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E-raamat: Optimal Enterprise: Structures, Processes and Mathematics of Knowledge, Technology and Human Capital [Taylor & Francis e-raamat]

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In the modern world, most gross product is created within Enterprise firms, project programs, state agencies, transnational corporations and their divisions, as well as various associations and compositions of the above entities. Enterprises, being, on the one hand, complex, and, on the other hand, widespread systems, are the subject matter of cybernetics, system theory, operations research, management sciences and many other fields of knowledge.

However, the complexity of the system obstructs the development of mathematically rigorous foundations for Enterprise control. Moreover, methods of operations research and related sciences, which are widely used in practice, provide optimization of the constituents of an Enterprise, without modeling it as a whole system. But the optimization of parts does not lead to the optimality of the whole, and, also, the absence of top-down and holistic mathematical models of Enterprise contradicts the principle of holism and the system approach.

The approach in this book looks first at Enterprise Systems and their essential aspects as complex sociotechnical systems composed of integrated sets of structural and process models (Chapters 1 and 2). A uniform description of all the heterogeneous fields of the modern Enterprise (marketing, sales, manufacturing, HR, finance, etc.) is then made, and the Enterprise Control Problem is posed as a top-down and holistic mathematical optimization problem (Chapter 3). Original models and methods of contract theory (Chapter 4), technology management (Chapter 5), human behavior and human capital (Chapter 6) and complex activity and resource planning (Chapter 7) are developed to solve the problem. Structural processes and mathematical models constitute an Optimal Enterprise Control Framework (Chapter 8) that provides a practical solution to the Enterprise Control Problem.

This book is a resource for postgraduate and doctoral students, postdoctoral researchers and professors with research interests in the following fields of science:











Fundamental Complex Systems study, Complex Systems Engineering, Enterprise Systems Engineering





Applications of Operations Research, Optimization, Probability and Stochastic processes to Management Science, Economics and Business





Theory of the Firm





Business and Management general, strategy/leadership, organization management, operations management and management information systems





