Research and Development Innovation: A New Study from a Search Vendor
August 3, 2012
I received message from LinkedIn about a news item called “What Are the Keys to Innovation in R&D?” I followed the links and learned that the “study” was sponsored by Coveo, a search vendor based in Canada. You can access similar information about the study by navigating to the blog post “New Study: The Keys to Innovation for R&D Organizations – Their Own, Unused Knowledge.” (You will also want to reference the news release about the study as well. It is on the Coveo News and Events page.
Engineers need access to the drawings and those data behind the component or subsystem manufactured by their employer. Text based search systems cannot handle this type of specialized data without some additional work or the use of third party systems. A happy quack to PRLog: http://www.prlog.org/10416296-mechanical-design-drawing-services.jpg
The main of the study, as I interpret it, is marketing Coveo as a tool to facilitate knowledge management. Even though I write a monthly column for the print and online publication KMWorld, I do not have a definition of knowledge management with which I am comfortable. The years I spent at Booz, Allen & Hamilton taught me that management is darned tough to define. Management as a practice is even more difficult to do well. Managing research and development is one of the more difficult tasks a CEO must handle. Not even Google has an answer. Google is now buying companies to have a future, not inventing its future with existing staff.
The unhappy state of many search and content processing companies is evidence that those with technological expertise may not be able to generate consistent and growing revenues. Innovation in search has become a matter of jazzing up interfaces and turning up the marketing volume. The $10 billion paid for Autonomy, the top dog in the search and content processing space, triggered grousing by Hewlett Packard’s top executives. Disappointing revenues may have contributed to the departure of some high profile Autonomy Corporation executives. Not even the HP way can make traditional search technology pay off as expected, hoped, and needed. Search vendors are having a tough time growing fast enough to stay ahead of spiking technical and support costs.
When I studied for a year at the Jesuit-run Duquesne University, I encountered Dr. Frances J. Chivers. The venerable PhD was an expert in epistemology with a deep appreciation for the lively St. Augustine and the comedian Johann Gottlieb Fichte. I was indexing medieval Latin sermons. I had to take “required” courses in “knowledge.” In the mid 1960s, there were not too many computer science departments in the text indexing game, so I assume that Duquesne’s administrators believed that sticking me in the epistemology track would improve the performance of my mainframe indexing software. Well, let me tell you: Knowledge is a tough nut to crack.
Now you can appreciate my consternation when the two words are juxtaposed and used by search vendors to sell indexing. Dr. Chivers did not have a clue about what I was doing and why. I tried to avoid getting involved in discussions that referenced existentialism, hermeneutics, and related subjects. Hey, I liked the indexing thing and the grant money. To this day, I avoid talking about knowledge.
Back to the study. Coveo reports:
We recently polled R&D teams about how they use and share innovation across offices and departments, and the challenges they face in doing so. Because R&D is a primary creator and consumer of knowledge, these organizations should be a model for how to utilize and share it. However, as we’ve seen in the demand for our intelligent indexing technology, and as revealed in the study, we found that R&D teams are more apt to duplicate work, lose knowledge and operate in soloed, “tribal” environments where information isn’t shared and experts can’t be found. This creates a huge opportunity for those who get it right—to out-innovate and out-perform their competition.
The question I raised to myself was, “How were the responses from Twitter verified as coming from qualified respondents?” And, “How many engineers with professional licenses versus individuals who like Yahoo’s former president just arbitrarily awarded themselves a particular certification were in the study?” Also, “What statistical tests were applied to the results to validate the the data met textbook-recommended margins of error?”
I may have the answers to these questions in the source documents. I have written about “number shaping” at some of the firms with which I have worked, and I have addressed the issue more directly in my opt in, personal news service Honk. (Honk, a free weekly newsletter, is a no-holds-barred look at one hot topic in search and content processing. Those with a propensity to high blood pressure should not subscribe.)
Here are the Coveo findings which caught my attention:
- About half of those identifying their organizations top challenges pointed out that work was duplicative and that employees had no clue about who in the organization had information which would help another employee complete a task.
- “31 percent of respondents referenced an issue with too many systems, making it difficult to know exactly what information is available where and how to access it.
- 32 percent called out the issue of employee turnover and the loss of intellectual property as a hindrance, as current employees recreate previously completed work.
- “Accenting the insight deficit challenges within engineering and product development organizations, a mere 6 percent of respondents noted that they do not have an issue with information fragmentation, while 19 percent noted the confluence of multiple issues – geographically dispersed teams, lack of access to previously completed work, silos and employee turnover– as impediments to a more productive work environment.”
