Summary: Driven by new technologies and data growth, the BI landscape is shifting dramatically from traditional BI solutions of the past. These changes create amazing opportunities for those who jump on board. In this article, you’ll learn more about why BI is changing and where it’s heading.

Over the last decade, Business Intelligence has slowly evolved. It’s gone from an IT-specific task to a company-wide function. It’s gone from time-consuming to near-instant. It’s gone from a luxury to a necessity.

Despite all of the recent changes, it’s still evolving.

How? Today, let’s explore a few BI trends to watch in 2019. While the list could be much longer, here are a few important trends to keep your eye on this year.

Embedded Analytics

According to Reuters, the embedded analytics market is growing by 14% annually. It’s expected to continue growing, and is a trend that you can’t ignore in the coming years.

So, what is embedded analytics? According to Gartner, “Embedded analytics is the use of reporting and analytic capabilities in transactional business applications.”

The growth is being pushed by a couple of factors.

First, software vendors are integrating BI tools into their platforms. This gives their users better insight into data and helps the vendor offer more features to their clients. Embedding pre-made solutions is typically far simpler than building their own.

Second, businesses are integrating BI tools into their existing software. This improves user adoption, as users can view important data within their current routine. In the coming years, we can expect both of these trends to increase.

“In 2019, there will be a boost among software vendors to integrate existing BI tools and technologies into their own application or platform, to provide insights on a much larger scale,” says Mieke Houbrechts, Digital Marketer, Cumul.io. “The reason why integrated analytics will become even more important is two-fold: From the business point of view, IT companies are looking for ways to monetize the richness of data available inside their platform. However, they typically don’t have the time & resources to build a fully custom BI solution themselves.

From the user’s point of view, software buyers look for tools that provide an all-in-one experience. Reporting & analytics stands high on their priority list of features a productivity app should include. The advantages of integrated analytics are numerous. It enables software vendors to speed up their time-to-market, without wasting time on development. At the same time, their users gain more insights in a visual, interactive way, directly inside their favorite tool stack. Ultimately, integrated analytics will boost software usage and customer satisfaction.”

Data Storytelling

If I had to guess, I’d say the majority of BI efforts in organizations across the world suffer from the same problem: They’re data-rich but insight poor. They provide data but rely on the users to find insights.

The problem is, the users don’t understand the data in the way that a data analyst might. So, while a BI app or dashboard might do a great job at summarizing data, its meaning might not be clear to the end user.

Here’s a great quote in this article that sums up this problem perfectly:

“People who are closest to the data, the complexity, who’ve actually done lots of great analysis, are only providing data. They don’t provide insights and recommendations.

People who are receiving the summarized snapshot top-lined have zero capacity to understand the complexity, will never actually do analysis and hence are in no position to know what to do with the summarized snapshot they see.

The end result? Nothing.”

The problem is, many BI applications are nothing more than data dumps. It’s data placed on a screen and called a report, dashboard, or BI application. This becomes an issue the farther up the chain you go.

For instance, if you give a data-heavy dashboard to a department head, they might want to dive into the data and look for insights. But, a C-level executive doesn’t have time to analyze the data. In this case, you must give them dashboards that provide insights.

These trends are driving the push for data storytelling. Rather than displaying data, BI needs to explain what it means and why it’s important.

“Data storytelling is likely to become one of the biggest trends in business intelligence, as not everyone interprets data the way an analyst does, says Amy Smith, Business Technology Analyst at FitSmallBusiness.com. “It isn’t enough to have data visualization, which only helps one make sense of the data. A good data story can help one understand the situation, the data behind it, and the actions need to help drive a decision toward resolution. Expect to see more than infographics in 2019.”

Proactive BI

What is Business Intelligence? For many, it’s just data visualization and reporting. It helps them understand their data and make more informed decisions.

In other words, it’s typically a reactive system. It lets you respond to past data. But, modern BI is becoming more proactive.

What do I mean by that? For instance, what if your BI software sent automated alerts when unusual changes in data occurred? In the event that data changes dramatically (for the good or bad), wouldn’t you want to know about it? Or, what if your BI system provided recommendations based on past data?

BI is moving beyond the constraints of data collection and reporting. In the coming years, we’ll see data being used as a trigger within BI platforms. As explained below, we’ll see BI platforms giving more recommendations.

“The hype around collecting data just to have it is over,” says John McDonald, CEO of ClearObject. “Now, organizations must use that data in a way that allows them to make business decisions affecting the bottom line, like preventive maintenance, customer satisfaction, and more. Predictive analytics will only advance in years to come, so that industries like manufacturing and logistics not only get the data they need, but are able to analyze the data and uncover suggested actions.”

Self-service BI

Over the past few years, we’ve seen the growth of self-service analytics. Businesses are moving away from the traditional BI process, where everything ran through the IT department. Now, the BI landscape is shifting to self-service.

How big is this shift? Last year, Gartner made waves in the BI industry when they revamped their BI magic quadrant criteria. The move towards business-user-centric platforms forced a new market perspective and reordered the entire landscape.

However, as self-service analytics grows, so will end user’s proficiency with the tools. They’ll soon move on from simple reports and dashboards and into more complex analytics.

Industry-specific Analytics

The BI market is becoming saturated with solutions, and it’s still growing. This will lead to a few changes.

First, BI costs will decrease. As more players enter the market, they’ll start differentiating themselves with price. While the big players probably won’t be affected by this, the lesser known platforms will try to undersell each other.

This will lead to greater adoption, as BI will become more affordable for small and medium-sized businesses (SMBs). As a result, we’ll see an uptick in adoption among SMBs.

The surge in adoption will create demand for niche tools. Businesses will start asking for BI tools that fit their exact needs. This will create a demand for custom analytics and more BI tools created for specific industries.

“Business leaders and professionals across the board recognize they need software solutions that are easy to use, have the ability to organize and analyze data, and are tailored to their business’ metrics, questions, KPIs and demands,” says Angela Kent, CMO of Phocas Software. “This means generic or spreadsheet-based packages that require data scientists or IT are becoming overlooked. On day one, if you’re in manufacturing, distribution or retail, you’ll want measures and dimensions to get to the answers and lead you to insights. The manufacturing industry wants to analyze trends about part price variance: what are the associated costs with engineered vs quality issues scrappage? In distribution, were items delivered in full on time? What is your slow-moving stock? In retail, what are your live stock turns? Which complementary products should your team upsell? The list goes on. With data analytics now pinpointed and specific, people want answers — and they want them now — to get an edge in their product-centric businesses. And with data analytics solutions now becoming industry-specific, organizations are gravitating toward them.”

Summary

These are just a few BI trends to watch in 2019, but the list could be much longer. Would you add anything to this list? Feel free to comment below!