Answering employees' questions
Bouygues Construction is using Sinequa's Context Engine to put employees in touch with in-house experts who can answer their questions in a broad range of areas, says Eric Juin, the worldwide construction firm's e-services and knowledge management director. "It could be a lawyer, an engineer or an executive, anywhere in the world." The semantic platform identifies and categorizes all experience within the company, worldwide, by analyzing vast quantities of unstructured information, including training materials, project documentation and other internal sources, as well as Web-based newspapers and scientific publications, Juin says.
The platform is also being used to help knowledge workers quickly find information that resides either on internal systems or on the Web, Juin says. The semantic engine pores through documents, as well as comments from internal experts, and scores the material in terms of relevance to the user's query, he adds.
Juin says that while no hard ROI numbers are available, there's plenty of anecdotal evidence that the platform has helped Bouygues employees to avoid mistakes on construction sites by allowing them to rapidly contact people who can answer their questions. These anecdotes helped his staff cost-justify the deployment to management, he adds. Not that the project was expensive. It cost "just a [small percentage]" of the cost of Bouygues' ERP project, Juin says.
Tips from the trenches
Data housekeeping is a critical preliminary step, experts agree. "The extent to which content is enriched with good metadata [means] you can start to build applications that deliver on the promise of semantic Web," says Geoffrey Bock, an analyst at Gilbane Group.
Consultant Simon says he's worked on a number of projects implementing "breakthrough" information technologies, and he has learned that if you don't do housekeeping chores like cleansing and deduplicating data, "you just have better access to bad data."
Lee Feigenbaum, vice president of technology at Cambridge Semantics, advises IT and business people to work together to determine a project where semantic technology would yield "differential value." Will it speed up the development cycle? Enable end users to infer new data? Improve experiences for customers or partners?
Take things slow, at least at first, Simon advises. The project will reach critical mass as people get used to it and start to realize the benefits, he says.
Best Buy is doing just that. Its semantic Web deployment, which is about a year old now, is very much a work in progress, Myers says -- as is the semantic Web itself.
"There are lots of semantic tools and open-source projects out there, plus SPARQL is a really powerful query language," Myers says. "This gives me hope that semantic technology is at least one of the answers to the problem of Big Data. We have this large mass of data under our noses that we're not utilizing. If we can find a way to gain insight from it and pass that on to customers and business partners, that's a big competitive advantage."
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Editor's note: In an earlier version of this story, we mis-identified Michael Lang as CEO of a different company. We corrected this story around 1 PM eastern on February 22 to connect Mr. Lang with Revelytix, and we regret the error.