The proper authorship of invention disclosures as an internal document meant to record and communicate the processes and products of early-stage innovation can be overlooked. It is an internal document, after all. But this critical step is vital to advancing ideation that organizations should see less as an obligation and more as an opportunity. When done properly and with the right tools, invention disclosures can improve ideation, collaboration, and—ultimately—invention value. They can reduce costs even before you decide whether or not to pursue a defensive publication or patent.
Invention disclosures are a requirement for some industries. For universities, for instance, invention disclosures essentially act as public disclosures and are required by institutions that automatically disclose them.
But innovation teams at public entities are not the only ones that can benefit from high-quality invention disclosures setting the foundation for technology transfer. For private sector companies, they can be the first opportunity to perform vital landscape and competitive research that could lead to capturing market share or formulating a blue ocean strategy.
Even if a disclosure stays internal, there is value in getting it right the first time. But doing so requires resources, attention to detail, and time. Semantic AI powered by NLP can help with all three.
Benefits to Internal Communication and Collaboration
Each innovator may see the logistics of the innovation lifecycle differently than their managers or support teams. But the innovator’s vital role can be devalued by siloed workflows specific to their expertise and process. This can result in innovation-killing delays and mistakes that frequently prohibit great ideas from being evaluated as painlessly as they could be. For highly productive engineering teams, this could mean ideas dying in early innovation stages, or because of choosing the wrong ideas to pursue.
Disrupting workflow siloing results in the authoring of effective invention disclosures that encourage collaboration and forward progress. Simply put, engineers are good at a lot of things, and writing for optimal collaboration is typically not one of them without the resources to do it well.
Less Writing, Faster Evaluation, and Streamlined Communications
Just as AI is driving change in the marketplace, NLP technology is driving change in AI. AI is already used in customer-facing touchpoints including customer service bots and product suggestions. But its impact to this point has been less realized in internal teams. It’s no fault of theirs, as AI has developed a reputation among both management and innovators as being untrustworthy and inconsistent in its application and results.
But the right AI can be an effective teammate when it’s automating portions of the disclosure authorship workflow while streamlining others. Idea viability can be readily assessed based on invention descriptions while maintaining explainability, rather than hiding behind a black box. A tool like IQ Ideas Plus™ 2.0, provides the best of both AI worlds. It provides simple idea evaluation using single, condensed scoring metrics comprised of variables that are transparent and easy to understand.
Inventors can actively modify their descriptions with IQ Ideas Plus 2.0 as the search tool works in the background to pull dozens of semantically relevant patents and prior art for idea comparison. Helping the inventor decide on the spot which ideas are worth advancing saves reduces costs, saves time, and improves ROI.
This active but simple workflow can easily be initiated by inventors that can better vet opportunities before moving a more polished disclosure to R&D supervisors as well as IP teams. IQ Ideas’s NLP tools prompt inventor-authors to simplify and clarify language beyond that of simple word processors while highlighting obvious grammatical errors.
Pivoting to Patent or Defensive Publications
While the value to internal teams is clear, invention disclosures can also serve as the origins of future patents or defensive publications. Therefore, the need to establish workable invention descriptions provides value beyond the cost savings delivered via automation and AI-optimized workflows. Too many teams are spending valuable time rewriting initial disclosure drafts and shuffling them between teams for repeated evaluation. Under this common scenario, inefficiency, slower analysis (due to incomplete or inaccurate research), and delayed publication are all significant risks to technology market share and profitability.