The Fuzzy Front End of New Product Development for Discontinuous Innovations: A Theoretical Model
Bibliographic record
Abstract
The fuzzy front end of the new product development (NPD) process, the time and activity prior to an organization's first screen of a new product idea, is the root of success for firms involved with discontinuous new product innovation. Yet understanding the fuzzy front‐end process has been a challenge for academics and organizations alike. While approaches to handling the fuzzy front end have been suggested in the literature, these tend to be relevant largely for incremental new product situations where organizations are aware of and are involved in the NPD process from the project's beginning. For incremental new products, structured problems or opportunities typically are laid out at the organizational level and are directed to individuals for information gathering. In the case of discontinuous innovations, however, we propose that the process works in the opposite direction—that is, that the timing and likelihood of organizational‐level involvement is more likely to be at the discretion of individuals. Such individuals perform a boundary‐spanning function by identifying and by understanding emerging patterns in the environment, with little or no direction from the organization. Often, these same individuals also act as gatekeepers by deciding on the value to the organization of externally derived information, as well as whether such information will be shared. Consequently for discontinuous innovations, information search and related problems/opportunities are unstructured and are at the individual level during the fuzzy front end. As such, the direction of initial decisions about new environmental information tends to be inward, toward the corporate decision‐making level, rather than the other way around. In order to cope with the special and complex nature of decisions made at the fuzzy front end of NPD for discontinuous innovations, this process is detailed as a series of decisions occurring over three proposed interfaces: boundary, gatekeeping, and project. The difference between each interface lies in the nature of the decisions made: At the boundary and gatekeeping interfaces, the primary impetus is individual‐level decision‐making; at the project interface, decisions occur at the organizational level. By articulating these processes in the form of a model, we achieve two objectives: (1) We outline a more detailed and comprehensive approach to understanding the nature of the front‐end decision making process for discontinuous innovations; and (2) we detail specific propositions for future research on each stage of the process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".