Theory of Business Processes, Business Processes Improvement and Reengineering
Foreword xi
Basic Notation and Abbreviations xvii
Definitions xix
Part I Methodology: Foundations of Enterprise Control
Chapter 1 Enterprise and Complex Activity: Qualitative Models
3(40)
1.1 Introduction
3(11)
1.1.1 Complex Activity and an Actor: an Enterprise
4(3)
1.1.2 Management of Enterprise and Its Complex Activity
7(4)
1.1.3 Related Disciplines and Knowledge Domains
11(3)
1.2 Structural Models of Complex Activity and Enterprise
14(6)
1.2.1 Structural Element of Activity
14(2)
1.2.2 Logical Structure of Complex Activity
16(2)
1.2.3 Cause-Effect Structure of Complex Activity
18(2)
1.3 Uncertainty and Creation of Elements of Complex Activity
20(4)
1.4 Lifecycles of Complex Activity
24(3)
1.4.1 Conceptualization of the Lifecycle of Complex Activity
24(3)
1.4.2 The Process Model (Model of the Lifecycle of Complex Activity)
27(1)
1.5 Implementation of the Management Processes
27(8)
1.5.1 A Methodological Analysis of the Category of Management
27(6)
1.5.2 Enterprise Complex Activity as an Aggregate of Lifecycles of SEAS
33(2)
Conclusion
35
References
34(9)
Chapter 2 Enterprise Management and Lifecycles Compatibility
43(28)
2.1 A Sociotechnical System, Complex Activity, and Purposefulness
43(2)
2.2 Subject Matter of Enterprise Management
45(6)
2.3 Means of and Factors Involved in Enterprise Management
51(6)
2.4 Ordering of Management Actions along the Lifecycle of Complex Activity
57(4)
2.5 Compatibility of Complex Activity Lifecycles
61(4)
Conclusion
65(2)
References
67(4)
Part II Mathematics: Mathematical Models and Methods of Enterprise Control
Chapter 3 Enterprise Control Problem: The Statement
71(48)
3.1 Concept of Optimization
72(3)
3.2 Enterprise Control Problem: Qualitative Model
75(5)
3.2.1 Controlled Entity
75(2)
3.2.2 Control Means
77(1)
3.2.3 Uncertainty
78(1)
3.2.4 Objective Function and Constraints
79(1)
3.2.5 Brief
79(1)
3.3 Enterprise Control Problem among Related Knowledge Domains
80(13)
3.3.1 "Epistemologically Weak" and "Strong" Sciences and the Enterprise Control Problem
80(3)
3.3.2 Enterprise Control Problem and Theory of Control in Organizations
83(7)
3.3.3 Enterprise Control Problem and Mathematical Models in Related Disciplines
90(3)
3.3.3.1 Operations research
90(1)
3.3.3.2 Models of structures and processes
91(2)
3.4 Enterprise Control Problem as an Optimization Problem
93(22)
3.4.1 Formal Description of a Structural Element of Activity as a Dynamic Active System
94(3)
3.4.2 Game of Agents in a Dynamic Active System
97(2)
3.4.3 Optimal Control of the Structural Element of Activity: a Dynamic Active System
99(3)
3.4.4 Optimal Control of an Enterprise: a Hierarchical Dynamic Active System
102(8)
3.4.5 Enterprise Control Optimization Scheme
110(5)
Conclusion
115(1)
References
116(3)
Chapter 4 Contracts
119(32)
4.1 Static Principal-Agent Models
119(11)
4.1.1 Deterministic Case
119(3)
4.1.1.1 Deterministic case
121(1)
4.1.1.2 Full awareness of the principal and agent
122(1)
4.1.2 Interval Model of Uncertainty
122(1)
4.1.3 Additive Probabilistic Model of Uncertainty
123(6)
4.1.4 "Simple" Agent (Probabilistic Model of Uncertainty)
129(1)
4.2 Static Multi-Agent Models
130(7)
4.2.1 Multiple Agents and Additive Probabilistic Model of Uncertainty
130(2)
4.2.2 Incentive Problem in an "Extended Enterprise"
132(5)
4.3 Dynamic Multi-Agent models
137(11)
4.3.1 Contracts in Dynamic System with One Principal and Multiple Agents
137(5)
4.3.2 Contracts in Dynamic Hierarchical Multi-Agent Active System
142(6)
Conclusion
148(1)
References
149(2)
Chapter 5 Technology
151(42)
5.1 Technology Management Problem
151(4)
5.2 Known Models and Methods in Related Scientific Domains
155(3)
5.3 Technology Evolution and Management
158(10)
5.3.1 Core Properties of the Basic Model of the Technology Evolution Process
158(3)
5.3.2 Approximations of Maturity/Learning Curve
161(2)
5.3.3 Expected Maturity/Learning Time
163(4)
5.3.4 Extension of the Basic Model of the Technology Evolution Process
167(1)
5.4 Integration of Technology Components
168(10)
5.4.1 Parallel and Sequential Maturing/Learning
169(2)
5.4.2 Complex Integration: "Learning to Learn"
171(7)
5.5 Technology in an External Environment
178(7)
5.5.1 "Standard Solutions" and Optimal Technology Management
178(6)
5.5.2 Entropy
184(1)
Conclusion
185(1)
Appendices
186(3)
Appendix 5.1 Expected time to reach the "absolute" maturity/learning level
186(3)
Appendix 5.2 Proof of Proposition 5.4 and Corollary 5.1
189(1)
Proof of Proposition 5.4
189(1)
Proof of Corollary 5.1
190(1)
References
190(3)
Chapter 6 Human Capital
193(32)
6.1 Problem of Human Capital Management
194(6)
6.1.1 Requirements to the Model of Human Capital of an Enterprise
194(4)
6.1.2 Known Approaches and Models of Human Capital
198(2)
6.2 Pools of Active Resources as a Formal Representation of Human Capital
200(5)
6.2.1 Basic Model of Pool of Active Resources
200(4)
6.2.2 The Human Capital Effect on Enterprise Output
204(1)
6.3 Statistics of the Active Resource Traffic
205(7)
6.3.1 Nonparametric Statistics of the Active Resource Traffic
