BI Software Vendors Choose Their Strategies: On Premises, Cloud, or a Hybrid Approach?

Where should we deploy our analytics and business intelligence (BI)? In the cloud or on premises? It’s a question that is thrown at me frequently. Most software vendors expect only 20% of the enterprises to run full cloud analytics in 2020. What about the rest? And what do you decide today? Is there an easy answer? It might seem not …..but a hybrid BI approach is!

The Evolution of Cloud Analytics

Before understanding why there is a discussion for cloud analytics and/or on-premises analytics anyway, we need to recap on the market situation a bit. When it comes to analytics, our world has changed dramatically and is still in this changing process. It is all part of digital transformation—where we initially shifted into renewed business networks with things like video collaboration, mobile devices, connected things and what have you, we’re now moving into insights-driven experiences using structured and unstructured data in real time and online. This change is massive.

Today we connect everything—devices, people, data, and processes. Enterprises, of course, undergo similar experiences; it changes the way they are competing. Data is their key asset in this competition and as such enterprises make data their strategic differentiator. Data becomes the new gold.

In the same time technology also emerged. Besides in-memory computing, we also got stable cloud platforms that leverage in-memory computing and boost performance tremendously. These platforms were welcomed a lot in today’s massive data generation. The cloud platforms are hugely attractive, given that maintenance and support efforts are limited down significantly, and in addition the platforms deliver the scalability that enterprises need today.

Analytics vendors got on top of this and provided cloud analytics tooling. SAP BusinessObjects Cloud is one of the best examples that even went a step further in answering the needs of enterprises by providing both monitoring, planning, and predictive capabilities all in ONE tool— the so-called closed loop portfolio.

The Perpetuation of On-Premises Analytics

Yet ….. it is expected that in 2020 only 20% of the enterprises will run full cloud analytics. Why only 20%? That is either because not everybody applies to today’s use cases to run analytics and business intelligence in the cloud, or because cultural differences mean that certain areas don’t feel ready to shift to cloud analytics.

So what about all the others? They still run on-premises analytics highly successfully. Software vendors keep on innovating the on-premises software, allowing it to handle the latest needs for agility, data volume and complexity, and real-time capabilities. And they succeeded in it. In the long term, we’re pretty sure all enterprises will shift to cloud analytics, but that will take another 7-10 years. In the meantime, analytics techniques need to further evolve to answer to the need of insights-driven experience and data-driven strategies. Now the question is, what should software vendors do? Should all the focus be on cloud analytics or should they continue to innovate the on-premises solutions?

The Shift from Descriptive Analytics to Predictive Analytics

To answer our question of whether software vendors should focus their developments on cloud analytics or on premises, some other elements are important too. These are the intentions of enterprises and their strategy on data insights.  With enterprises using data as their core assets to be competitive, we see them shifting from the more traditional descriptive analytics (the typical monitoring) into predictive analytics. Simply put, where descriptive analytics answers “what happened” and “how did it happen,” predictive analytics tell us “what could happen.

In the long term, this shift will further evolve towards pre-emptive analytics, quantum analytics, or even adaptive analytics:

  • Pre-emptive analytics: analytics focused on anticipating a certain outcome
  • Quantum analytics: machine intelligence and mathematics are used to “ask” the data questions (both automated and most relevant) for insights
  • Adaptive analytics: the ultimate goal towards fully adaptive enterprises where enterprises can predict which of the available analytical insights are really valuable

This shift to predictive analytics says a whole lot which we will discuss in other articles, but one thing is sure—it will definitely mean that we all need to bring analytics to where the data is created. That’s the place where we can create the data intelligence algorithms, so that the enterprise can predict what it needs to ask in terms of analytics questions, making them adaptive enterprises. Everything must be analytics-enabled.

We must have integration for predictive models and machine learning for a closed loop system. If we can all accomplish that, the world is ready for the opportunity of monetization and designing business models for subscribing to the outcomes of data.

Bringing the analytics to the data, means enabling almost any application with analytics. Given that the future of applications is in the cloud anyway (companies will also start using applications to their needs – a typical cloud model), we can also conclude that the future of analytics is in the cloud.

The Hybrid Approach Strategy

Enterprises, however, drive the speed and adoption towards adaptive organizations. They might shift iterative or in chunks. As such, they also drive the bigger part of the decision by software vendors to either focus on cloud  or on premises. Therefore, the immediate answer is the hybrid analytics focus (it must be!).

This means that enterprises must innovate the on-premises software tooling in parallel with evolving the cloud analytics offerings. It also means that enterprises should whenever possible align them and make them interoperable. Cloud analytics must be able to interconnect with the vendor’s on-premises analytics and the other way around.

The long-term strategy of analytics vendors should be on cloud analytics. However, the adoption of cloud analytics is at a speed that in 2020 we can expect only 20% of all enterprises to be running full cloud analytics and the vast majority will still—partially—be running on premises.

Digital Transformation, however, keeps on going and enterprises need to go forward using their data insights as a competitive advantage. Short and midterm strategy for software vendors can thus only be hybrid.

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This post originally appeared on Iver van de Zand’s blog and has been republished with permission.

 

January 27th, 2017|Analytics, Business Intelligence, SAP|

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