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December 31, 2007

BI, Delivered from the Cloud

A new report in Knowledge Management confirms a trend that began emerging over the past year -- business analytics delivered via Software as a Service.

"More and more business analytics software providers are moving to address increasing market demand for software that is updated frequently, hosted off-site and purchased on a subscription basis," KMWorld notes. Factors propelling this trend include corporate budget constraints on traditional software, limited development resources for in-house BI software, and increasing maturity of BI-over-the-wire solutions.

The report notes that recent market consolidation -- such as the Oracle-Hyperion, SAP-Business Objects, and IBM-Cognos acquisitions -- is spurring the proliferation of business analytics solutions, which will grow the market, and thus, the opportunities for SaaS-delivered services (which could come from these large vendors as well.)

The authors note that they don't expect the whole BI world to move to the Cloud anytime soon, however. As they put it, the shift will be gradual, and both SaaS and traditional, on-premises, licensed software will co-exist within enterprises for a long time to come.

A few months back, while preparing a report for Database Trends & Applications, I spoke with Tracy Trawick, consumer insights manager for Hamilton Beach, which employs such a hybrid approach to BI, getting the best of both worlds of SaaS and on-site. Hamilton Beach's market research department primarily relies on on-site software, but lately has begun tapping into SPSS's SaaS-based platform to cover a growing workload that end-users simply don't have time to sort through. "All the data manipulation on the back end is supported by SPSS," Tracy said. "We're using it for very template-based iterative projects so we don't use up a lot of programming time. I don't have the time to learn the logic and the programming tools." Tracy uses the SPSS SaaS platform to create and launch consumer market research surveys, and manipulate the data as it comes in. However, she still employs SPSS on-site software for more complicated projects.

In line with the Hamilton-Beach example, I also spoke with Oliver Halter, partner with Diamond Management & Technology Consultants, who concurred that "companies currently tend to use SaaS on the fringe of their operations." Oftentimes, "this also means that the SaaS partner provides an additional service that makes it worthwhile for the company to outsource the software and function. Companies tend to have an easier time switching to SaaS if the data managed in these systems is 'non core' and is not considered a competitive advantage."

Moving to a SaaS model has its share of challenges, however. Dilip Wagle, a partner with McKinsey & Company, told me that integration remains a big challenge, especially for companies seeking to leverage solutions from the Cloud. Dilip cautioned, for example, that "counter to the promise, the deployment and integration effort is not zero. Most effort is centered on integration and customization effort of single SaaS applications, especially in the enterprise space. Moreover, as companies increasingly move to more SaaS applications, integration challenges will manifest themselves in terms of integration with other SaaS applications."

Data security and availability is also another challenge, and perhaps the achilles' heel of SaaS arrangements. What happens if the application provider goes out of business, or has a major network outage? SaaS customers need to make sure they have robust backup systems in place. Security raises more red flags. As Dilip warned, "pure 'in-the-cloud' services imply that all the customers data are essentially stored off-premise in a data center owned or contracted by the service provider. In the event of data center failure on the part of the service vendor, the customer has no recourse but to hope that data were appropriately backed up and managed in a secure fashion. The problem can be exacerbated if the SaaS vendor in turn, outsources back-end data center operations to yet another third party. This can complicate accountability and liability in the event of failure or security breaches."

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