe had not tied her, his big hound would have been sufficient attraction to keep her around for at least a few days. After that, she
- 72. might have fallen in with life as it was lived at Rafe's and been happy to remain. Rafe had tied her, and for that he could not be forgiven. Sue lived for the day she would be free to return to Mun Mundee. With an abiding faith that everything would turn out for the best if only she was patient, Sue was sure that day would come. Until it did, she might as well sleep. The bluebottle fly, tiring of its futile efforts to annoy her, buzzed importantly off in search of a more responsive victim. Sue opened one bloodshot eye then closed it again. She sighed comfortably, went back to sleep, and was shortly enjoying a happy dream about another coon hunt. When the sun reached its peak she rose, lapped a drink from the dish of water Rafe had left for her, and sought the shade of her kennel. Rafe would return with evening. She would be fed, sleep in her kennel, and tomorrow would be another day. Rafe did not come with twilight. The rope trailing beside her like a rustling worm, Sue came out of her kennel and whined. She was not lonesome for Rafe, but she was hungry. Sue paced anxiously for as far as the rope would let her go. Whippoorwills, flitting among the trees at the borders of the clearing, began their nightly calling. She lapped another drink and resumed her hungry pacing. Then, just before early evening became black night, the whippoorwills stopped calling. A moment later it became apparent that someone was coming. Their arrival was heralded by an unearthly clatter and rattling that puzzled Sue until they entered the clearing. Then she saw that they were two men in a car, a marvelous vehicle held together with hay wire and composed of so many different parts of so many different cars that even an expert would have had difficulty determining the original make. The car quivered to a halt and one of the two men bellowed at the dark house,
- 73. "Rafe! Hey, Rafe! Whar the blazes be ya, Rafe?" There was a short silence. The second man broke it with a plaintive, "Kin ya tie that? First night in two years coons raid our ducks, Rafe an' that hound of his gotta be chasin'!" "He would," the first man growled. The second's roving eye lighted on the kennel and then noticed Sue. "Thar's another hound." "Ya don't know," the first said, "that it'll hunt coons." The second declared, "If it's Rafe's, it'll hunt coons. I'm goin' to git it." "Keerful," the first man warned. "That Major hound'll take the arm off anybody 'cept Rafe what tries to touch it." "Le's see what this'n does." The second man left the hybrid car and approached Sue, who waited with appeasing eyes and gently wagging tail. When the man laid his hand on her head, Sue licked his fingers. "Tame's a kitten," the man declared jubilantly. "I'll fetch her." He untied the rope, and the instant she was free, Sue slipped aside and raced toward the woods. Not in the least affected by the anguished, "Here, doggie! Come on back, doggie!" that rose behind her, she entered the forest at exactly the same point she'd left it to meet Rafe Bradley's hound. The cries faded and only the whisper of the wind kept her company as Sue traveled on. Suddenly there was a great need that had not existed before to put distance between herself and Rafe Bradley's clearing. Sue traveled until near morning, then crawled gratefully beneath the thick branches of a wind-toppled pine. She turned around and around to smooth a bed.
- 74. The sun was just rising when her pup was born. Almost five months after she left it, Precious Sue came once again into her own land. Where she had once been gaunt, she was now little more than a skeleton. But the pup that frisked beside her, and was marked exactly like her, was fat and healthy enough. There just hadn't been enough food for two. Precious Sue fell, and the pup came prancing to leap upon her, seize her ear, and pull backwards while it voiced playful growls. Sue got up. Head low, staggering, she labored over a fallen sapling that the pup leaped easily. She reached the top of the hill she was trying to climb. From the summit, she saw Willow Brook sparkling like a silver ribbon in the sunshine. Just beyond were the buildings of the Mundee farm. Sue sighed happily, almost ecstatically, and lay down a second time. She did not get up.
