One of the biggest paradoxes in business intelligence (BI) is that self-service BI requires a lot of hand holding to succeed. That was the predominant sentiment voiced in a recent Webcast panel I conducted with Laura Madsen, a healthcare BI consultant at Lancet, Russell Lobban, director of BI and customer analytics at Build.com, and Brad Peters, CEO and co-founder of the multi-faceted BI vendor, Birst. (The Webcast will soon air on SearchBusinessAnalytics (date TBD.)
Training required. The panelists iterated the need for significant training and support to ensure the success of a self-service BI initiative. Madsen said companies should implement multi-modal training (i.e., Web, classroom, self-pace) on a continuous basis. Peters said many of his customers are effectively using social media to grease self-service BI wheels; specifically, discussion forums that enable users to share experiences and answer each other's questions. Lobban said it's critical to offer an integrated data dictionary that defines data elements used in the BI tool.
Know your audience. Another critical success factor is knowing the audience for self-service BI. Peters, for example, said there are two types of self-service: "data self service" for power users and "business self service" for casual users. Power users require ad hoc access to data using visualization tools that enable them to explore application data and local files. Casual users, on the other hand, need structured access to data via a semantic layer that adds business context. Although a semantic layer requires time and effort to build, all three panelists said it is critical to the success of any self-service BI program and helps ensure that users make accurate decisions.
Lobban emphasized the importance of starting small and iterating quickly. He said users often get discouraged when they don't find the data they need. Thus, it's critical for the BI team to add new data quickly to keep up with user requirements. The other major challenge Lobban sees with self-service BI is that business users often misinterpret the data in reports and dashboards. This is especially true for new hires or transfers from other departments. Thus, it's critical new hires and transfers get mentored by experienced BI users, either in person or virtually via help desks, training classes, or online forums.
Which tools? The panel also spent a lot of time discussing the types of tools that are best suited to self-service BI. Most thought the new generation of in-memory visualization tools are great for power users who can navigate their way through existing databases and applications, but inadequate for casual users who need more structured access to data. The panel also discussed the benefits of traditional OLAP tools versus the new visualization tools. The consensus is that OLAP tools still play an important role in BI tool portfolios because they provide robust dimensional views and calculations that new visualization tools don't support.
Finally, the panel discussed the tradeoffs between best of breed versus all-in-one BI suites. Best of breed tools provide the best functionality available or satisfy the parochial needs of individual workgroups or departments, while BI suites provide an integrated experience and architecture that addresses the entire spectrum of BI needs in an organization and is thus easier to administer. Ultimately, the panel agreed that each organization needs to decide which approach best fits their individual requirements and culture.
Summary. Self-service BI is the holy grail for BI professionals, but it has been difficult to achieve. BI practitioners and business users expect self-service BI to be easy when it's not. It requires clean, comprehensive data, integrated metadata, and continuous training and support. Ultimately, self-service BI is the true test of a BI program's overall maturity.
Posted September 23, 2013 9:35 AM
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