Description

Book Synopsis
The Design of Insight is a personal problem-solving platform that will enable readers to break out of familiar thought models and create innovative solutions for impactful change at any level in their business.

Trade Review
"Moldoveanu and Leclerc introduce business students and faculty to a personal problem-solving platform, an integrative approach toward thinking about complex problem solving as well as innovative ways of generating solutions . . . Recommended."—J.P. Miller, CHOICE
"The Design of Insight is a tour de force in the craft and discipline of problem solving. It points to both new solutions and new ways of generating solutions—which is the crux of the problem solver's skill. Read it once for fun and insight, and a second and third time for discipline and practice."—Dominic Barton, Global Managing Director, McKinsey & Company

Table of Contents
Contents and Abstracts1What Is This All About? chapter abstract

Business problem solving is hard not only because problems feature a lot of uncertain, volatile elements, but also because they are loosely defined or undefined. We introduce the basic craft of problem shaping and definition, and show how models and modeling languages help us turn ill-defined, ill-structured problems into well-defined problem statements we can solve. We also show how using several different problem solving languages to define the same problem can increase the span of possible solutions and the probability of finding and unexpectedly optimal ('innovative') solution, once it is defined. We introduce five problem solving languages – which we call Flexons - drawn from the natural and social sciences that provide lenses for representing and defining problems, and which are powerful enough to help us frame problems at any level at which we may choose to intervene: individuals, dyads, groups, teams, organizations, markets and institutions.

2The Networks Flexon chapter abstract

We introduce and elaborate the Networks Flexon – a problem solving language that uses graphs to represent entities as varied as social interactions in an executive team, deal flows in an investment syndicate, modules in a software platform or value-linked activity chains in an industry. We show how problems at multiple levels of analysis can be defined, shaped, structured and simplified using this language, which supplies not only a basic representation scheme – nodes and links – but also a set of performance measures at the level of the network as a whole (density, connectivity, clustering, path length) and at the level of individual nodes (centrality measures). The Networks Flexon has been used in fields as varied as statistical mechanics, industrial organization economics, sociology, psychology, neuroscience and information theory to solve problems across many different disciplines.

3The Decision Agent Flexon chapter abstract

We introduce and elaborate the Decision Agent Flexon – a problem solving language that uses agents, decisions, outcomes and payoffs or incentives to define and structure business problems at any level of analysis. The Flexon also uses concepts such as decision rights, and information and expertise to model the complex landscape of relationships in a hierarchical or non-market organization – and offers a set of performance metrics – such as agency costs, communication costs and coordination costs – that problem solvers using the flexon can use to define their objective functions. This flexon – used broadly across the fields of economics - decision sciences, game theory, agency theory – can be flexibly deployed to define business problems at any level of analysis.

4The System Dynamics Flexon chapter abstract

We introduce and elaborate the System Dynamics Flexon – a problem solving language that uses causal maps and stocks and flows of money, matter and information to define and structure business problems at any level of analysis. The Flexon also supplies a set of performance metrics for business problem solving, such as desired transient and steady state responses of a dynamically evolving system – to supply objectives to the problem solver. This modeling language has been broadly used and developwed to datre in fields as diverse as classical mechanics, mechanical, chemical and electrical engineering, psychology, neuroscience and macroeconomic modeling to supply tight and precise problem formulation at any level of analysis.

5The Evolutionary Flexon chapter abstract

We introduce and elaborate the Evolutionary Flexon – a problem solving language that uses the basic concepts of populations and variation, selection and retention mechanisms to supply models of the evolution of entities ranging from deliberations within a group, to the evolution of organizations, product modules, technologies, and markets. The Flexon also supplies a set of outcome measures – like fitness maximization and the speed and accuracy of convergence in variation-selection-retention processes to allow problem solvers to define and sharpen their problem solving objectives. The Evolutionary Flexon has been used in fields as diverse as theoretical and experimental biology, biological archaeology and anthropology, industrial organization economics, sociology, psychology, theoretical computer science and the theory of algorithms to both explain and predict a large number of phenomena in multiple domains of experience.

6The Information Processing Flexon chapter abstract

We introduce and elaborate the Information Processing Flexon – a problem solving language that uses the basic concepts of problems, solutions, solution search spaces, problem solving agents and the complexity of various problem statements to represent business processes at any level. It also supplies a set of performance measures like accuracy, reliability and speed of convergence that will help problem solvers define objective functions for the problems they are solving. The Information Processing Flexon has been used in fields as diverse as information theory, theoretical computer science, the theory of algorithms, organizational theory and statistical mechanics to address a large number of diverse problems.

7Recombinant Problem Solving and the Design of Insight chapter abstract

This chapter shows how the five Flexons can be used, serially and in parallel, to define, structure and solve loosely articulated business difficulties, predicaments and situations. Through examples, it highlights the value of the flexons in both supplying the requisite depth and precision required for solving real business problems in practical amounts of time, and the value of diversity and heterogeneity of models and modeling languages in solving any business problem.

