Can Intelligent Search Solve Information Governance Challenges?
Intelligent search is a primary component in information governance and should be treated as a core infrastructure requirement, driven by executive management. When effective, intelligent search forms the basis of improved organizational performance and touches discrete applications that together meet the tactical objectives of an overarching information governance strategy. When search doesn’t work, information governance as a whole is undermined and can negate any benefits, affecting the ability to achieve organizational objectives. Without risk assessment and policies that apply to enterprise search, a Pandora’s box of problems is opened.
Search covers a broad spectrum of business processes. Not only to identify relevant information required for business users to perform their responsibilities, but also in the retrieval of documents of record, prohibiting access and protection of confidential or data privacy content, text analytics and the various applications that rely on accurate search, such as eDiscovery, litigation support and FOIA. At an equally important level, ineffective search affects customer service and sales. The result of ineffective search negatively impacts the bottom line, and increases organizational risk as well as the cost of doing business.
Organizations can no longer support the theory that the search engine will solve all findability issues. At the organizational level it is a risk and compliance issue. The traditional approach to improve search continues to fail. Until organizations realize that unstructured and semi-structured content must be managed just as database applications are, implementing effective search is impossible. Which search engine the organization deploys is actually irrelevant, as most deliver similar capabilities. What really matters is the ability to provide rich and meaningful contextual metadata that, when consumed by the search engine index, will deliver a more intelligent search experience for the end user. This improves information access, as well as ultimately playing a key role in information governance for the organization as a whole.
Intelligent search can be achieved when the organization is willing to commit to the development of an enterprise metadata repository. Quite simply, metadata matters. This information governance stumbling block is, and always has been, the lack of metadata—subjective metadata—and the role of the business user as the primary author of metadata. Cumbersome drop-down lists and forcing metadata management on the business user doesn’t work and never has. Automatic semantic metadata generation eliminates business user tagging. The metadata framework can then address information complexity and effectively increase information accuracy, by providing the ability to manage content regardless of where it resides, normalize vocabulary, eliminate the silos of diverse content repositories and create a consistent framework available to any application that requires the use of metadata. The key to meaningful metadata is the ability to extract concepts from content, eliminating the keyword or proximity approach and the totally automated approach that prohibits the management and tuning of metadata to improve search results.
Metadata alone cannot deliver intelligent search but it is the primary enabler. Adding auto-classification of content and taxonomies provides a flexible and complete solution that can be managed to address multiple application requirements. For many years, organizations have struggled with taxonomy development, which has traditionally been viewed as a cumbersome, resource intensive and lengthy process to not only develop but also maintain. The ability to automatically classify content based on semantic metadata removes many of the challenges in taxonomy development and offers both IT and business users the ability to easily manage taxonomies, where changes can be tested in real time and the tools provide an interactive interface to visually identify concepts and develop business rules to improve the relevancy of search.
From an intelligent search standpoint, the hierarchy as defined in the taxonomy and presented to the business users from the search interface greatly aids in the search process. Adapting to both location and discovery searches, location queries deliver the most relevant information and discovery queries are presented with similar concepts and information that typically would not be found. The use of the taxonomy delivers improved search outcomes by providing insight into content: grouping similar users, concepts and relationships together. The end result is consistent understanding of the value and context of information that is instrumental in improving business outcomes and reducing organizational risk. The hierarchy of the taxonomy identifies similar content and relationships that are typically not obvious in the search process. This is important as it guides the user through parent/child relationships, resulting in more relevant information being identified more quickly. This fundamental change through the search interface affects user activities and transforms it from searching to insight and discovery.
Many organizations have different search engines deployed within the organization. The ultimate goal should be the deployment of the enterprise metadata infrastructure component that manages information regardless of the search engine or where it resides. From this enterprise metadata repository, taxonomies can be rapidly deployed and developed to support specific audiences and functional groups. This achieves a consistent internal and external vocabulary and is easier to maintain, as the content can be managed within the context of the business delivering business process improvements, and makes a positive impact
on the bottom line. As a key component in information governance, intelligent search provides secure and compliant access to information and creates the backbone for the deployment of intelligent metadata-enabled solutions that support the overarching information governance strategy.
Concept Searching specializes in semantic metadata generation, auto-classification and taxonomy management, and has a Microsoft Gold Application Development competency. Its technologies encompass the entire portfolio of unstructured information, in on-premise, cloud or hybrid environments. Clients are using the technologies to improve search, records management, data privacy, migration and text analytics. For more information: www.conceptsearching.com