I have been a bullish investor of companies that provide on-demand BI solutions (to date I invested in Pivotlink and Host Analytics). After being involved with BI for over two decades I see SaaS as a fundamentally transformational model whose benefits outweigh the adoption issues I described in my last posting. Moreover, these issues are not “show stoppers.”
The value and uniqueness of on-demand BI is coming from the following areas:
- Cloud-enabled collaboration. Collaborative BI can effectively be enabled through cloud computing. Companies want to collaborate through data. Employees want to collaborate with other colleagues and partners by looking together at a single view of internal and external data that impacts daily their business “ecosystem.” Today the only decisions that are effective are those based on data blended from inside and outside the company.
- More efficient analysis paradigm. On-demand BI transforms the "traditional" ETLA (Extract Transform Load Analyze) process found in most data warehousing/BI environments, to an ELA process (Extract Load Analyze) process. This doesn't simply mean that you are removing a costly step (Transform) from the process, but that you are changing the entire analysis paradigm. Because on-demand BI applications make Extraction and Loading very cheap, the user of an "ELA environment" doesn't have to be extremely thoughtful on what data to include in the warehouse (or data mart) and how to transform it in order to improve the analysis results. Instead he can load a bunch of data and "experiment" with it. If the experimentation goes well then he continues. If it doesn't go well then he "throws the loaded data away" and load some more without delay or guilt. On-demand BI companies like Pivotlink have been developing extremely fast data extractors and loaders in order to better support the ELA paradigm for an expanding set of cases.
- Social networking/Community. Social networking and other social media applications have demonstrated the power of communities and are now moving from personal use to enterprise use. Community-based tools built around on-demand BI solutions can increase a BI solution’s adoption, reduce service delivery costs and, through the established dialog between users and the solution provider, improve the application’s feature set and performance. Imagine, for example, through a presence tool, such as Microsoft Messenger, a user determines that another user who is an expert on inventory analysis is online. By looking up this user’s profile he finds out that the user has received good recommendations from co-workers and customers about his ability to create inventory analysis reports. A real-time dialog can begin and lead to collaborative problem-solving.
- Better maintenance of the application and the data. Because the application/reports and the database/data warehouse are located in the vendor’s data center, software updates, database maintenance for optimal query performance, report organization and other tasks associated with the support of a properly running BI solution are managed and performed centrally by the vendor. This activity results in optimally running BI solutions enjoyed by all users. The performance of on-premise BI solutions is dependent on the IT organization’s abilities to a) devote the right resources to address the above mentioned tasks along with software updates and patches coming from the vendor and b) develop local expertise to optimize the performance of each BI solution being used. This may be possible in certain companies with large and sophisticated IT organizations but, unfortunately, it is not found in every company that uses on-premise BI solutions. For example, a recent Oracle critical patch bundle included 16 updates for Oracle Database Server, 12 updates for Oracle Application Server, 3 updates for Oracle Applications, 4 updates for Oracle PeopleSoft and JDEdwards Suite, and 8 updates for BEA Products Suite.
- Usage optimizations. By monitoring the on-demand BI solution’s usage, the vendor can a) dynamically make optimizations to improve its performance, and b) determine which features are being used effectively, which features are not being used at all, which features present difficulty to the user (even though they are perceived as useful) and also make improvements as appropriate. There is a bigger point here relating to a vendor’s monitoring a SaaS application’s usage. It should first be noted that this type of monitoring cannot be accomplished for on-premise applications. The vendors of such applications don’t know how their software is being used. On-demand application vendors have the opportunity to closely monitor usage to identify: a) if the application is used as expected, b) which parts of the application are being used the most (not unlike how a web analytics package reports on which web site pages are being visited), and c) even provide cross user statistics in the way Nielsen and comScore report various types of audience metrics.
- Easier to avoid vendor lock-in particularly now that the major on-premise BI vendors (Cognos, Business Objects, Hyperion) have been consolidated. Because of how critical BI is to every corporation, customers should always try to select the BI vendor with the most-suitable solution rather than the vendor that offered them "a great deal" on BI by bundling it with a bigger IT contract, as the major IT vendors are likely to do.
- Innovation. The consolidation of the major on-premise BI companies can also result in slower innovation since they are now divisions of larger IT vendors that may have different overall objectives than to provide innovative BI solutions.
Areas that are impacting the TCO of an on-demand BI solution:
- Fewer personnel needed to support the application. Moreover these personnel don’t have to possess specialized knowledge in the way that personnel that support on-premise BI solutions must have. BI solutions have been particularly personnel-intensive (database designers and administrators for the data warehouse, programmers and analysts to create and maintain reports, data analysts to extract information from the collected data).
- No upgrades to hardware. The dissemination of on-premise BI solutions within the enterprise has been frequently stymied by the need for upgrades so that client machines can satisfy the processing needs of BI tools. On-demand BI solutions are not only accessed through a web browser obviating the need for hardware upgrades but also resulting in fast deployments of these solutions.
- Cheaper implementation of a data warehouse/data mart because using a standard data model is faster and can benefit from the improvements (functional, architectural, implementation) performed by the vendor’s dedicated staff for all customers.
- No hidden costs in terms of solution upgrades, customizations, systems and data integration.
- Dedicated vendor personnel keeping the data warehouse in top shape (through data model refinements, data utilization, additional aggregations, etc.) and disaster recovery. When considering the cost benefits of SaaS, many companies do not include the value of transparent and immediate upgrades to the latest software version. Companies deploying traditional on premise solutions must account for the ongoing cost of planning, implementing and supporting new software upgrades and bug fixes. This can easily cost from tens to hundreds of thousands of dollars in professional services, IT resources and duplicate hardware and it usually involves running parallel applications during the implementation, testing and acceptance period. It is not surprising that the average ERP implementation is typically 2-3 versions behind the latest software update.
BI continues to score high as an important corporate solution even during this time of shrinking IT budgets. On-demand BI addresses many of the issues that had plagued on-premise BI solutions and offers some unique advantages making such solutions possible for more and larger segments of the market. As such it warrants serious consideration by small and large companies alike.
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