Idea management

In a turbulent and more competition-oriented environment, organizations need to develop their ability to adapt quickly. To be able to adapt, an organization must, of course, enhance its innovativeness and successful innovation requires to be planned carefully. Even if some researchers treat the early stages of innovation as " fuzzy " because of their uncertainty, others suppose that well structured processes must be used and we agree with this last view. This paper presents a theoretical construct, defined as a new idea management lifecycle that aims to support all activities of the Front End of innovation, from insight to idea validation. This lifecycle consists of four key parts: four stages, followed by decision points "Gates", knowledge engine that enable learning to occur and flow, and contextual factors to keep alignment with organization's strategy, goals, needs... Next, a new innovation lifecycle that cover all the innovation activities was introduced. This innovation lifecycle forms the basis of a new emerging innovation management framework.

This article pinpoints requirements for organizing the fuzzy front end of the Innovation process. The author derived the conditions for computer-aided idea management from benchmarking the fuzzy front ends of several German and European companies and proposes differentiating between general and company-specific requirements for organizing the fuzzy front end. It is suggested that structuring the fuzzy front end involves low financial Investment but highly sensitive and transparent leadership. Using specific properties of ideas in the
workplace as springboards, considerations on further new requirements for successful idea management are developed. Placing a particular emphasis on the interface between the idea
owner and the idea-adoption system, an ‘idea types’ model is developed, which defines four different extreme types of employees and their inclinations to solve problems. An Extended set of requirements for managing ideas in the workplace as a useful instrument in Creation and implementation of idea-pipelines in companies and in checking software programmes for idea management or the early stages of new product development programmes is
presented.

In a turbulent and more competition‐oriented environment, organizations need to develop their ability to adapt
quickly. To be able to adapt, an organization must, of course, be innovative and attractive, and successful innovation
should be carefully planned and efficiently managed. Even if some researchers treat the early stages of innovation as
“fuzzy” because of their uncertainty, we suppose, as many others that a well structured processes, a clear representation
and a good designed management framework are crucial for the ultimate success of any innovation. Understanding the
process of innovation is to understand the factors that facilitate and inhibit the success of innovations. A best
understanding of how these factors are related will lead to define a proper representation and an efficient management
framework supporting the innovation full lifecycle. In addition, organizations have become more aware of external
knowledge and technology to maintain their competitiveness in the global market and they feel a growing need to open up
their innovation processes. Therefore, to achieve successful innovation in an open context, it is necessary to overcome the
challenge of integrating distributed and heterogeneous knowledge management systems. The emerging and rapid
development of semantic technologies brings new opportunities and provides a promising direction for such challenge.
Semantic technologies focus on the formalization of knowledge to create schemes that allow knowledge to be effectively
stored, modified, shared, exchanged and reasoned. In this paper, a semantically‐powered framework for innovation
management is presented. This framework includes a new Lifecycle Model supporting all activities of innovation with a
special focus on its front end stages; a Semantic Representation of innovation, based on three factors we have identified as
cornerstones of any successful innovation and that supports a set of automatic and intelligent services such as annotation,
relationship retrieval and semantic search; used to power the Core Services of our framework that aim to promote
innovation, notably within an open context.

In the increasingly competitive environment that characterizes the world today, the need to develop innovations
quickly has become the key driver of growth for many organizations. To be able to respond more effectively to
this new challenge, organizations would make best use of their corporate knowledge resources and memory.
Managing heterogeneous and distributed knowledge sources available in different forms and rather weakly
structured has become a challenging problem.
In this paper, we introduce taxonomy as one of the key technology for innovative knowledge management in an
open context, we revisit and review, discuss and explore the existing classifications of innovation and we
present a Generic Taxonomy for Innovation Management.

How to build effective and sustainable idea management systems, while dealing with the inherent complexity and unpredictable nature of ideas and innovation? A fundamental question crops up – are there structured ways in which complex systems can survive and thrive? Here we can take inspiration from living systems – cells, organisms, ecosystems, organizations, societies etc.

The following living system principles have been discussed: Recycling (waste = food), Diversity, Multi-functionality, Equilibrium, Flux, Oscillation, Interdependence and Emergence.

Deciding which ideas to pursue is an essential step in innovation management. Organizations increasingly open up their decision-making processes internally and externally by harnessing the collective intelligence of crowds. One mechanism for doing so is enterprise crowdfunding, i.e. inviting employees to propose and support ideas on a crowdfunding platform inside the enterprise. In this paper, we empirically analyze such an enterprise crowdfunding endeavor where hundreds of employees endowed with the discretion to spend company budget proposed dozens of ideas and decided to fund 10 of them. Based on log files and information on the employees’ roles in their enterprise, we investigate the time course of individual decision-making – i.e., whether they decide rather quickly or more time-lagged which ideas to support Factors that influence decision-making style include characteristics of proposers, supporters, ideas, supporters’ activity level, and the progress of the trial. From this, we derive suggestions for future research into crowdfunding, and we propose relevant design parameters for using crowdfunding as a tool for internal openness and Enterprise 2.0.