The Design of Insight

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    A Paperback / softback by Mihnea Moldoveanu, Olivier Leclerc

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of The Design of Insight by Mihnea Moldoveanu

      Publisher: Stanford University Press
      Publication Date: 06/05/2015
      ISBN13: 9780804794091, 978-0804794091
      ISBN10: 080479409X

      Description

      Book Synopsis
      The Design of Insight is a personal problem-solving platform that will enable readers to break out of familiar thought models and create innovative solutions for impactful change at any level in their business.

      Trade Review
      "Moldoveanu and Leclerc introduce business students and faculty to a personal problem-solving platform, an integrative approach toward thinking about complex problem solving as well as innovative ways of generating solutions . . . Recommended."—J.P. Miller, CHOICE
      "The Design of Insight is a tour de force in the craft and discipline of problem solving. It points to both new solutions and new ways of generating solutions—which is the crux of the problem solver's skill. Read it once for fun and insight, and a second and third time for discipline and practice."—Dominic Barton, Global Managing Director, McKinsey & Company

      Table of Contents
      Contents and Abstracts1What Is This All About? chapter abstract

      Business problem solving is hard not only because problems feature a lot of uncertain, volatile elements, but also because they are loosely defined or undefined. We introduce the basic craft of problem shaping and definition, and show how models and modeling languages help us turn ill-defined, ill-structured problems into well-defined problem statements we can solve. We also show how using several different problem solving languages to define the same problem can increase the span of possible solutions and the probability of finding and unexpectedly optimal ('innovative') solution, once it is defined. We introduce five problem solving languages – which we call Flexons - drawn from the natural and social sciences that provide lenses for representing and defining problems, and which are powerful enough to help us frame problems at any level at which we may choose to intervene: individuals, dyads, groups, teams, organizations, markets and institutions.

      2The Networks Flexon chapter abstract

      We introduce and elaborate the Networks Flexon – a problem solving language that uses graphs to represent entities as varied as social interactions in an executive team, deal flows in an investment syndicate, modules in a software platform or value-linked activity chains in an industry. We show how problems at multiple levels of analysis can be defined, shaped, structured and simplified using this language, which supplies not only a basic representation scheme – nodes and links – but also a set of performance measures at the level of the network as a whole (density, connectivity, clustering, path length) and at the level of individual nodes (centrality measures). The Networks Flexon has been used in fields as varied as statistical mechanics, industrial organization economics, sociology, psychology, neuroscience and information theory to solve problems across many different disciplines.

      3The Decision Agent Flexon chapter abstract

      We introduce and elaborate the Decision Agent Flexon – a problem solving language that uses agents, decisions, outcomes and payoffs or incentives to define and structure business problems at any level of analysis. The Flexon also uses concepts such as decision rights, and information and expertise to model the complex landscape of relationships in a hierarchical or non-market organization – and offers a set of performance metrics – such as agency costs, communication costs and coordination costs – that problem solvers using the flexon can use to define their objective functions. This flexon – used broadly across the fields of economics - decision sciences, game theory, agency theory – can be flexibly deployed to define business problems at any level of analysis.

      4The System Dynamics Flexon chapter abstract

      We introduce and elaborate the System Dynamics Flexon – a problem solving language that uses causal maps and stocks and flows of money, matter and information to define and structure business problems at any level of analysis. The Flexon also supplies a set of performance metrics for business problem solving, such as desired transient and steady state responses of a dynamically evolving system – to supply objectives to the problem solver. This modeling language has been broadly used and developwed to datre in fields as diverse as classical mechanics, mechanical, chemical and electrical engineering, psychology, neuroscience and macroeconomic modeling to supply tight and precise problem formulation at any level of analysis.

      5The Evolutionary Flexon chapter abstract

      We introduce and elaborate the Evolutionary Flexon – a problem solving language that uses the basic concepts of populations and variation, selection and retention mechanisms to supply models of the evolution of entities ranging from deliberations within a group, to the evolution of organizations, product modules, technologies, and markets. The Flexon also supplies a set of outcome measures – like fitness maximization and the speed and accuracy of convergence in variation-selection-retention processes to allow problem solvers to define and sharpen their problem solving objectives. The Evolutionary Flexon has been used in fields as diverse as theoretical and experimental biology, biological archaeology and anthropology, industrial organization economics, sociology, psychology, theoretical computer science and the theory of algorithms to both explain and predict a large number of phenomena in multiple domains of experience.

      6The Information Processing Flexon chapter abstract

      We introduce and elaborate the Information Processing Flexon – a problem solving language that uses the basic concepts of problems, solutions, solution search spaces, problem solving agents and the complexity of various problem statements to represent business processes at any level. It also supplies a set of performance measures like accuracy, reliability and speed of convergence that will help problem solvers define objective functions for the problems they are solving. The Information Processing Flexon has been used in fields as diverse as information theory, theoretical computer science, the theory of algorithms, organizational theory and statistical mechanics to address a large number of diverse problems.

      7Recombinant Problem Solving and the Design of Insight chapter abstract

      This chapter shows how the five Flexons can be used, serially and in parallel, to define, structure and solve loosely articulated business difficulties, predicaments and situations. Through examples, it highlights the value of the flexons in both supplying the requisite depth and precision required for solving real business problems in practical amounts of time, and the value of diversity and heterogeneity of models and modeling languages in solving any business problem.

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