- 75. HARKY GOES FISHING When Mun sent him out to hoe corn, Harky knew better than to protest or evade. An outright refusal would instantly bring the flat of Mun's hand against the nearest part of Harky's anatomy that happened to be in reach. Evasion would rouse Mun's suspicions, and like as not bring a surveillance so close that Harky would find escape impossible. Campaigns must be planned. When Mun said, "You go hoe the corn," Harky answered meekly, "Yes, Pa," and he did his best to seem enthusiastic as he shouldered the hoe and strode off toward the cornfield. The field was a full three hundred yards from the house, and if one were fleet enough of foot, one might throw one's hoe down the instant one arrived and simply start running. Harky had long ago learned the futility of such tactics. Mun was winded like a bear, gifted with the speed of a greyhound, and he knew all the hiding places Harky might be able to reach if all he had was a three-hundred-yard start. He knew some that were even farther away. When it came to finding his son, Harky sometimes believed, Mun had a nose fully as keen as Precious Sue's when she was sniffing out a coon. Sue provided an interesting diversion of thought as Harky marched manfully toward the cornfield. Neither she nor Old Joe had been seen since that fateful night in February, and though of course Old Joe seemed to be immortal, available evidence indicated that Sue had been swept under the ice and drowned in Willow Brook. It could be, but Harky had a feeling about Sue. She couldn't have been more than a couple of jumps behind when Old Joe jumped into
- 76. Willow Brook, and if one had escaped, why hadn't both? Though there was always a possibility that the ice had held for Old Joe and broken for Sue, in Harky's opinion, the current where the ice broke should not have been too strong for a swimmer of Sue's talent. Naturally the catastrophe had not gone unchallenged. Except for essential tasks, farm work ended the day after Sue disappeared. As Mun explained it, a body could always get more cows or pigs, or even another farm. But there was only one coon hound like Precious Sue. Mun was not unduly optimistic when he began the search, for after all Sue had run in the dark of the moon. But the fact that Sue was doomed by the gods did not prevent Mun's pressing the hunt with utmost vigor. Mun and Harky traveled up Willow Brook and down, visiting every neighbor for nine miles in one direction and eleven in the other. Mellie Garson hadn't seen Sue. Though Mellie had not seen her, he recognized a genuine emergency and joined the hunt for her. So did Raw Stanfield, Butt Johnson, Bear Pen Crawford, Pine Heglin, and Mule Domster. After two weeks it was sadly concluded that Precious Sue had indeed placed herself beyond hope of redemption when she took after Old Joe in the dark of the moon. The searchers gathered in Mun Mundee's kitchen, decided that Sue's mortal remains would come to rest an undetermined number of miles down Willow Brook, since it was impossible to tell where the breakup would carry her, and they drank a solemn toast to the memory of a great coon hound. And Harky still had a feeling. He reached the cornfield, and, as though his heart were really in it, started hoeing at the right place. The right place, naturally, was the side nearest the house. Mun Mundee would have reason to wonder if Harky evinced too much interest in starting near the woods. As he began the first row, which was thirty yards long when one was not hoeing it and thirty miles when one was, Harky mentally reviewed his caches of fishing tackle.
- 77. Upstream, thirty steps north, eight east, and ten south from a round rock above the first riffle, which in turn was above the first pool where a snapping turtle with a pockmarked shell lived, a line and three hooks were hidden in a hollow stump. Downstream, on a straight line between the pool where Precious Sue had jumped an almost black coon and the white birch in which she'd bayed it, a line and two hooks were concealed in last year's nest of a song sparrow. Harky worried about that cache. It had been all right two days ago because he'd seen it, and most birds had already nested. But some would nest a second time, and the ruins of this old nest might be summarily appropriated for a new one. His line would disappear, too, and like as not his hooks. Birds were not particular as long as they had something to hold their nest together. As soon as he found another place not likely to attract Mun's eye, perhaps he'd better move his tackle from the nest. Good hooks and line were not so easy come by that a man could get reckless with them. Leaning slightly forward, the position in which Mun thought the wielder of a hoe would do most work, and slanting his hoe at the angle Mun favored, Harky sighed resignedly as the blade uncovered a fat and wriggling earthworm. He did not dare pick it up and put it in his pocket—Harky had never seen the need of bait containers—for there were times when Mun seemed to have as many eyes as a centipede had legs, and an eagle's sight in all of them. If he saw Harky put anything in his pocket—and he would see—he'd be present on the double. Well, there were plenty of worms to be had by probing in moist earth near pools and sloughs. The trouble with them was that they were accustomed to water, and they did not wriggle much when draped on a hook and lowered into it. Garden worms, on the other hand, were so shocked by an unfamiliar environment that they wriggled furiously and attracted bigger fish. The sun grew hot on Harky's back, but his body was too young, too lithe, and too well-conditioned, to rebel at this relatively light labor.
