2016 And Business Analytics: Be Prepared For A Smashing Year: Part Two

Iver van de Zand

In  Part 1 of this blog, I outlined the key trends that I’ve identified for business analytics in 2016. These are based on the conversations I’ve had with my customers and the plans that they’re making.

These five key trends for business analytics in 2016 are:

  1. Self-service BI will become a commodity
  2. Business will embrace the portfolio loop
  3. Companies will really analyze Big Data
  4. Cloud BI adoption will accelerate
  5. Operational BI footprint will grow

I also discussed the first two trends in detail in my last blog. Today, let’s take a closer look at the other three.

3. Companies are really ready to analyze Big Data

Big Data discovery (you can find an interesting article here) is now ready to be implemented. We all used 2015 to understand and practice how to connect to Big Data sources like Spark clusters, Hadoop, Cloudera, MongoDb, and others. In parallel, software vendors ensured the analytics components were prepared to do so not only in the way they connect to the sources, but also in how they liaise with core data. The latter refers to enrichment tools like SAP Vora and techniques like data blending. For 2016, we’re now all set to start adopting Big Data discovery to use its insights in our company’s performance management. And the icing on the cake is that now predictive analytics components can be utilized by even “normal people” like you and me.

4. Cloud BI accelerates

In his blog post, Who’s Afraid of Cloud Analytics?, Timo Elliot discusses a kind of anxiety that some organizations have about running BI in the cloud. His article is very interesting, and confronts readers with the fact that, since lots of data is already coming from outside, it’s reasonable to leave your own data there. He also argues that business users shouldn’t really care where their data is.

Fact is,  BI in the cloud has a number of undeniable advantages, like state-of-the-art performance and functionality and highly limited maintenance while securing your own data. It allows business users to focus on what they’re good at and well-positioned to do—collecting insights and acting intelligently upon them.

According to Forrester, “36% of respondents had already replaced, or are planning to replace, their on- premise BI with SaaS BI, and 31% had chosen SaaS BI to complement their existing BI, or intended to do so in the future.” From this I conclude that companies are becoming more open towards cloud BI and so we can expect accelerations in 2016.

5. Operational BI says, “Hello world!”

To be honest, I expected a bigger footprint for operational business intelligence already in 2015. The reason for my expectation was  how widespread  implemented in-memory platforms were. The calculation power of these platforms is so high, it often allows users to run analytics directly on the operational data instead of creating a dedicated data-warehouse environment.

Why the delay? Conversations with my customers reveal that companies were waiting with operational BI because of the very simple fact that analytics has become a core activity with them. They’re cautious changing their model into operational analytics because they rely on their analytics so intensely. Companies prefer to first implement their operational applications onto in-memory computing. Then, in a second phase, they shift their existing (!) analytics onto in-memory computing. Only in a third phase do they consider simplifying their analytics and running them directly on the operational apps. It’s a bit of a safe route, but very understandable.

As a trend for 2016, we can clearly see that analytics projects, especially new ones, will “say hello” to operational BI being developed directly on the operational data. The platforms are there, and the simplification is the driver.

Other things to keep an eye on

Is there more stuff coming up in 2016? Definitely. But for me—and especially the customers I work with—these five trends are the ones that really matter. However, you’ll definitely want to keep an eye on:

  • Collaboration within analytics. Collaboration, particularly within the closed loop portfolio, is becoming more and more important. We expect further focus on the topic of collaboration and workflows by both users and software vendors.
  • Predictive analytics. Predictive analytics will get even further momentum as it closely integrates with analytics. We’ve already seen predictive analytics become useful to end users during the last two years.

What do you think of these key trends? Are there any others you would add to the list?

Read Part 1 of this blog here.


Iver van de Zand

About Iver van de Zand

Iver is the Director of  the SAP Global Analytics Hub for business intelligence and predictive analytics focusing on enablement for pre-sales, collaboration, content generation, and best practices. He works closely with global leadership and stakeholders across SAP incorporating the latest insights, tools, and best practices in order to optimize the use of SAP resources, improve cross organisational collaboration, and drive efficiencies in business execution. Iver is also a member of the Lumira Advisory Council (LAC) and the International Business Communication Standards (IBCS) community that focuses on data visualization standards and Hichert principles.