Historical Challenges in Business Intelligence

This is the transcript of a Webinar hosted by InetSoft in October 2017 titled "What's New in BI." The speaker is Mark Flaherty, Vice President of Marketing at InetSoft.

Mark Flaherty: There have historically been three big challenges in business intelligence.

The first is BI adoption and appeal. There is limited adoption, and BI tools are known for being not that appealing. They look a little boring or intimidating. They are meant for power users or for when you are desperate to get to the data.

The next one is time to insight. Volumes of data are exploding. We have more and more granular data, click stream data, shopping cart data, and of course internal corporate data. People don’t want just quarterly summaries. They want intra-day updates. Trying to make sense of all this data and discover new opportunities, gain new insights at a faster pace is an ongoing challenge.

The third one is the concept of relevance, making BI relevant for more people.

Over the past few years, there have been a lot of innovations that speak to these challenges. The ones that are most interesting are ones that make BI more engaging, more insightful, and ultimately more actionable. Also important are any features that extend the reach of BI beyond the power users. Phrases like “BI for the masses” and “BI for mainstream” have been talked about for more than a decade now, and we’re still trying to get there.

So let’s list some of these innovations. The first is Web-based business intelligence where anyone with access to a browser can get to a report or a dashboard.

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Read how InetSoft was rated #1 for user adoption in G2 Crowd's user survey-based index.

That’s pretty mature. Some of the innovations like Flash and mobile BI are still emerging. Take dashboards as an innovation. They have been around for a while, but the degree that they are becoming more integrated with the whole BI platform and more interactive, that is drastically improving. Advanced visualization is another innovation. This is helping speed the time to insight. In-memory capabilities also fit in this category. Some of these innovations speak to that concept of BI appeal and greater adoption. And some of them apply to faster time to insight.

The last challenge area, relevance, that is not something that an individual technology can address. Instead, that is still something that takes BI visionaries inside the enterprise have to think about, where you try to flip the requirements definition process on its head. Whereas in the past, we’ve been very reactionary, waiting for the business users to ask for something, and then go off and build the solution. Instead what all BI experts have to do is study what drives the business, what matters most to improving revenues, improving customer service, and build solutions to that. Change that requirements definition process to make BI more relevant.