ipad1-150x150In October, Gartner identified their top 10 strategic technology trends for 2013 across big data, cloud, analytics, and mobile. In a recent SAPinsider article, John Schweitzer, senior vice-president and general manager for Analytics at SAP, shared technology-driven trends that will enable companies to use data to make more informed decisions.

In this post, I’ll  focus on three key analytics trends that you should consider if you ‘re looking to invest in analytics technology.

Operations and Analytics Converge

For more than 40 years, organizations have been forced to run operational and analytic processes on different systems. The latency of disk-based databases and the high cost of live memory were such limiting factors that combining operational and analytic processes didn’t make economic sense.

Now new technology and falling costs are overturning a generation of analytics best practice. It’s becoming faster, simpler, and cheaper to use a single in-memory system for both operations and analytics. This offers  new opportunities for analytic insight and brings us a big step closer to having “a single source of the truth” for the enterprise.

In 2012, SAP started releasing applications that combine the best of operations and analytics in a single solution running on SAP HANA—SAP  CRM , SAP Business One, and SAP Sales and Operations Planning.  Big in-memory advances for SAP’s core ERP and SCM systems have been promised for 2013.

Business-Focused, Cloud-based, Mobile Analytics Solutions Emerge

Business people don’t just want to analyze information, they want to take action and make changes to business processes. Rather than use general analytic tools, they would prefer to use systems that are tailored to their particular needs as a seamless part of a larger business workflow.

Systems that combine analytics technology with industry and line-of-business best practice aren’t new, but the artificial separation between operations and analytics has limited their usefulness and deployment.

The new advances in in-memory computing, cloud platforms, and mobile devices are combining to breathe new life into these solutions. We’re now seeing the start of the enterprise wave of the mobile revolution with small, actionable analytic applications designed for a particular industry, person, or role, that combine analytics and operational activities.

SAP  Precision Retailing is an example of the new solution approach. Powered by SAP HANA in the cloud, it makes it easy to provide powerful new functionality to business users and customers without having to install or upgrade existing systems. The solution:

  • Gathers information from on-premise or on-demand systems (from any vendor) and stores it in an in-memory data model.
  • Provides marketing managers with best-practice analytics that allow them to analyze shopper behavior.
  • Allows consumers to use mobile applications to get personalized 1-to-1 offers in real time across multiple channels

Throughout 2013, more of these packaged, single-use applications will be launched by SAP and the SAP ecosystem, and they will steadily include technology such as embedded predictive analytics, text analysis, and advanced visualization.

The Pendulum Swings Back to Analytics Standardization

The explosion of new analytic technologies, from data discovery to big data and Hadoop, combined with more emphasis on small, agile solutions has brought great benefits. However, it has also resulted in a rise in analytic fragmentation with data duplication, higher costs, and less data consistency.

The right solution is a central, real-time data platform that serves as an information foundation for the organization as a whole, across both on-premise and cloud-based systems.

This platform includes:

Organizations want the best of both worlds. By using solutions like SAP Visual Intelligence, business divisions and users get the  flexibility they need to experiment and quickly create their own mini-applications that combine corporate data with their own figures and external information.

However, as those applications mature into full solutions, they should not become yet another extra analytics silo. It should be as easy as possible to promote them to the central data platform so that they can  integrate with other data sources, benefit others from the same insights, and ensure information governance.


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