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06 October 2007

New applications for patent analysis in competitive intelligence

The exploitation of patent databases for competitive intelligence has been a key staple of much of the private sector’s intelligence work. This has been particularly a feature in consultancies with strong scientific and technical accounts, as well as the major manufacturing and R&D houses in the pharmaceutical and materials engineering sectors.

The Economist profiles a new method of mining patent information as feedstock for genetic algorithms designed to rapidly develop problem solving approaches for those wishing to find a novel alternative free of patent encumbrance (and in the process, avoid legal difficulties that may be created by the re-use of existing solutions).

The wider adoption of this technique would likely drive additional interest in what has been a longstanding element of competitive intelligence tradecraft. This follows an increasing trend within the private sector’s evolving intelligence sophistication – the reliance of many firms on intelligence products and services not merely for the executive level (as had long been the insistence of those wishing to assure C- level buy in, or model their own efforts on common IC publications processes such as the PDB). Rather, many of the successful new applications of intelligence are tightly integrated at the working level in the corporation’s various business units, and directly support the line responsibilities of teams of industry experts through specialist contributions.

To a large extent, this shift in private sector CI also mirrors the evolution of many intelligence efforts in other environments, which trend now towards increasing numbers of analysts embedded with units of operations professionals, in a distinct break from the supposed ideal of the “ivory tower” analyst organization divided functionally and geographically from the consumers they are supposed to support.

We might add that the same genetic patent analysis approaches, may also certainly have applications beyond the private sector. One can easily envision counterproliferation purposes for the same genetic algorithm approaches, particularly given the starting point of known weapons systems designs and the existing stable of scientific expertise that may be present in a given proliferant state’s program. The genetic algorithm might suggest alternative materials or processes that an adversary may attempt to substitute for prohibited components in a military or dual use acquisition program.

h/t Slashdot

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