2015•Creativity and Innovation ManagementRequires access

Managing Radical Innovation as an Innovative Design Process: Generative Constraints and Cumulative Sets of Rules

Pierre-Antoine Arrighi, Pascal Le Masson, Benoît Weil

Open publisher page 20 citations

Abstract

This paper focuses on the organization of design processes and the difficulty of simultaneously achieving control and exploration while aiming to achieve radical innovation. After a first generation of works that tended to oppose new product development (NPD) processes (with controlled convergence and very limited exploration) to innovation processes (with poorly controlled convergence and random (uncontrolled) exploration), the new generation of works proposed ways to combine control and convergence either through concept shift or through stable architectures. Relying on a generic analytical framework (design space/value management), it appears that each model makes restrictive hypotheses (respectively smart leadership or stable architecture) to address two critical questions: How can one increase the efficiency of exploration? How can one ensure forms of cumulative convergence? Relying on the same analytical framework, we analyse two cases that explore the unknown in a controlled way and still do not correspond two either of the two models. We show that these two anomalies and the two models actually have two critical features in common: a focus on generative constraint and a logic of cumulative design rules. As a consequence, these two features might lead to several processes where teams have to explore the unknown and still have to keep a rigorous control of exploration and convergence.

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What this paper is about

This paper focuses on the organization of design processes and the difficulty of simultaneously achieving control and exploration while aiming to achieve radical innovation. After a first generation of works that tended to oppose new product development (NPD) processes (with controlled convergence and very limited exploration) to innovation processes (with poorly controlled convergence and random (uncontrolled) exploration), the new generation of works proposed ways to combine control and convergence either through concept shift or through stable architectures. Relying on a generic analytical framework (design space/value management), it appears that each model makes restrictive hypotheses (respectively smart leadership or stable architecture) to address two critical questions: How can one increase the efficiency of exploration? How can one ensure forms of cumulative convergence? Relying on the same analytical framework, we analyse two cases that explore the unknown in a controlled way and still do not correspond two either of the two models. We show that these two anomalies and the two models actually have two critical features in common: a focus on generative constraint and a logic of cumulative design rules. As a consequence, these two features might lead to several processes where teams have to explore the unknown and still have to keep a rigorous control of exploration and convergence.

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Available abstract

This paper focuses on the organization of design processes and the difficulty of simultaneously achieving control and exploration while aiming to achieve radical innovation. After a first generation of works that tended to oppose new product development (NPD) processes (with controlled convergence and very limited exploration) to innovation processes (with poorly controlled convergence and random (uncontrolled) exploration), the new generation of works proposed ways to combine control and convergence either through concept shift or through stable architectures. Relying on a generic analytical framework (design space/value management), it appears that each model makes restrictive hypotheses (respectively smart leadership or stable architecture) to address two critical questions: How can one increase the efficiency of exploration? How can one ensure forms of cumulative convergence? Relying on the same analytical framework, we analyse two cases that explore the unknown in a controlled way and still do not correspond two either of the two models. We show that these two anomalies and the two models actually have two critical features in common: a focus on generative constraint and a logic of cumulative design rules. As a consequence, these two features might lead to several processes where teams have to explore the unknown and still have to keep a rigorous control of exploration and convergence.

Key concepts: Convergence (economics), Generative grammar, Computer science, Constraint (computer-aided design), Process (computing), Control (management), Space (punctuation), Management science

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