The conclusions in the news release summarizing the results was:
The collective knowledge of an organization is not only critical to its success, but is truly the competitive differentiator. Forward thinking companies are embracing advanced indexing technology, enabling organizations to access and share contextually relevant knowledge in order to collaborate in real time, and hence to go to market faster with more innovative products.
I applaud Coveo’s effort to expand the application of search into work flow streamlining. The company pioneering in this field, as I recall, was Tacit Software, which was acquired by Oracle. In the 2008 news release about that deal, Oracle asserted:
Tacit Software’s unique automated profiling technology is an expertise location solution that helps organizations uncover new opportunities for collaboration. Oracle plans to integrate Tacit Software into Oracle Beehive, a secure, integrated, standards-based enterprise collaboration platform. The combined solution is expected to enable enterprises to make effective and immediate use of the knowledge present in their people, messaging and content.
My recollection of Tacit is that it had promising technology which indexed email and other documents, tracked who asked whom for information so “influencers” could be identified, and provided a range of reports about information flow. However, I am not sure if the promise of the Tacit technology has been able to give Oracle the dominant position in collaboration that it sought four years ago. Oracle, as you know, spent billions acquiring somewhat complementary technology to perform search, content processing, and even advanced metatagging. Oracle owns the Artificial Linguistics technology, the Triple Hop technology, InQuira’s NLP technology, Endeca’s Guided Navigation technology, and RightNow with its Q-Go search and indexing technology. Coveo, therefore, may have a killer solution which will cause a company like Oracle to acquire the firm, or Coveo will have to find an opportunity which I think has eluded the formidable Oracle. Of course, Oracle may be a victim of the “too many cooks” problem or Oracle was just buying customers to whom to sell Oracle consulting.
Inefficient information access may be a practical response to contractual or government requirements, not an indication that the company is working in a non productive manner. An engineer without a need to know should not know.
With regard to information sharing and finding expertise, I think that sounds really great. The one possible sticking point is related to contractual requirements. What if an organization does consumer oriented work and work for a government entity requiring adherence to secrecy guidelines. The notion of making people and information findable may run into a problem if the information systems are audited by the government client. In the pharmaceutical industry, certain research methods enforce compartmentalization. The cost and risk of leaking information about key hires, compounds or equipment purchased, and information about certain tests or trials is closely guarded. In fact, the idea of making an expert findable in some research endeavors is the exact opposite of what management wants to happen. There are other examples as well, but the administrative work required to prevent information from turning up in an indexing system which just runs is formidable. One of the early knocks about the Google Search Appliance was that it would index indiscriminately. Some licensees were startled to find out what was in the index. Few organizations know what information is where and what exactly is available. The lessons of flubs in eDiscovery remind me of the joke “You don’t know what you don’t know” and “known unknowns”.
Finally, search vendors are looking for new markets. Customer support, sentiment analysis, big data, knowledge management, and dozens of other “markets” are being probed, tilled, prodded, and poked. Right now, finding customers is tough for several reasons:
- There are open source alternatives to proprietary search systems
- Search is just embedded in functions available from analytics firms like Digital Reasoning and others
- Companies are wary of on premises search solutions because of the scorched earth experienced when the Convera-type solutions were bought, test, and scrubbed.
- Big outfits like Microsoft are bundling search with other software solutions in order to get shelf space in companies
- Cloud options are available from well known companies like Amazon and from lesser known companies like Basho and Riak
- Purpose built solutions are available from firms like Artirix and Lucid Imagination companies which use open source technology to deliver search based applications.
Years ago, Business Week used to publish a table of Fortune 500 companies’ expenditures for research and development. I have lost track of that type of report. My recollection is that R&D is one of those line items which has long been a favorite of cost cutters. Google tried to squeeze some R&D value from its employees with its 20% time for personal projects, and that has gone away. Microsoft has moved some of its R&D to lower cost places such as China. In short, improving the productivity of R&D is a good idea, but the returns from indexing text may be less than the CFO wants or needs.
In my view, a company wanting to reduce research and engineering costs should take a look at the Inforbix technology. The company’s innovative system indexes engineering related content from specialized CAD systems, email, vendor quality assurance reports, and similar data sources. The idea is that an engineer will be able to run a query, locate related drawing files and identify specific technical facts quickly.
Based on our research into proprietary and open source search systems, general purpose search and content processing systems do not federate, index, and make findable binary, structured, and unstructured engineering data. Like Vivisimo’s claim to be a “big data” system, search vendors have to do more than say they perform a function. The system must do the function in a way that satisfies engineering users.
Stephen E Arnold, August 3, 2012
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