The Future of BI: Simplicity

Industry Expert Steven Schneider Discusses the Rise of “Easy BI”

Business intelligence is complex.

Sometimes, it’s too complex.

For those new to the game, it can be hard to understand what BI can do. Even experienced users sometimes struggle to understand the potential of BI.

And others familiar with the benefits of BI often lack the technical expertise to employ the technology at the highest level.

The movement to “democratize” business intelligence has swept across the industry, leading to a rash of tools aimed at empowering users across the organization to gain benefits from data analysis.

“BI software vendors are increasingly trying to commoditize the complex and provide ‘data science in a box,’” says Steven Schneider, Chief Product Officer with LogiAnalytics.

BI Software Insight spoke with Mr. Schneider about the need for simpler business intelligence, the types of simple tools that are being developed, and the future of the industry.

Keep it Simple, Stupid (KISS)

Data science is more important than ever. According to Forbes, the big data software market is expected to grow to $50.1 billion in 2015.

But why is simple so important, and why now?

“The objective of BI is to deliver the right information to the right people in the right way,” says Steven Schneider, Chief of Products with Logi Analytics.

“If the ‘right people’ for a company is restricted to an elite team of data scientists performing predictive analyses for the CEO, then a complex BI tool is probably appropriate.”

Yet for all other companies – which includes most – simplicity becomes vital.

In an increasingly competitive market where more companies are using business intelligence, providing more people with more access to analysis is more important than ever.

“But the real value of BI isn’t in empowering super users with a new toy,” Schneider says. “It’s achieved through driving actionability against data insights across the organization.”

And while there is an increasing push to educate experts to close the skills gap, the reality is that no organization will ever be entirely filled with data scientists.

“Companies are increasingly weaving BI tools into their workflow processes all the way down to the factory floor. In this case, the “right people” are the other 90 percent of the organization who aren’t advanced data users. For BI to be actionable, it must be accessible.”

Unlocking Simplicity: Tools that Empower Users

“Easy BI” is not a trend in every business intelligence field, however.

The creativity and breakthroughs are primarily occurring with tools that would be widely used in the first place.

“I think you’ll see the innovation around BI simplification start with tools already targeted at the business user,” says Schneider, adding that this means “primarily data discovery tools.”

In developing their own data discovery product with LogiVision, Schneider and his team went to great pains to ensure that their product was as intuitive as possible.

“A lot of this effort focused on automating the analysis process by performing complex data profiling, modeling, and blending algorithms within the application,” he says.

Schneider thinks that this could be the future of BI product development: streamlining and making as accessible as possible the processes that the most users in an organization will be most likely to use.

Further, he notes that in-depth BI processes have been utilized already by most people outside of a business environment – possibly even without their knowledge.

“Consumer applications like Amazon and Netflix have been hiding the complexity of data science to empower broad, diverse audiences for years,” he says.

“Why not apply these same tools and technologies to the enterprise?”

These tools would include “data profiling, modeling, blending algorithms, social sharing tools, and intuitive recommendation engines.”

Data science is the magic fairy dust of analytics.”

Use Case: Geomapping

As more data is being produced and gathered, more of it is tagged with a geographical element: something that associates it with place.

It fits the exact profile of an easy BI tool: data discovery software that can be used by anyone. In fact, Schneider calls geomapping “one of the most intuitive forms of visualization.”

“From a young age we’re taught how to quickly read and digest information on a map – even though it may be a map of Disneyland,” he says. “Maybe we don’t formally recognize it as geospatial analysis, but that’s what it is.”

This very fundamental brain process is then turned into a way to digest complex analytics.

Applications of this are vast.

“A manufacturer measures sales by region. A multinational retailer allocates annual budgets by country. As such, tracking and measuring geographic performance is foundational to business success across every industry.”

For every person in the organization to be able to read a metric like “geographic performance” quickly, without hassle, and even remotely on a mobile platform, is the essence of what companies want out of BI.

The Future of Easy BI

But where is it all leading?

As more tools become simpler and more accessible, it would seem that a plateau could be within reach. Drawing insights can only get so easy, mapping can only be displayed so clearly.

What is the future of easy BI? How will the new technology change the field?

Schneider notes that wider increase in adoption of these tools across an organization will have a fundamental impact on business.

“With the democratization of BI, I think you’re going to see an increase in ‘extended learning organizations.’ These companies will use inputs from every level of their organization – as well as external inputs from customers and partners – to constantly adapt to changing market conditions.”

He points to Amazon and Capital One as examples of such companies where the democratization of BI itself is going to create a democratization of individual participation within a company. Increasing amounts of well-informed, well-equipped individuals will be leaned upon to provide insight for more important decisions.

Small businesses, too, will particularly thrive going forward thanks to simpler BI. Small businesses are the most hard-hit by a lack of data science experts, because they have fewer resources. Empowerment across entire organizations will

Schneider even notes that because simple BI will thrive in the small business environment, and because small businesses and more flexible in their organizational approach, they could also serve as the laboratory for developing the next generation of innovation.

“By aligning the organizational dexterity of small businesses with intuitive BI solutions,” he says, “the potential for rapid prototyping and innovation skyrockets.”