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Blog Downfall of dashboards, dreams of transparency: A response to Gartner 2020 trends


Gartner’s latest report analyzes and discusses the top ten trends in data analytics for 2020. The report begins by acknowledging the fragile state of the world currently. The trends they outline “will help to accelerate renewal, drive innovation and rebuild society over the next three to five years.”  The ten trends are outlined below and discussed in depth in the paper.

Narrative Science CEO Stuart Frankel discusses his thoughts and reactions to these trends below:

I found this report to be long overdue. It’s a great paper — spot on in nearly all the trends it identifies but these trends have been brewing for years and are not new to those of us who have been thinking about the future of analytics for the last decade.

Narrative Science has been on the forefront of many of the trends presented in this report. For years we have predicted that language would be the dominant interface between people and machines. We see this on the consumer side with the popularity of products like Siri and Alexa and consumer trends are often great predictors of upcoming changes in the enterprise. 

For us, there is no better proof of this than the fact that we have 150+ customers, most of which are large enterprises, integrating and using our products in their workflow.  

There is proof in this report which verifies what I, and many at Narrative Science, have been saying for years. The status quo is not enough for many people within an organization. Most people need more than dashboards and figures to comprehend their data. Everyday workers are not being given enough. They need tools that fit their needs in order to thrive.

The past few years have been a golden age for data analysts and data scientists. Analytics and Business Intelligence are a $35 billion market and almost all of this money is being spent on tools for this relatively small group of people in an organization. Everything has been for them. The challenge now, however, is that we expect everybody in an organization to be data-driven, not just the analysts and the tools that work so well for analysts are simply not extendable. These are not the right tools for salespeople, customer success people, medical professionals and almost every other worker. Gartner agrees and is now predicting declining dashboard usage and increasing usage of data storytelling tools over the next few years.

Besides Gartner’s prediction, there is a lot of evidence to support the bifurcation of the market into tools for analysts and different tools for everybody else. Dashboard usage is low and it always has been. Only about 30% of employees who have access to a BI tool actually use it. That alone should be evidence that the status quo is not working for most people. Analysts now spend over 60% of their time writing up analysis and reports instead of doing data discovery and ad hoc analysis in support of the business. Finally, the usability of enterprise applications is terrible when compared to consumer applications. Why is Slack so popular in the enterprise?  Messaging and collaboration tools have been around for years. It’s popular because it’s so damn easy to use. Shouldn’t analytics tools be the same? 

Moving forward, there will still be significant investment in back-end infrastructure, particularly as companies accelerate their transition to the use of applications hosted in the Cloud. However, I believe there will be (and should be) a new strong focus on the end user and their needs. This increased focus on the people who really need help will lead to breakthrough solutions that fundamentally improve data-driven decision-making. 

Another element of the report which is worthy of discussion is the concept of “responsible AI.”  Any discussion of responsible AI has to begin with the notion of transparency. We have long advocated that companies developing AI products and applications need to be crystal clear in terms of how their products work.  

AI is a powerful set of concepts and there needs to be systems in place to ensure that AI is being used ethically and for its intended purpose. AI systems need to be auditable so buyers and third-party entities can evaluate how an AI is making decisions. We can’t know where to start if we do not know how these things work.

Overall, the “Top Ten Trends in Data Analytics for 2020” is a comprehensive and robust report that inspires deeper thought into the future of analytics. I encourage everyone to read the report, and evaluate for yourself what the future of data analytics will look like.

Read the report here.

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