For any R&D company that has a lot of in-house raw data, the Watson Discovery Advisor is likley to generate a lot of interest.
Imagine you're an executive VP in R&D in a board meeting. You receive this challenge from the CEO who hates your guts: "Our R&D productivity continues to decline. What're you doing about this? How are you extracting every last bit of value from our data? Our major competitors are using tools like Watson. Why aren't we?" You damned well better have an answer.
I work for a Fortune 100 R&D company that is *very* interested in improving its R&D ROI. I know for a fact that any opportunity to reevaluate our data to derive additional value (e.g. new prospects) will set off bells among the C suiters. IMHO Watson, and especially Discovery Advisor, is the first system I've seen with that potential.
Of course, IBM is going to have to step up its game in loading and tagging all that data. I suspect that's where most of its new Watson staff will work. I suspect the most fruitful features in data are not readable in natural language (English). Much has been summarized in graphs, or lies in tables, or in addenda. Or it's buried deep in old screening results stored in flat files that were long ago archived to tape. And it's certainly not present in easy-to-access content like online research paper abstracts.
But all it takes is one or two significant new leads to make the millions you spent hiring Watson look like money *very* well spent. And personally, I think that scenario is entirely plausible.