205(2)
6.3.2 Sequential Analysis of the Active Resource Traffic
207(5)
Conclusion
212(1)
Appendices
213(9)
Appendix A6.1 The Effect of Human Capital on Enterprise Output
213(4)
Appendix A6.2 Nonparametric Statistics of the Active Resource Traffic
217(2)
Appendix A6.3 Detection of Changes in the Active Resource Traffic
219(3)
References
222(3)
Chapter 7 Planning
225(68)
7.1 Algorithmic Models of Planning Process in a Hierarchical Dynamic Multi-Agent Active System
226(14)
7.1.1 An Algorithm of Compatible Planning in a SEA Hierarchy
226(5)
7.1.2 Quantitative Planning in the Hierarchy of Structural Elements of Activity
231(5)
7.1.3 Optimal Planning of CA Execution According to the Networked Technology
236(1)
7.1.4 Optimal Design Process of Networked Technology
237(3)
7.2 Planning of Transition from Design Phase to Execution Phase in Dynamic Active System
240(7)
7.2.1 Optimal Transition from Design to Execution Under Known External Environment
240(4)
7.2.2 Transition from the Design Phase to Execution One under Unknown External Environment
244(3)
7.3 Planning and Control in Dynamic Multi-Agent Active System with Changing Characteristics
247(8)
7.3.1 Classes of Optimization Problem in an Active System with Changing Characteristics
248(3)
7.3.2 Planning and Control Procedure in an Active System with Changing Characteristics
251(4)
7.4 Planning of Human Capital
255(11)
7.4.1 Sources of Uncertainty and Variants of Optimization Task
256(1)
7.4.2 Known Methods and Models
257(1)
7.4.3 Planning of the Headcount of the Active Resource Pool
258(6)
7.4.4 Planning Characteristics of Active Resource Lifecycles
264(2)
Conclusion
266(1)
Appendixes
267 (20)
Appendix A7.1 Optimal Choice of the Decision-Making Procedure Parameters (7.26)
267(4)
Appendix A7.2 Simulation-Based Study of the Decision-Making Procedure (7.26)
271 (4)
Appendix A7.3 Optimisation in "Batch Production" Case (7.27)
275(1)
Appendix A7.4 Example of "Simple Agent" Model Planning with Disorder of Technology Function
276(4)
Appendix A7.5 Bellman Equations Solution for Probabilistic Case (7.36)
280 (4)
Appendix A7.6 Bellman Equations Solution for Interval Case (7.37)
284(3)
References
287(6)
Part III Practice: Business Tools and Applications
Chapter 8 Optimal Enterprise Control Framework and Practical Implementation
293(50)
8.1 Optimal Enterprise Control Framework
294(13)
8.1.1 OEC Framework as the Universal Algorithm of Optimal Enterprise Control
294(5)
Design phase
296(2)
Execution phase
298(1)
Reflection phase
299 (1)
8.1.2 Integration and Generalization Capabilities of the OEC Framework
299(3)
8.1.3 Perfect Enterprise Concept and Checklists
302(5)
8.2 Some Applications of Contracts
307(4)
8.3 Practical Technology Development Optimization
311(6)
8.3.1 Optimal Technology Development in Batch Manufacturing
311(4)
8.3.2 Optimal Learning in Customer Service Center
315(2)
8.4 Optimal Planning in Practice
317(15)
8.4.1 Compatible Planning in Hierarchical Enterprise
317(3)
8.4.2 Headcount Planning and Optimization
320(2)
8.4.3 Optimization of Economical Characteristics of Human Resource Lifecycles
322(2)
8.4.4 Contracts in Changing Business Environment
324(3)
8.4.5 Control of Characteristics of Human Resource Lifecycles
327(2)
8.4.6 Earned Value Management and Activity Planning
329(3)
Conclusion
332(1)
Appendixes
332(10)
Appendix A8.1 Simulation of the Optimal Technology Development Process in Batch Manufacturing
332(4)
Appendix A8.2 Technology Learning at the Customer Service Center
336(6)
References
342(1)
Afterword 343(4)
Index 347
Mikhail Belov is Deputy CEO of IBS, responsible for new technology and business development in the area of engineering IT systems, PLM and other industrial IT systems. His 38-year career has centered on systems engineering, operations research, economics and finance, IT, electronics.

Mikhail was Vice-President of Metrosvyaz, Deputy Finance Director of TOKOBANK, and President & Owner of Geliosoft Consulting, a startup company focused on cutting-edge technologies, such as an ultra-wideband multi-radar system.

Mikhail holds an MS in electronics from Moscow Engineering Physics Institute and a PhD in operations research and applied math statistics from the Central Scientific Research Institute.

Doctor of Science (Techn.), he also holds an MBA in finance.

Dmitry Novikov is director of Institute of Control Sciences of Russian Academy of Sciences. His scientific interests cover: Control Theory, Cybernetics, Game Theory, Decision-making, Collective Behavior. More than 500 publications (see the full publication history), including more than 20 monographs (Springer, CRC, etc), textbooks and brochures; more than 100 papers in leading journals.

He has more than 25 years extensive experience in the field of scientific and technological projects and company management (manufacturing sphere, research, teaching, consulting).

Dmitry is Doctor of Science (Techn.), Professor, Corresponding member of Russian Academy of Sciences, Head of Control Sciences Department of Moscow Institute of Physics and Technology