Business Intelligence Is Dead, Long Live Business Intelligence

March 29, 2016 Jeff Kelly


sfeatured-BIdead-BIlivesWell, it had a good run.

Since Gartner analyst Howard Dresner coined the term in 1989, business intelligence (BI) has consistently ranked as a top priority for C-levels across industries. A multi-billion dollar market for BI tools and applications evolved to meet the demand. Enterprises continued to prioritize investments in BI for years, helping them gain better visibility into their business operations and improve decision-making.

Those were the good old days, but it appears those days are over. At the Gartner Business Intelligence and Analytics Summit in Grapevine, Texas earlier this month, analyst Frank Buytendijk declared in his keynote address that BI, for all intents and purposes, was dead (Buytendijk probably should have alerted the Gartner events team beforehand, who could have removed “Business Intelligence” from the name of the show). The public markets, too, are in the process of reassessing the BI market. Former market darling Tableau Software has lost over 50% of its market cap since the beginning of the year. And just this week it was revealed Qlik is exploring a sale after pressure from activist investors.

So what gives? Why is BI, once the savior of the enterprise, suddenly the recipient of such scorn? Is BI really dead? And if so, what will replace it?

OK, So Maybe BI Isn’t Dead

To paraphrase Mark Twain, the reports of BI’s death are greatly exaggerated. Enterprises still require BI applications and data visualization tools to gain a deeper understanding of their corporate data. Think about your enterprise. What do you think would happen if tomorrow, the reports and dashboards you and your colleagues rely on to monitor the business suddenly vanished? There would be chaos. It would be the corporate equivalent of Lord of the Flies.

The vendor landscape likewise suggests the BI market might still have a few years left in it. Despite its shrinking market cap, Tableau still grew revenues 58% year-over-year in 2015 to just over $650 million. Qlik, while not growing as fast as Tableau, likewise topped $600 million in revenue last year. Not bad for two companies in a “dying” market.

The reality is that BI applications and tools continue to provide some degree of value to enterprises nearly 30 years after their emergence. However …

The Two Big Reasons That BI Is Less Relevant

In today’s world, unlike 30 years ago, BI is no longer the star of the data management show. Rather, today’s BI is just one component—and an increasingly less critical component—of a modern, Cloud Native platform that enterprises require to truly derive maximum value from their data.

There are two reasons that traditional BI is less relevant in 2016 than it was in 1996.

First, BI tools are great at telling you what happened last week, last month, or last year. How many red widgets did your company sell in the midwest between June and September of last year compared to the same period a year earlier? Just about any BI tool can provide an answer (assuming it has access to the relevant data) using an assortment of visualization techniques. In recent years, modern BI tools have added some level of predictive analytics capabilities, allowing enterprises to forecast how many red widgets it will likely sell depending on any number of predictive variables. Good stuff, indeed.

In today’s consumer-centric world, however, enterprises need more than just insights into past performance or even forecasts into future performance to compete. Start-ups, without any legacy infrastructure holding them back, are emerging across vertical markets that use software, data and analytics to deliver highly personalized services to consumers. Think Uber in the taxi industry or Netflix in entertainment. These companies are first and foremost software companies with highly data-driven businesses. They use software, such as MPP analytics databases and in-memory systems, to mine massive volumes of data, from multiple sources, for actionable insights, and operationalize those insights through smart, often real-time applications—also called delivering information in context.

Note that the Ubers of the world surely rely on BI tools to monitor the day-to-day business and to forecast likely revenue, profit and other metrics in the future, but they don’t stop there. They have also mastered the art and sicence of delivering information in context to their customers, partners and even their own employees, depending on the use case. Traditional enterprises need to learn to do the same if they want to compete and win in the digital economy.

Which brings us to the second reason BI has lost some of its luster in recent years. Traditionally, BI applications and tools were available only to the privileged few, usually the C-suite and upper management, in any given enterprise. For the last decade, the concept of self-service BI has been sought by companies, with its promise to democratize data and make it available to rank-and-file workers. But still, depending on which study you rely on, adoption of BI applications and tools in the enterprise tops out at between 15% and 25%. BI Scorecard pegs adoption at 22% in the average enterprise. That leaves a lot of employees, not to mention partners and customers, without access to potentially valuable insights.

Operationalizing Data Insights: Linking Context And Action

The BI vendors, in attempting to expand access to their tools, are on a constant quest to make the tools themselves easier to use (via drag-and-drop capabilities, GUIs, etc.) and/or easier to acquire (i.e., SaaS applications). And, that’s all fine and good. But, the way to get more people to make better decisions based on data-driven insights is, once again, to deliver information in context. Rather than asking a front-line worker to stop what he’s doing and open a BI tool to help make a decision, for example, it is much more effective to deliver that insight via the tools and applications that worker uses everyday to do his job. Same goes, even more so, for influencing a customer.

For example, you can’t expect a front-line worker (say a truck driver at a shipping company) to monitor a BI application to determine the optimized route he should take. Rather, that type of information must be delivered to the driver in the context of the driver’s way of working, say via an on-board navigation system.

BI is not dead. Far from it. But, its historical value has diminished, at least by way of comparison, to the ability to deliver information in context. Still, the ability to operationalize insights by delivering information in context has its roots in traditional BI, without which we wouldn’t be where we are today. Business intelligence is dead. Long live business intelligence.

In a follow-up post, I will delve deeper into how “information in context” actually manifests in the real-world and dig into emerging best practices for developing the required capabilities. In the meantime, if you’d like to learn more about delivering information in context, don’t miss Pivotal’s Ian Andrews presenting on this very topic in his keynote address at Strata + Hadoop World 2016.


About the Author

Jeff Kelly

Jeff Kelly is a Director of Partner Marketing at Pivotal Software. Prior to joining Pivotal, Jeff was the lead industry analyst covering Big Data analytics at Wikibon. Before that, Jeff covered enterprise software as a reporter and editor at TechTarget. He received his B.A. in American studies from Providence College and his M.A. in journalism from Northeastern University.

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