Bibliographic record
Abstract
Product and service innovation does not happen in isolation; it requires a cross‐functional team—most of whom are not designers and may not even be familiar with design practices. In digital product or service offering, more often than not the core team developing/enhancing product consists of multiple functions—from design and engineering to marketing and sales, with little or no familiarity with design processes and practices such as creative ideation. In such cases, ideation becomes a platform for groupthink and corporate inertia, deterring lateral thinking and innovation. Hence, a structured approach to idea facilitation can help achieve the maximum opportunities availed by ideation sessions: innovative experience and service ideas. Structured ideation frameworks can discourage linear thinking and encourage teams to think strategically and laterally—by switching perspectives, identifying multiple points of view, challenging assumptions, and contextualizing problems. This paper provides a number of idea facilitation frameworks that enable creative and innovative outcomes when working with a multifunctional team—with design and nondesign professionals with various levels of product–service development experience. These frameworks bridge the gap between insights and strategy and create conditions necessary for creative and lateral thinking. Additionally, it provides best practices to help operationalize idea management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".