2022-05-26 00:00:00
7 min read
Although BI tools are being widely indoctrinated into a company’s tech arsenal, their usage and adoption still leave a question mark on the validity of the BI investment made. Some of the common reasons why Business Intelligence tools are not being adopted company-wide are:
1. Insights production is slow - Assuming, as is often the case, that a business manager needs such a query answered as has not been covered in the original dashboard scenario. The back-and-forth between the business team and the analysts to acquire the right information points will run well past the due date of the usability of that information point
2. It is difficult to understand what the data is saying, even with the help of these tools - This can primarily be attributed to the ‘visualizations as answers’ approach of many, even popular, dashboards. The data is decoded as charts; now who’s going to decode the charts? (Narrative-based insights might help)
3. The insights produced are not action-oriented - Retrospective dashboards do not solve prospective business problems. Dwelling in the past doesn’t bode well for anyone - be it a person or a dashboard (that’s right - we covered your daily dose of motivation too)
4. The interface is so tech-oriented, professionals from other specializations go ‘I’m better off without this’ - The rejection of non-tech people to use BI tools is wholly the fault of the tool - and this is a mindset that is missing in most enterprises. Providing technology and providing accessible technology are two very distinct activities that an enterprise undertakes. The former creates a hindrance in the formation of a data-driven culture
NO ONE DENIES DATA
There is no denying that the importance of data in decision-making is ingrained in people’s minds - no one denies a solid data-backed observation, once it is made. It stands to reason that the issue is not one of not having the data or the tool/s to extract actionable insights from it - neither is it the mental resistance of accepting hard data-based decisions
The problem seems to be of a more tangible nature. The right kind of BI Tool, complete with both the right capabilities and user interface, should foster a culture where every individual actively uses data to make everyday decisions, and realizes the value of BI tools in helping make sense of data.
WE HAVE REDUCED THE SOLUTION
To 4 points. Here are 4 features that every BI Tool should possess:
1. Narratives
Vivid visualizations are good, but if a company truly wants its business leaders to make data-based decisions, language-based insights (narratives) are the way to go.
Insights in natural language are welcomed by business users, who simply read and understand what’s going on, and use the understanding to formulate great business decisions.
A ‘visualizations-only’ dashboard is one of the biggest reasons for low dashboard adoption rates too, something that language can easily solve.
Concluded: A BI tool MUST have language generation capabilities to drive enterprise-wide BI adoption.
2. Going Beyond Visual Drill-Down
Do not stop at the introduction of language-based insights at the entry level. Some BI tools (like Phrazor) provide insights in language at every data level one explores!
Advanced features like
- Customizable visualizations at any data level
- Dynamic narratives i.e. narratives adapting to the visualization type selected
are possible in Phrazor. This is a boon for business users who can conduct ad-hoc analysis on the spot, without queuing up and waiting for weeks to get their questions answered. Greater independence in interacting with data can also be easily observed among business users using Phrazor to conduct data drill-downs
Concluded: Faster time-to-insights requires business users to conduct ad-hoc queries on the spot. Narrative-based drill-down provides business users with the independence to interact with data on their own, and extract insights then and there, or as the French say it, tout de suite.
3. Related Insights - A BI Tool’s Detective
Added intel from an expert authority is always appreciated. Automated data surfacing models present in some BI tools will sift through the underlying data pool and surface relevant insights in real-time. The below example shows ‘Related Insights’ surfaced by Phrazor in response to the question asked.
Concluded: There are many crucial insights, which, for all the meticulousness in insight derivation, can be overlooked. Here, it is up to the capabilities of the tool to be able to surface hidden insights and detect anomalies and outliers
4. A Conversational Querying Platform!
Conversational querying platforms are empowering business users to create relevant dashboards all on their own - via simple chatting, and in just 4 steps.
Phrazor’s conversational querying platform, Ask Phrazor,
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Allows syntax-less querying, meaning users can ask questions in a human manner without worrying about codes
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Generates answers in language, in real-time
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Recognizes industry-specific jargon and allows forming your own set of KPIs to be used in queries
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Allows multiple teams to collaborate on the same project through a chat-type interface, not unlike Google Docs
These are our 4 must-have features in any BI tool, to provide actionable insights instantly and foster a data-driven company culture by enabling every professional to extract insights and create dashboards on-the-fly, all on their own
Interested in a Phrazor walkthrough? Book a no-obligation demo here!
About Phrazor
Phrazor empowers business users to effortlessly access their data and derive insights in language via no-code querying
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