Enterprise Search Implementation Services
Experience, Pragmatism, and Best Practices for Enterprise Search Initiatives
WHERE DOES YOUR ENTERPRISE SEARCH PERFORMANCE STAND?
Most search engine implementations fail to deliver to their full potential – not through limitations in search software – but through a lack of applied expertise and proven processes.
Every organization has its own combination of data sets, user requirements and business goals presenting:
- Unique challenges, which can only be addressed by the application of experience and expertise.
- Common challenges, to which proven best practices can be applied.
By working with Search Technologies, you will ensure that these challenges are anticipated and dealt with. The result is lower project risk, lower total cost of ownership, and a search solution that fully supports your business objectives.
THREE COMMON CHALLENGES TO ENTERPRISE SEARCH
For illustrative purposes, three typical challenges to successful enterprise search implementation are summarized below.
1. Search Quality
So the plumbing is installed, your datasets have been connected and indexed, and the search capability fundamentally works. But users complain about poor results and difficulties finding the information they need.
Most of the leading search engines have the functionality to deliver great search results, but to achieve consistent results quality is it necessary to:
- Match relevancy ranking to the company's (unique) data-sets.
- Implement engine scoring processes to ensure that search quality is maintained as corporate data evolves.
- Take care to ensure that disparate data sets "play well together" behind a single search box.
- Improve search for documents in foreign languages using advanced multilingual text analytics.
- Use AI technologies like Natural Language Processing and Machine Learning to enhance the search and analytics experience.
2. Complexity Management
For large enterprise search projects, complexity poses a significant threat. Deployments are typically rolled out one data set (or one business application) at a time, and with each new addition, complexity grows. Inter-dependencies cause complexity, and time-saving shortcuts made earlier in the project close options and limit flexibility. Complexity-creep is the leading cause of large project failure.
Complexity can be managed through forward planning and the application of best practices to design and implementation.
3. Connector Maintenance
Real-world issues pose challenges to the implementation and maintenance of connectors. For most data repositories, off-the-shelf connectors require configuration. Connector performance can be problematic causing incomplete or failed indexing. This is often not the fault of the connector, but is caused by dependencies on the target repository.
Connector implementation, monitoring, and maintenance can be simplified with the right approach.
Contact us to start assessing your enterprise search strategy and defining your implementation or improvement plan.