A lot of organizations have adopted SaaS, having moved past from their issues with cloud.

Marketing and Sales were early SaaS users, and now the CIO has become an end-user of SaaS-based tools for monitoring, app dynamics, etc.

Mainstream IT is not only trying to keep up but also is struggling to remain relevant. Previously, IT departments provided bulk of research, procurement, installation, testing and integration of on-premises applications. The cloud-enabled stack elevates the user experience and transparency at the edge of the organization, driving value. Agile IT departments will shift focus to customizing this new software to suit enterprise goals, as enterprises have crossed over to SaaS en masse within the past year.

Adrian observes that a few interesting companies are doing "business process as a service," or, a SaaS for building SaaS applications, providing "building blocks" to build custom applications with different data sources around the enterprise — Finance, HR, etc. (Michael suggests that another mini-singularity is coming where computer-literacy screening becomes a core management tool.)

Christian sees these new services as resolving the "problem with context" - executives are seeing more data than ever, but most of the things that matter to the business don't live inside the general ledger, rather they live in data streams outside the walls of the enterprise. How to bring this into the context of planning activities, which are traditionally mired in quarterly documentation and annual forecasting?

With context enabled at the edge of the organization, the end user can now assemble analytic processes rapidly, directly in an application, through modeling and collaboration, without going through a central command such as legacy systems required. These services could also lead to the demise of "Excel Hell" and "Powerpoint Hell."

Traditional information services were concerned with careful curation and the quality of data that feeds into reporting. The new services quickly leverage and analyze data, helping executives harness those streams in order to pose unstructured questions that produce high-value answers.

Many of these unstructured questions can be put into narratives for easier understanding and discussion. Also, it's not only about getting to the answer quickly but also it's about what can be done about what is learned.

Michael sees the next step as a cultural shift away from performance- and presentation-mastery and toward better data analysis. Adrian sees hypotheses as the essence of testable ideas to meet the overwhelming volume of data. Christian agrees that making sense of the data that exists will empower enterprises into subsequent data-driven decisions.

Adrian's research shows that while primary SaaS investment among startups goes to data and data analytics, but is most recently going toward talent management, which may suggest a shortage of data scientists.

Christian says that the very popular SaaS application areas include profitability and workforce planning, as well as talent management, forecasting and asset management. Adrian notes that traditionally conservative departments such as Finance are actively looking at SaaS applications, due to simplicity and price considerations.