For Enterprises Struggling to Get the Most from Their Data, It’s Time for Cognitive Search
All organizations are notorious for hoarding data. Whether it is research data, customer data, marketing data or another type of data, businesses are savvy to the power of data-driven insights and are keen to hold onto whatever data they can glean in case it could provide business value through analytics.
However, with so many datasets for different types of data, relevant data can quickly get lost in siloes, which makes it increasingly hard for employees to find the information they need to work smarter and more productively.
The trouble with that is that it is about to get a lot worse.
Unstructured data is taking over. Data is no longer only found in conventional structured Excel spreadsheets or Word documents, it is now present in a whole range of formats, from audio and video files, to slides from a webinar or a link in a Slack conversation. Unstructured data represents the majority of data used today, according to IDC and is expected to continue growing at a high rate.
Much of a company’s structured data is seen as “dark,” or untapped, because it is stored in multiple siloes and has poor tagging, making it increasingly difficult for search tools to find amid all the clutter.
What is cognitive search?
Enterprises that have large stores dark data are already wondering how that situation will worsen as more unstructured data is created and stored. When a company’s valuable insights are locked inside a plethora of formats which conventional search technology finds impossible to interrogate, it will be the businesses that have invested in cognitive search that will assume a competitive advantage.
Unlike the systems used by most enterprises today, cognitive search does not rely solely on tagging and keywords to match with what an employee is looking for.
Instead, the new field uses artificial intelligence to understand data and connect it with the people who need it. With cognitive search, an enterprise is not reliant on someone calling a file by the right name and saving it in the right format within the best folder on the correct server. Organizations employing cognitive search to connect all content -- both text and data – derive meaning, learn from user interactions and present information in context. This solves content chaos and informs employees through a single, secure interface. They get the knowledge, expertise and insights needed to make informed decisions and do more, faster.
This means employees always have the latest up-to-date information at their fingertips without having to try multiple searches which still fail to pick out the right data because it was not included in a tag or saved within a specific folder.
The inconvenient truth is that with existing mainstream search options, nobody knows what they do not know. If a search does not come back with the most relevant information, the staff member has no way of knowing there is a hidden finding or discovery that could greatly help their work. If your data is dark, your people are left to work in the dark, too.
How can enterprises gain from cognitive search?
This can mean different things to different industries and different roles. Customer services staff, for example, can spend less time trying to work out a customer’s background or purchase history and quickly attend to issues with all the necessary facts at their fingertips. In retail, customers get relevant recommendations based on what they have previously purchased and what the latest items are, in which size, and in which stores.
In healthcare and life sciences, drug discovery becomes accelerated when researchers have all the relevant data at hand. To get a sense of the scale of the problems these businesses face, some life science leaders are struggling to connect over 15,000 researchers to the insights stored away in more than 180 million documents, across multiple systems.
Similarly, leading financial service providers are finding it difficult to make sense of thousands of fund sheets produced each month and turn them into client insights. With cognitive search, they readily have the insights they need and find value in additional unstructured data, which they previously could not leverage. This means queries are answered more quickly and better investment choices are spotted sooner for their wealth management clients.
In manufacturing, cognitive search can streamline processes and boost productivity. By putting the right information in front of the people who need it most, the average knowledge worker in the sector can save 18 hours per week, according to IDC research.
Improving strategic decisions
All enterprises can make better strategic decisions when armed with insights from the dark data that they did not know they possessed. Not only does cognitive search unearth the hidden data and make unstructured data searchable, but it also enables enterprises to boost employee satisfaction by giving people the tools to work smarter and more efficiently, rather than spending hours inefficiently trying to find the information they need to do their jobs.
With the expected growth of unstructured data that leading enterprises will have to decipher and glean insights from in the future, it becomes clear that AI-driven search is the key to improving efficiency and boosting innovation.
About the Author
Alexandre Bilger is the president and CEO of intelligent search platform vendor, Sinequa. Bilger is passionate about cutting edge technologies including AI, machine learning, cognitive computing and natural language processing. Prior joining Sinequa, Bilger co-founded and served as CTO for E-Front, a data-processing software vendor specializing in the financial industry. He started his career as a lead architect at NAT System, a leading client server development tools vendor. He graduated from Ecole Polytechnique and the Ecole des Mines in France.