Hands down, the competitor who uses the AI Innovation Platform prevails.
This is the most consequential idea for survival on every level: we prevail through innovation. Innovation is a very inefficient process of trial and error. Innovation productivity is boosted by applying generic tools that are not specific to any field of research, rather, like management tools, are universal. Some tools are simple and ready, others are sophisticated and complex. Take it in. Until now you thought that only someone familiar with your research area can help you. Not so! Your R&D can be conclusively accelerated using D&G Sciences -- Innovation Productivity Corporation generic tools: InnovationSP
Introducing the AI Empowered Innovation Solution Protocol (InnovationSP): based on an unbiased, credible measure of innovation progress, and on next-step procedure that offers dead-end-free innovation pathway.
Serving innovators, their underwriters, and their beneficiaries to allocate resources better.
•Creativity points to successful pathways but mixed with delusional tracks.
•To improve innovation, creativity must be awakened, but its suggestions must be rank-ordered so that limited resources will not be wasted on tantalizing but unrealistic scenarios.
•InnovationSP spurs creativity, and guides the allocation of resources.
Measuring Innovation Progress
Dead-End Free Innovation
How often have you encountered an innovation wall – got stuck?
The InnovationSP protocol says: facing a stubborn innovation challenge, IC, identify a related challenge IC’ which is easier to solve than IC (IC’ < IC), such that when you solve IC’, it will be easier to solve IC.
This IC-Shift is iterative, continue until a derived challenge is solved, then climb back.
This procedure is dead-end free
Next Challenge Category
•Breakdown (B): (i) to smaller challenges, (ii) to parallel solution options, (iii) to complexity graded challenges.
•Extension (X): homomorphic mapping to known challenges of identified structural similarity
•Abstraction (A): Redefine the innovation challenge in a more essential form, stripping off the details.
Shifting to the next innovation challenge is an iterative process, repeated for as many rounds as desired, until the newly defined challenge is simple enough to be resolved. Then one climbs back to the previous challenges up to the original innovation challenge that invoked the Innovation Solution Protocol
The Innovation Map
The multi-directional challenges spread out and define the Innovation map on which the innovator charts their path from challenge-stated to challenge resolved.
The Innovation Map Real Life Illustration
The chart below depicts an innovation process that was invoked by an industrial innovation challenge posed by environmental technology. It developed along a well defined pathway marked on the Innovation Map. On the side, this innovation process yielded four granted US patents.
The Developer's Story
As a practicing engineer Gideon realized that bold innovative ideas are left unfunded on account of bad cost estimates, mostly done without advanced math tools. Spotting a niche, Gideon established a cost engineering service firm. The biggest challenge was to estimate cost-to-complete, and time-to-finish for R&D projects. Gideon soon realized that the cost estimation curve is a leading indicator as to the state of the innovation challenge and hence it can be used as an innovation guide, resulting in more efficient innovation. The emerging theory became increasingly complex, so Gideon returned to his admired professor at the Technion in Haifa for some help. Professor Ephraim Kehat said: this challenge fits for a PhD dissertation. So while staying in field practice Gideon dedicated several years to formulating these promising ideas for innovating the process of innovation. Following the doctoral thesis, Dr. Samid applied the emerging tools on live innovation challenges, including his own innovative pursuits. An avalanche of 7-8 patents a year were granted owing to this now maturing Innovation Solution Protocol (InnovationSP) methodology. Nowadays Prof. Samid is busy migrating the methodology into artificial intelligence framework. Great Expectations
