This post is the first of a two-part series on enterprise search and discovery technology and use cases.
With so many employees working remotely, the need to easily and efficiently access information to drive business performance has never been greater. Unfortunately, with the explosion of data sources, the ability for enterprise data architects, analysts, and engineers to process these inflows with speed and precision continues to be challenging for many organizations.
Research clearly shows that enterprises that prioritize data search and discovery are more productive and innovative. However, the path you take to powering your search and discovery capabilities can have a material impact on the level of success your enterprise can achieve.
In this post, we will define enterprise search and discovery, examine its importance to employee productivity and innovation, and introduce a few of the most common use cases.
Enterprise search is:
Data search and data discovery are related but not the same. Search is when you find information, discovery is when information finds you. For example, when you search for engine parts and the search application discovers additional related information to assist you, such as instruction manuals and group discussion forums. Deploying an intelligent content discovery system, also known as an “insight engine,” goes beyond buying search application software and usually requires organizations to change the way they integrate and curate data for improved outcomes.
Insight engines combine search with AI technologies to expand the ability to search intelligently across data silos. They incorporate elements of semantic and machine learning to enhance knowledge discovery and exploration.”
Marydee Ojala, Information Today Inc.
At their zenith of performance, search engines surface relevant content when, where and how employees need it. Minimizing the effort required to achieve this maximizes the value to the business.”
Gartner – Improve Search to Deliver Insight
Although search and discovery has come a long way thanks to intranets and the advent of enterprise search systems, the reality is that employees still struggle to find the information they need, and are dissatisfied with search functionality. As data sources and data volumes continue to grow, so will these challenges.
By 2025, IDG projects that there will be 163 zettabytes of data in the world, and estimates indicate that 80% of this data is unstructured. Without a modern approach to data integration and governance, enterprises will continue to fall short in providing employees with the best possible search experience. Removing search and discovery limitations can have significant impacts on business performance in areas of productivity and innovation.
Your employees spend considerable time searching for data and information to do their jobs. According to a study by RingCentral, employees lose over one month per year (~32 business days) just switching between applications, folders, and databases in order to find the information they need. Although not always apparent, the financial costs to enterprises from productivity “losses” can be material. Inefficiencies resulting from sub-optimal search and discovery can cost enterprises millions of dollars in lost productivity, duplication of efforts, and employee turnover.
Providing employees with access to the right data at the right time spurs insights and innovations. It can also help executives make timely decisions about project funding. With the amount of capital poured into research and development and other innovation projects, enterprises must invest in the optimal search and discovery systems to maximize outcomes and gain a competitive edge.
We see enterprises across all industries using search and discovery functionality to solve problems and develop opportunities horizontally and vertically within an organization. Here are some examples of common use cases for enterprise search and discovery:
Behind every great enterprise innovation is an effective R&D process. Powering those R&D processes are the best systems and practices for data search and discovery. Research hubs, such as those used to improve product development in life sciences, manufacturing, and investment services, are examples of business use cases that benefit from enhanced search and discovery.
Improving productivity means having access to unified and actionable data to run your business. Compliance functions are often required to conduct internal research for new regulatory requirements and ad-hoc requests and must have access to enterprise-level data that is accurate and up-to-date. Human Resources is another area where better data access enables improved analysis needed to support organizational agility, and unleash productivity and innovation.
Enterprises in nearly every industry publish external content for sales, marketing, and servicing purposes. Some enterprises, such as those found in the Media industries, must monetize their content to thrive. For these enterprises, the ability to rapidly search and discover data and curate differentiated content for their customers is mission-critical.
In the next part of this series, you’ll find out why a data hub is the right platform for developing your search and discovery applications, and how leading companies have deployed a MarkLogic Data Hub to develop best-in-class search and discovery solutions.
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