Hosted systems can expand access to analytic information. But Ventana Research recommends evaluating SaaS models for particular business needs and to determine how they can work together with internally deployed BI applications.
A growing number of vendors of business intelligence (BI) software, both well-established companies and new entrants, are offering BI software as a service (SaaS). Ventana Research believes this method of access can help companies lower costs, speed deployments and broaden usage of BI. But we believe companies should not make a blanket choice to deploy all BI internally or as a service, instead we recommend evaluating each for particular business needs and determining how to make the two approaches work together.
Software as a service can help companies overcome barriers to the use of business intelligence tools. For some, the initial startup cost limits launching of BI projects. SaaS offers them a viable alternative to deploy applications that can provide significant business value. BI SaaS does not require companies to make major upfront investments in a hardware server and licenses for the BI software, operating system, a database, and application and Web servers; instead the software provider hosts them over the Internet for a fee.
For companies in which IT workloads, knowledge and skills are barriers to deploying BI capabilities like reporting and analysis or business-specific analytics in a timely fashion, software as a service offers a means to quicken the IT function’s response to business needs. IT organizations need not install, configure and upgrade software components and ensure they work together properly. In addition, IT does not have to spend time gathering extensive requirements information to understand how to build the application so that it fulfills the business need.
And for companies in which cost and speed of deployment limit BI deployment, software as a service offers a way to make information available to more employees. Responses to Ventana Research’s surveys show that less than one-fourth of companies have deployed BI to front-line workers and less than one-sixth have deployments in the supply chain or customer operations. BI SaaS can provide timely information about causes and impacts of business events to a broad spectrum of stakeholders whose decisions can drive improvements in performance. To accomplish this, organizations need to assess the use-case scenarios of business users to ensure that BI SaaS can meet their needs.
Of course, BI SaaS comes with its costs. Although SaaS can help companies get past the barrier of initial startup costs, the total cost over the lifetime of the application can be as much if not more than deploying internally. Ventana Research recommends that companies regularly review and evaluate their BI SaaS costs to ensure the arrangement is delivering full benefit for the price. Before handing over internal IT management, Ventana Research recommends that companies evaluate BI SaaS vendors’ knowledge of their vertical industry, the horizontal business function and technology best practices to make sure they can address them as effectively as internal staff does. And as they deploy BI to more users and functions, in which they likely will have a mix of internal and SaaS BI, IT organizations should evaluate the BI SaaS vendor’s architecture to make sure they and internally deployed BI systems can work together.
Ventana Research believes BI SaaS can help companies lower costs, speed deployments and broaden usage of business intelligence software. But before going ahead, we recommend companies evaluate the trade-off between initial and total costs over three years and the return on investment; they also should consider the security implications of where the hardware physically is located, who has access to the servers and data, and the impact of these factors on data governance and regulatory compliance. Further, we recommend that organizations evaluate how a vendor’s SaaS architecture fits with their IT standards and its interoperability with their internal systems.
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