February 22, 2010, 4:43 PM — When considering strategic business intelligence needs, would you put your faith in the cloud? The idea made sense for Distribution Market Advantage. For Creativity Inc., not so much.
The profiles of these two companies draw a clear line between where the nascent BI-as-a-service offerings fit -- and don't fit -- in business today. At one end of the spectrum, Schaumburg, Ill.-based DMA has no in-house BI expertise and needed to rapidly develop a Web-accessible BI dashboard for a narrowly defined purpose. On the other, Van Nuys, Calif.-based Creativity has developed its own in-house data warehouse and business analytics expertise. It mines that data to develop highly customized metrics that provide a competitive edge in developing and marketing new products for the consumer crafts market.
But even Creativity's vice president of IT, Jim Mulholland, who decided to pass on BI software as a service (SaaS), sees the game-changing potential of BI as a service: its ability to rapidly deliver a standardized suite of analytics tools that give users most of what they need without the time, expense and hassle of developing a BI infrastructure internally. BI in the cloud could be "the next killer SaaS application," he says.
However, the technologies -- and the business models behind them -- are still evolving. "It's still an embryonic market," says Jeffrey Kaplan, managing director for on-demand services consultancy ThinkStrategies Inc.
BI-as-a-service offerings typically import business data in a common format (such as an XML or comma-delimited file) put a structure around it, apply the appropriate data models and generate a Web-based user interface that allows for some analysis and the creation and distribution of standardized reports and dashboards. Some services can also query data in place, either behind the corporate firewall or from other SaaS applications, such as Salesforce.com's system. And some providers offer professional services, such as data integration, ETL (extract, transform and load) and data transformation services that organize, clean and normalize data for organizations that can't do it themselves.
DMA needed those services. The supply chain logistics organization supports 50 regional food service distributors and has no in-house BI capabilities. "We are not a technology company. Our core competency is supply chain management," says Jim Szatkowski, vice president of technical and data services. With no in-house expertise, putting BI in the cloud made sense. But DMA's needs also fit the hosted model in two other ways: BI-as-a-service offerings tend to play well with other popular SaaS products, and they often have easy-to-use Web-based interfaces that facilitate collaboration with entities beyond the corporate firewall.
BI SaaS at a Glance
What You'll Pay
- Most customers spend $20,000 to $50,000 annually, says Brad Peters, CEO of Birst. PivotLink charges $3,000 per month for 100 million rows of data and 50 users. But users can get a small pilot project started for $100 or less per month.
Consider BI SaaS If...
- You don't have in-house resources to do the job or BI isn't a core competency.
- You need something that can be built, adjusted and scaled quickly, such as customizable sales reports.
- You need it fast.
- You can get 80% of what you need with a few customizable templates.
- You're already using SaaS in operational areas such as CRM and HR and need to add an analytics component.
Think Twice If...
- You're uncomfortable processing business intelligence data outside of the corporate firewall, regardless of security assurances.
- You have a complex project or one that requires a high degree of customization.
- You have a very large data set.
- The data on which you need to perform analytics changes every day.
- BI tools will be used primarily within the organization.
- It doesn't fit the broader business model or culture. Balancing departmental and enterprise needs is key. A myopic view of BI needs can lead to application-specific silos of BI data that might be difficult to integrate in the future. Services might not have an API or support standards that would allow you to easily bring data back in-house.
How to Get Started