- 78. His soul ached. Of all the vegetables calculated to bedevil human beings, he decided, growing corn was the worst. He tried to find solace by thinking of the good features of corn, and happily alighted on the fact that it attracts coons. Also, it tasted good when stripped milky from the stalk and either boiled or roasted. However, the coons would come anyhow. If there was no corn, they'd still be attracted by the apples in Mun's orchard. And if the Mundees had no corn, neighbors who did would be glad to share with them. Meanwhile, this patch must be hoed a few million times. Harky pondered a question that has bemused all great philosophers: how can humans be so foolish? Working at that rhythmic speed which Mun considered ideal for hoeing corn, missing not a single stroke, Harky went on. Discontent became anguish, and anguish mounted to torture, but Harky knew that the wrong move now might very well be ruinous. Like all people with great plans and strong opposition, he must suffer before he gained his ends. But he'd suffer only half as much if the master strategy he'd worked out did not fail him. Exactly halfway across the first row, Harky turned and started back on the second. It was a bold move, and Harky's heart began to flutter the instant he made it, but the situation called for bold moves. Harky did not break the rhythm of his hoeing or look up when he heard Mun approach, and he managed to look convincingly astonished when Mun asked, "What ya up to, Harky?" Harky glanced up quickly. "Oh. Hello, Pa!" "I said," Mun repeated, "what ya up to?" "Why—What do ya mean, Pa?" "You know blasted well what I mean," Mun growled. "You didn't do but half the first row."
- 79. "Oh," Harky might have been a patient teacher instructing a backward pupil. He gestured toward tall trees that, in a couple of hours, would keep the sun from the far half of the corn patch. "The sun, Pa. It's high and warm now, but it'll be high and hot time I get this first half done. Then I can work in shade." Mun scowled, suspecting a trick and reasonably sure there was one, but unable to fly in the face of such clear-cut logic. If he thought of it, he conceded, he'd plan to hoe the corn that way himself. As he turned on his heel and started walking away, he flung another warning over his shoulder. "I hope ya don't aim to scoot off an' go fishin'." "Oh no, Pa!" Suddenly, because he'd have to hoe only half the corn patch, Harky's burdens became half as heavy. It had worked, as he'd hoped it would, and the most tangled knot in his path was now smooth string. Of course he was not yet clear. But even Mun could not watch him constantly, and once he was near enough the woods to duck into them, Harky would be satisfied with a ninety-second start. Two hours later, having hoed his way to the edge of the woods, Harky dropped his hoe and started running. When Mun Mundee would shortly be on one's trail one must ignore nothing, and all this had been planned, too. Harky took the nearest route to Willow Brook. So far so good, but strictly amateur stuff. Mun, who'd need no blueprint to tell him where Harky had gone, would also take the shortest path to Willow Brook. Harky put his master strategy into effect. Coming to a patch of mud on the downstream side of a drying slough, Harky ran straight across it the while he headed upstream. He emerged on a patch of new grass that held no tracks, leaped sideways to a boulder, and hop-skipped across Willow Brook on
- 80. exposed boulders. Reaching the far side, he ran far enough into the forest to be hidden by foliage and headed downstream. With the comfortable feeling of achievement that always attends a job well done, Harky slowed to a walk. Mun, hot in pursuit and even more hot in the head, would see the tracks leading upstream. Thereafter, for at least a reasonable time, he would stop to think of nothing else. By the time he did, and searched all the upstream hiding places, Harky would be a couple of miles down. He knew of several pools that had their full quota of fish, and that were so situated that a man could lie behind willows, fish, and see a full quarter of a mile upstream the while he remained unseen. His heart light and his soul at peace, Harky almost started to whistle. He thought better of it. Mun Mundee never had mastered the printed word. But his eyes were geared to tracks and his ears to the faintest noises. If Harky whistled, he might find his fishing suddenly and rudely interrupted. The softest-footed bobcat had nothing on Mun when it came to silent stalks. More than once, when Harky thought his father was fuming at home, Mun had risen up beside him and applied the flat of his hand where it did the most good. Harky contented himself with dancing along, and he never thought of the reckoning that must be when he returned home tonight, because in the first place tonight was a long ways off. In the second, there were always reckonings of one sort or another. A man just had to take care he got his reckoning's worth. Harky halted and stood motionless as any boulder on Dewberry Knob. A doe with twin fawns, and none of the three even suspecting that they were being watched, moved delicately ahead of him. Harky frowned. It was a mighty puzzling thing about deer, and indeed, about all wild creatures. Except for very young poultry, a man could tell at a glance whether most farm animals were boys or girls, and that was that. He
