Use Cognitive Search to Power Your Research Portal
We used to think of knowledge workers as a few librarian-like employees responsible for managing all kinds of information. But information has become like currency: the more you have, the more you can do with it. And that means everyone has the potential to leverage information to perform their jobs better and increase the quality – and speed - of their decisions.
A research portal enables organizations to use their information to improve business outcomes. Whether it’s a financial institution that wants to give its financial managers or clients investment insights or an insurance company that needs to make all customer information available to adjustors, a research portal can help employees locate relevant information quickly.
The key to a research portal’s ability to surface the right information lies in how it manages the information. In the best portals, information doesn’t have to be located in a single repository; the portal instead unifies information silos across the company and provides a central location from which knowledge workers can search.
The ability to unify disparate information across repositories increases the chance of finding the most relevant information and speeds decision-making. It’s not just about unifying silos though. It’s also about surfacing the best information when it’s needed, sometimes before it’s needed, offering proactive insights.
When you put cognitive search at the core of your research portal you are doing two things:
- Unifying information silos from across the entire organization, so knowledge workers don’t have to spend their time searching in multiple locations, trying to correlate and derive insights from what they find.
- Consistently applying technologies such as machine learning, text analytics, and natural language processing to learn from the information, the queries, and interactions to improve the quality of the results surfaced, and even offer proactive insights.
Cognitive search is what helped UBS improve the ability to serve users of its wealth management, asset management, and investment banking services. UBS produces over 300 publications across a number of independent applications. It also maintains commentaries, research updates, meeting briefs and content for events, roadshows, and client conferences.
Looking for a way to unify these underlying information sources - structured and unstructured - and make it available to institutional clients, UBS developed Neo, a unified cross-asset platform that supports the entire investment lifecycle. At its core, UBS Neo uses cognitive search to index hundreds of data sources. Text analytics improve the findability of information by correlating information across data sources.
Neo also includes an ontology module that automatically applies UBS’s custom-built ontology for financial-related classes, attributes, and terms. Attivio’s cognitive solution’s ability to learn from information and how it’s used enables it to recommend additional tags for review and approval automatically.
We are used to asking Siri and Alexa a question and getting the best answer possible in our personal lives; similarly, we use Google to research and find answers to things we need to know. That expectation of immediate response - immediate right response - is something employees now expect in their business applications.
But providing that “right answer” isn’t straightforward. It requires an underlying cognitive solution like Attivio to connect the dots and surface the best information possible. Attivio doesn’t just unify information across silos; it applies machine learning and text analytics to understand the information, correlates it across repositories and learns as the solution is used to improve the quality of the answers returned.