In these unprecedented times where you don’t have your colleagues available on the next desk, searching for that one doc that you discussed on that one Zoom call that Friday is a challenge bigger than ever before. According to McKinsey, employees spend 1.8 hours every day on average searching and gathering information. Your organization loses valuable working hours in search-related activities.
Why it takes this long might have to do with bad UI or siloed experience overall. Employees shouldn’t have to search on five different applications separately to be able to find what they are looking for. Enterprise search must evolve to become actually helpful and not time-consuming.
An effective enterprise search tool needs to be unified, scalable, flexible, secure, and intuitive and accommodating of today’s employees’ needs. It can help employees make informed decisions and the organization gain a competitive edge. In this blog, we will explore the critical capabilities of a modern enterprise search.
1. Search Capabilities: Keywords, Faceting, User Data
Legacy solutions require users to enter a specific syntax in order to get the results they actually wanted. Modern search parsers, however, can function without this specificity. This allows for a better user experience without the struggle of finding the right keywords.
Faceting refers to the ability of sorting results based on a specified field. As most search solutions allow to define synonyms, implementors can now adapt user queries to their corpus of data.
Another key search capability involves analyzing user data. This data includes users’ behavior and interactions with other business apps like Teams, SharePoint, Outlook enterprise search, natural language conversation solutions like chatbots and so on. The solution analyzes this data and might be able to provide recommendations later based on the same.
2. Recommendations and Smart Suggestions
In providing recommendations, it’s not enough to just suggest what results the users often searched for, at large. AI-powered recommendations have now evolved to give recommendations based on the interests and search behaviours of other users who share similar profiles as the intended user. Giving weight to context as well as the user, recommendations can become far more relevant and provide users with what they want at the right time. Recommendations should also be based on the user persona i.e users’ interests, locations, roles, preferences etc.
Search engines should also provide a rich user experience with auto-complete, smart suggestions, geospatial search, filtering and faceting features.
3. Supports Conversational, MultiMedia, Multilingual Searches
A modern enterprise search should support different search types including:
- Conversational search: The ability to conduct natural language searches (Google or Bing-level search experiences) with the enterprise search on the intranet or a chatbot or voice bot and access information seamlessly via text or voice mediums.
- Multimedia search: Enterprises collect huge amounts of image and video content that are usually not searchable. A modern enterprise search needs to be equipped with AI and NLP to convert this unstructured data into searchable content. In addition, it also should leverage custom AI vision services such as Azure Custom Vision to identify objects like people, places, text etc. that may be present in images and videos.
- Multilingual Search: The ability to deliver search results in multiple languages and cater to the language needs of employees across the globe.
You can implement a great enterprise search solution but its success depends on user adoption which relies on how intuitive and user-friendly the solution is. The platform should be designed for the user and have a world-class user interface. The solution should also provide user-friendly options like filters with which users can improve their search results.
5. Operational Capabilities: Scalability, High Availability, and Disaster Recovery
Scalability is one of the must-have capabilities for your enterprise search solution. It’s imperative that the solution is able to scale with the increasing number of users and doesn’t crash or lag with more data. In implementing enterprise search solutions, organizations must consider future-proofing it based on their estimates for the coming years.
Other capabilities like high availability and disaster recovery are also important in the event of network outages, fibre cuts, or any calamity. Your organization’s preparedness for such unprecedented events can minimize chances of data loss or downtime.
The Importance Of Upgrading From Enterprise Search To Cognitive Search
Modern enterprise search platforms ensure security especially given the large quantities of data that they deal with. Some of the practices include connectivity to major security technologies, role-based security authorization, and document-level security. By limiting access to only the people that need it, enterprises can optimize security. Users don’t see the documents or any type of content stored in backend applications for which they don’t have access to in their search queries.
7. Analytics Capabilities
Search analytics can provide information on user behavior and what they are looking for. These analytics give implementers insights into how users are interacting with different functions. They can even inspect actions of an individual user if needed. With the help of the analytics, they can also realize their conversion goals and see how things are changing over time. They can take steps to improve user adoption and make user experience more effortless.
8. Data Sources
In choosing an enterprise search platform, organizations must ensure that it supports the data sources that they currently have in place today and in the future. It doesn’t matter how many data source connectors the solution supports if it doesn’t support the ones you have deployed.
9. Advanced Capabilities
Search solutions usually show the most relevant results at the top but that can be resource-intensive. Streaming enables the platform to display results in the order that they are actually retrieved but based on the defined conditions.
Named entity recognition, clustering and classification, and head/tail analysis are some AI/ML techniques that can be useful for faceted searches, grouping queries, and improving underperforming queries, respectively.
Find Information Faster with Modern Enterprise Search
In choosing an enterprise search solution for your organization, you must also consider the capabilities of your vendor. Can they customize the solution to meet your employee needs? Can they partner with you to understand the nuances of your organization and deliver on time? Have they done this before for someone like you? What are some of their best practices from the industries they have worked with?
At Acuvate, we offer intelligent cognitive enterprise search that is integrated with an autonomous intranet. You can connect all your internal and external enterprise apps together and have a unified search engine to access relevant org-wide knowledge from within your intranet. Our cognitive enterprise search solution leverages Microsoft Cognitive Services and Azure Machine Learning services to provide personalized and highly relevant search results.
If you would like to experience the power of enterprise search and watch our SharePoint intranet, Mesh in action, get in touch with one of your solution experts for a short demo at your convenience.