What Do Employees Gain from Using Advanced Search Analytics?

We have become accustomed to finding an answer to any question in seconds – all it takes is a mobile device and an internet connection. Entering queries into search engines multiple times a day is now second nature — whether it’s the height of an actor in a show you are streaming, the latest update on a current event, or fact-checking a piece of trivia someone just dropped on you.

A similar proclivity for search has developed in the workplace. This is especially true as more organizations work to become data-driven. Enterprises can use search-based data analytics to connect employees with the information they need to understand performance and make informed decisions.

Table of Contents 1 Introduction 2 What is Advanced Search Analytics 3 Wider Data Accessibility 4 Natural Language 5 Drill Down to Insights 6 Reporting Backlogs 6 Conclusion

 

What is Advanced Search Analytics?

 

We can use various tools for selecting, extracting, cleansing, and understanding content gathered from various sources including the Internet. The processed data can be used for your own business for building/integrating custom search, analytics, and business intelligence (BI) applications. The downloaded content can be fairly structured data with metadata fields and values, have categories and tags.

Here is what the advanced search-driven analytics available today offers employees.

 

Wider Data Accessibility

 

Imagine if, every time you had a question, you had to write it down and submit it to someone else so they could find the answer for you. This is the way it worked in the not so distant past. Researchers had ongoing relationships with their local librarians.

There were times when said researchers found themselves waiting for a while when librarians were swamped with requests. This lead to the need to be far more selective about the types of information sought. Further, what you saw was what you got. Follow-up questions would kick-start the process all over again. As you can imagine, this was a very inefficient way to handle search queries.

In much the same manner, data analytics used to be the domain of the IT team complete with siloed information and restricted access for non-specialists. All of the pitfalls described above-held employees back from getting answers to all the questions they had on a daily basis. This is why there’s been a shift toward data democratization, empowering employees to freely access data without having to work through gatekeepers.

Access to self-service search analytics enables employees to query data directly at any time they have a question or the need to create a chart or a dashboard. Wider data accessibility throughout an organization paves the way for higher adoption rates as employees start to incorporate data into their regular workflows.

 

The Ability to Ask Questions in Natural Language

 

There are a number of ways for employees to harness search-driven analytics these days. The most common is typing queries into a search box; the second is speaking queries aloud to a conversational analytics platform. Both forms of search harness natural language processing (NLP), which enables employees to ask straightforward questions in plain speak rather than needing to input anything in a programming language.

 

The Ability to Drill Down into Insights

 

One challenge associated with gatekept data, as we mentioned above, is the fact that static reports are — static. There is little opportunity for drilling down, even when follow-up questions are needed to fully understand an insight to unlock the data’s true value.

Another component of today’s advanced search analytics is its ability to automatically produce interactive visualization models. Instead of accepting a “what you see is what you get” mentality, employees can drill down into the details to examine data from different angles. After all, it sometimes takes a bit of digging to reach that “aha” moment.

 

Reduced IT Reporting Backlogs

 

When employees can ask questions anytime using search analytics, IT reporting backlogs drop. This frees up data specialists to work on strategic projects beyond creating reports for other teams. Search-based data analytics empowers employees to ask questions in natural language and drill down into data on their own, with no specialized data knowledge required.

 

Conclusion

 

If we build/integrate search, analytics, and BI applications the combination of web data mining tools and techniques, perform continuous quality analysis and improvement then sustained performance will be assured. However, instead of using own resources (server and manpower), there are many ready to use IT services which do the job more efficiently in a cost-effective manner. An employee without proper tools is powerless manpower of a business. The gain of insight by the employees essentially improves the overall quality of the business which possibly will increase the revenue.

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