Enterprise search is plagued by a myriad of problems. When users try to find documents, they are often frustrated by the search results that come back. They may not even know what they’re looking for.
A new breed of enterprise search solutions is emerging, however. These solutions offer semantic analysis and machine learning to provide more intuitive and relevant results to users.
Enterprise search is becoming more important for organizations of all sizes, but it can be difficult to get the right solution in place. In this article, we’ll cover key requirements for an enterprise search solution and discuss how our own approach to enterprise search has evolved over time.
Here are the 10 key requirements an organization must look for in an enterprise search solution:
1. AI Powered Enterprise Search:
Among the many benefits inherent in a good enterprise search solution, the most important is that it is able to automate many of the search tasks. This is enabled by the capability of intelligent search.
When the system has enough knowledge to predict the possible next steps given a set of known facts, it can effectively automate many of the common search tasks.
2. Queries Both Structured and Unstructured Data:
Most enterprise information systems today do not store their content as structured data. Most of it is stored as semi-structured or unstructured data. It would be desirable for an enterprise search engine to address both types of data.
Structured data can be queried with SQL like queries whereas unstructured data can be queried with regular expressions and other parsing techniques.
3. Understands Natural Language:
A good enterprise search engine should understand natural language queries and should be able to match them against the content stored in their database. This is necessary because users are usually not adept at using complex Boolean or keyword queries, or even syntactically correct sentences to describe their intent when performing searches.
A majority of the users rely on natural language rather than proper syntax to express themselves in natural language queries. Such capabilities will make an enterprise search engine more human-like and hence provide users better productivity gains over time.
4. Moderate Cost:
Creating an enterprise search engine is not a simple task. It requires huge investments in terms of both human resources and technology. Hence, it should be expected that an enterprise search solution would come at a moderate cost.
The cost of an enterprise search solution would also depend on the number of documents they have to process as well as the number of users they have to service.
5. Minimal Human Effort:
An effective enterprise search solution should minimize human intervention in the process of searching for information. Human effort is required to create new indexes and maintain the content of the indexes. It should also minimize human effort required to train the users to use the system effectively.
6. Minimal Deployment Time:
An enterprise search system is a long-term investment. When deciding to implement a search system, it is important to consider the time and resources required for the initial deployment, as well as the ongoing maintenance of the solution.
An effective enterprise search solution should optimize the overall time to deployment and minimize ongoing maintenance efforts.
7. Applicable to all Workflows:
Organizations are increasingly adopting an agile approach to development and operation. As such, an effective enterprise search solution must be able to support a wide range of workflows, from traditional waterfall development models to highly dynamic Agile/scrum methodologies.
This requires support for both structured and unstructured data sources, which typically require different query and indexing techniques.
8. High Level of Accuracy:
Upon implementation of an enterprise search solution, it is important that users are presented with relevant results in a timely manner. An effective enterprise search solution should provide high levels of accuracy across all content types and languages.
This is especially critical in regulated industries or when information may have repercussions on people or organizations (e.g., medical or legal). For example, an effective enterprise search solution will be able to ignore stop words and provide results that are highly accurate for complex queries involving multiple terms.
9. Continuously Learning:
An effective enterprise search solution will learn about its users and their evolving workflows on an ongoing basis in order to continuously improve relevance scores for future queries and content sources.
An effective enterprise search solution should also be able to maintain relevancy scores over time without requiring constant reindexing of content sources or data changes within those sources. This requires supporting the ability to monitor user behavior at the query level, as well as the ability to monitor user behavior across multiple queries in aggregate form.
A secure enterprise search solution will protect information by allowing only authorized people access to data while ensuring that sensitive data is not inadvertently exposed through search results or otherwise through archiving/retrieval processes (such as SharePoint). It will also protect against unauthorized modification of indexed data by means of controls on data input, data modification, and data output.
The characteristics of an effective enterprise search solution are not easily met, which is why organizations should carefully consider their options before implementing a new search system. Establishing the right balance of features, functionality and cost can be difficult. However, by following the guidelines above, organizations can ensure that they are making an informed decision before embarking on a major search implementation.