Package Design | packagedesignmag.com

(May 2009) posted on Sat Oct 10, 2009

By Joe Buzzanga

Compelling consumer package design brings together simplicity, functionality, and an inherent call to purchase. But the road to reaching this R&D end goal is oftentimes hindered by hours of dead-end research and somewhat random guessing, both in regards to what consumers want, and how to engineer the packaging that will cater to customer demand. In the middle of this laborious and time-consuming process, it can be hard to imagine that a consumer-friendly, cost-effective and attractive product will someday emerge.

Corporate R&D teams struggle with these budget and time constraints on a daily basis. In reality, they are grappling with the root of the problem: the mountains of information that, thanks to the constant proliferation of the Internet, grow exponentially every day. This vast repository of information is a great resource, but only when it can be searched and used in an effective, efficient manner. Given the amount of time that the scientists and engineers spend in corporate R&D research, it is clear that more information is not what is needed. According to OutSell Inc.'s 2007 survey of 6,300 knowledge workers R&D staff members spend on average 5.5 hours gathering, looking for, or pulling together information and an additional 4.7 hours analyzing and applying this information. Instead, package developers and other research professionals need to get more out of the resources they already have by effectively leveraging all of this valuable information to their advantage.

Better searching

Semantic technology, with its ability to "read into" search phrases and terms, provides this vital functionality. By maintaining the meaning of a query, semantic search can generate actionable solutions rather than just links or a list of records, allowing researchers to quickly uncover useful and important areas of investigation. From an old-school technology perspective, semantic search turns familiar resources—including the Internet, scientific journals, patent information and more—into an organized, easily searchable database.

As a technology, these forms of advanced intelligent search are clearly the next generation of the Web. Unlike traditional consumer search engines, the semantic searching does not rely on popularity or keyword when "reading" information and returning results. Rather, it parses queries to give researchers actionable information related to the specifics of the question or problem at hand.