The MVP of Open Innovation: Technology Scouting Software

October 5, 2022
4 mins read

Introduction

In the previous blog, technology scouting is shown to be a vital cog in the wheel of innovation. To identify technologies, certain sources of information are tapped into with various methods. However, manually sifting through mountains of information and looking for small details is analogous to finding needles in haystacks. Luckily, there are better and faster ways to do this.

Let’s just Google it?

Sources of information are loosely divided into two categories: informal and formal [1]. The most popular examples of informal sources include conferences, trade fairs and coffee-breaks with work-colleagues. Traditionally, informal sources took precedence over formal sources, whereby 80% of external information may be found internally within the company and its external network [2].

Popular examples of formal sources include journals, patents and websites. Given the rise of the web, formal sources have a huge advantage: Information can be found on an on-demand basis with automated information searches, such as online search engines (eventually leading to the term ‘just Google it’).

Scraping the Barrel

Despite the wealth of information available from (in)formal sources,  the information is still often found through a manual process. This is rather tedious, as the information is often unstructured and scattered across a multitude of sources, whereby even website links on search engines are often ranked according to popularity (and not relevance) [3].

To skip this tedious task, dedicated software tools for technology scouting may be the saving grace. Software tools perform all the donkey work, whereby relevant text(data) sources are scraped into organised results, and, with the link of the text source (for example, the digital object identifier), are saved onto a centralised platform.

Artificial Intelligence

Nevertheless, could the text already be digested in this process? This is where artificial intelligence(AI) and software tools may go hand-in-hand. AI has the power to interpret text in a human-like manner. So now, not only is the task of scraping all data delegated to the computer, but so too is the task of reading and understanding large amounts of (un)structured text.

By going beyond matching simple keywords, AI is proven to be very powerful for technology scouting. It can provide a semantic understanding between the words in the text, and more context between the information extracted and the situation at hand. Consequently, the noise in the search results is reduced, and, in-tandem, result in far more accurate answers from a complex search query.

Conclusion

With the growing number of information sources, it is time for technology scouting to take on a new look. Digital software tools look to be the future in equipping the most important information for technology scouting. With the integration of AI to contextualise all the information, it may finally be time to say bye-bye to sieving through the pile of desk papers marked “interesting to read”.

References:
  1. Rohrbeck, René, Harnessing aNetwork of Experts for Competitive Advantage: Technology Scouting in the ICTIndustry (January 7, 2010). R&D Management, Vol. 40, No. 2, pp.169-180, 2010, Available at SSRN: https://ssrn.com/abstract=1532985
  2. Blomdell, Tor and Örtendahl, Oscar, TechnologyScouting in China For identifying cost reduction and opportunities forinnovation, Master’s Thesis, Lund University (2010).
  3. Technology Scouting as aService (TSaaS), Technical University Munich [accessed 30thAugust 2022], https://wwwmatthes.in.tum.de/pages/6rpn399cz999/Technology-Scouting-as-a-Service-TSaaS