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Deep Semantics: the Future of Innovation Research

  
  
  

Yesterday, we hosted a webcast on the Future of Research and how Question Answering Technologies – and Deep Semantics, in particular – address the needs of the knowledge worker.

We feel your pain.
The response was overwhelming. Hundreds of registrations for the event, a flood of responses to our pre-event survey and dozens of questions throughout the live broadcast.  Clearly, the topic of search – and the failure of traditional search – has struck a chord.

Traditional Search Failing the Innovation Worker

For the innovation worker, in particular, search or research is a tremendous challenge – and time suck. 

Finding the innovation ‘needle in the haystack’. 
Whether it exists within your organization’s four walls or in patent literature, trade publications, competitive literature, or out on the Web – finding the precise information you need gets harder every day. 

The problem starts with the staggering fact that the information available to the knowledge worker today is growing at an explosive and exponential rate. Industry analysts, IDC, estimate a 40-60% year-over-year growth of information.  

Beyond the sheer volume of data, knowing ‘where’ to look becomes increasingly more challenging. Product development information is scattered across the organization – across teams, departments, verticals, sciences, geographies, etc.  Knowledge exists in personal and corporate drives, in email, field reports, customer service records, PLM and PDM systems, and so on. Corporate intranets, shared drives and repositories do little to solve the knowledge retrieval challenge. And, as demonstrated by our survey - accessing valuable external content is an even greater challenge.

Traditional keyword and enterprise search technologies fail the innovation worker – returning too many documents, too much duplication and too much irrelevant information. 

What engineers, scientists and researchers need are precise answers to their questions – not a list of irrelevant ‘results’.

The cost of failed search efforts. 
IDC estimates that an enterprise employing 1,000 knowledge workers wastes millions each year searching for nonexistent information, failing to find existing information, and recreating information that can’t be found. The cost to productivity is big, but the opportunity cost is far greater... Imagine the cost of missing a market? of going to market ahead of competition, instead of behind? of developing the next breakthrough technology? of developing a better performing product?

Fortunately, there is a solution.
Invention Machine Goldfire is a purpose-built innovation intelligence platform that integrates Deep Semantics capabilities with proven innovation tools and methods, collaboration capabilities and access to rich technical content to:

  • Power breakthrough search experiences to deliver precisely relevant concepts
  • Help innovation workers explore problems and their solutions
  • Unlock the value hidden deep in internal and external knowledge sources to speed discovery and knowledge-enable decision making
  • Stimulate idea generation and accelerate inventive problem solving

From identifying a new market to developing a new product to improving existing products and processes, Goldfire is being used by hundreds of organizations – across industries and across the globe – to bring efficiency, uniformity and repeatability to innovation processes across the product lifecycle.

Learn more: Take a 3-minute tour or request a demo today.