With a two-decade consistent research interest for Systematic BiologicallyInspired Design, a number of methods and tools to support bio-ideation have been proposed. However, objective quantification of the effects these aids have on the design outcomes is rare. This contribution presents an impact analysis of the most popular knowledge-based tool, AskNature, in the form of an outcomebased study. The results consistently support a common claim used in favour of bio-inspired design, i.e. the expectation of identifying more out-of-the-box solutions. Furthermore, to further facilitate biological solution analysis and cross-domain knowledge transfer, an adaptation to AskNature's stimuli format d i.e. adding a graphical illustration of the biological solution principle d is validated to further boost novelty. C reative problem solving is a key task for companies pursuing inventions that may grow into successful innovations. One strategy for solving new problems is learning from previously solved analogous problems. In Design-by-Analogy (DbA) a solution principle behind an already solved problem is transferred to solve a new problem. For example, when looking for new ways to unfold a tent, products with similar functionality, like for instance umbrellas, can be sources of inspiration and knowledge transfer. Biologically-Inspired Design (BID) is a specific type of between domain DbA where inspiration is taken from the natural world (source domain) to solve technical problems or challenges (target domain). Three frequently used arguments for looking at nature for inspiration are (1) the proven performance of biological systems, (2) the potential for sustainable products and (3) the potential for finding out-of-the-box solutions. The first, proven performance of biological systems, logically follows from the overwhelming evidence supporting evolution, i.e. the change in inherited characteristics of biological populations over successive generations, a continuous repetition of a non-random selection mechanism (survival of the fittest) applied to traits subject to random variation. The products of these continuous improvement iterations d solution principles of biological systems d Corresponding author: Dennis Vandevenne dennis.vandevenne@ kuleuven.be www.elsevier.com/locate/destud 0142-694X Design Studies --(2016) --e--http://dx.Please cite this article in press as: Vandevenne, D., et al., Enhancing novelty with knowledge-based support for Biologically-Inspired Design, Design Studies (2016), http://dx.