Comment
I’ll address specific issues in a moment but let me first make a fundamental point regarding automated analysis, which so many people seem to be missing. Automated analysis should not be viewed as a replacement for human analysis. Rather, it is a different method that is opening up entirely new and tremendously exciting ways of analysing data. The analogy I like to use relates to the film industry when ‘talkies’ first came along. When this first happened producers just started to film plays and stage shows. In other words they didn’t understand or appreciate that talkies enabled film to be used in a completely different way, which would allow it to become a new medium in its own right. Likewise, I’ve found that people simply look upon automated analysis as an alternative way of carrying out analysis that would otherwise be done by humans. Yes, there are some applications where that is the case but of far greater importance are new areas, which automated analysis is opening up. In particular is the ability to generate large volumes of time series data, which allows very robust statistical analysis to be conducted that would be impossible with human analysis.
The language debate is an interesting one but in our experience the overwhelming volume of online media coverage, at least in business terms, is in English. Indeed, an aggregated search will reveal at least 95% of domains being .com followed by .co.uk. So much so, in fact, that we haven’t carried out analysis in any other language for a long time (we can currently handle Spanish, French and Italian as well as English; and remember that Spanish is one of the world's major languages). Yes, languages such as Mandarin present particular problems (not least in terms of characters as well as structure) but necessity is the mother of invention so don’t be too surprised if this changes rapidly if China’s online presence overcomes the political issues currently faced re censorship, etc.
Re the use of automation to conduct ‘open’ analysis there are a number of tools developing rapidly that address this very issue and the time when computers can be used to analyse “what’s there” rather than “what we tell them” isn’t far away. Indeed, it’s already possible though not quite yet on the scale required for commercial applications.
As for the question of looking forward, this is something for which automated analysis is ideally suited – far more than human analysis, in fact. Neither machine nor human can predict the future but one major benefit of automated analysis is the volume and granularity of time series data that it generates, which enable very sophisticated predictive models to be developed. Of course, humans still need to interpret the results of these models but they provide a very robust basis for forward-looking decision-making that, again, is pretty well impossible with human analysis.
Last but not least the question of competitive advantage where, again, automated analysis offers huge benefits. The reason is that automated systems can analyse a hundred companies just as easily and only a few seconds longer than it takes to analyse one. The breadth and depth of competitive information this creates is huge and much, much greater than is practical – or cost-effective – using human analysis.