- 81. could never be sure about wild ones, largely because he could never come near enough, and there might be something in Mellie Garson's theory that the young of all wild creatures were alike, a sort of neuter gender, until they were six months old. Then they talked it over among themselves and decided which were to be males and which females. Thus they always struck a proper balance. It was a sensible system if Mellie were correct, though Harky was by no means sure that he was. Neither could he be certain Mellie was wrong, and as the doe and her babies moved out of sight, Harky wondered what sex the two fawns would choose for themselves when they were old enough to decide. Two does maybe, or perhaps two bucks, though it would be better if one were a doe and the other a buck. Both were needed, and the Creeping Hills without deer would be nearly as barren as they would without coons. When the doe and her babies were far enough away so that there was no chance of frightening them—a man never would get in rifleshot of a buck if he scared it while it was still a fawn—Harky went on down the creek. He stopped to watch a redheaded woodpecker rattling against a dead pine stub. He frowned. The next job Mun had slated for him was putting new shingles on the chicken house, and the woodpecker's rattling was painfully similar to a pounding hammer moving at about the same speed that Mun would expect Harky to maintain. Obviously finding something it did not like, the woodpecker stopped rattling, voiced a strident cry, and flew away. It was a bad omen, and Harky's frown deepened. He'd seen himself in the woodpecker. Just as the bird had come to grief, so Harky was sure to meet misfortune if he tried shingling the chicken house. He'd have to think his way out of that chore, too. But the shingling was still far in the future, and the only future worth considering was embodied in what happened between now and sundown. Troubles could be met when they occurred.
- 82. When Harky was opposite the pool where Precious Sue had jumped the almost black coon, he turned at right angles. It was scarcely discreet to go all the way and show one's self at the edge of Willow Brook, for though Mun should have been lured upstream, he might have changed his mind and come down. As soon as he could see the pool through the willows that bordered it, Harky turned and sighted on the white birch in which Sue had finally treed the coon. He was about to start toward it but remained rooted. Suddenly he heard Precious Sue growl. Not daring to believe, but unwilling to doubt his own ears, Harky turned back to the pool. He peered through the willows and saw the pup.
- 83. DUCKFOOT By some mischance, one of the willows bordering the pool grew at a freakish angle. A two-pound sucker, probably coon-mauled or osprey- dropped somewhere upstream, had washed down and anchored beneath the misshapen tree. Its white belly was startlingly plain in the clear water. When Harky came on the scene, the pup was trying to get that sucker. Harky almost called, certain that he had finally found Precious Sue. Then he knew his error. The pup was marked exactly like Sue, and at first glance it seemed exactly the size of Sue. But though it was big for its age, and was further magnified by the water in which it swam, undoubtedly it was a puppy. Since wild horses couldn't have torn him away, Harky stayed where he was and watched. The pup couldn't possibly have scented the fish, for the water would kill scent. Therefore he must have seen it and known what he was looking at. Now, despite a certain awkwardness that was to be expected in a pup, he seemed as comfortably at home in the water as Old Joe was in Mun Mundee's chicken house. He made a little circle, head cocked to one side so that he might peer downward as he swam. For a moment he held still, paws moving just enough to keep him from drifting in the gentle current. Then he dived. Smooth as a fishing loon, the pup went down headfirst and straight to his objective. Reaching the anchored sucker, he swiped at it with a front paw. The sucker did not move. The pup, who did not seem to know that he was where no dog should be and trying what no dog
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