Traditional BI approaches and technologies — even when using the latest technology, best practices, and architectures — almost always have a serious side effect: a constant backlog of BI requests. Enterprises where IT addresses more than 20% of BI requirements will continue to see the snowball effect of an ever-growing BI requests backlog. Why? Because:
- BI requirements change faster than an IT-centric support model can keep up. Even with by-the-book BI applications, firms still struggle to turn BI applications on a dime to meet frequently changing business requirements. Enterprises can expect a life span of at least several years out of enterprise resource planning (ERP), customer relationship management (CRM), human resources (HR), and financial applications, but a BI application can become outdated the day it is rolled out. Even within implementation times of just a few weeks, the world may have changed completely due to a sudden mergers and acquisitions (M&A) event, a new competitive threat, new management structure, or new regulatory reporting requirements.
- Conventional waterfall SDLC approaches are poorly suited for BI. The traditional waterfall methodology for the software development life cycle (SDLC) calls for collecting user requirements, transforming them into specifications, and then turning these specifications over to developers. While this approach is often successful for traditional enterprise application implementations, it won't work for the majority of BI requirements. The "build it, and they will come" model is directly applicable — and recommended — for BI, as only once an end user sees something she can touch and feel and play around with will the real requirements materialise. "What are the key requirements that your BI application must address?" is a typical IT question. "It must address everything, because I don't know what kinds of reports I'll have to produce and what kinds of analysis I'll have to perform tomorrow," is, unfortunately, a typical answer.
- Business and IT do not always see eye to eye on BI applications and projects. In the eyes of business executives, managers, and individual contributors, nothing is more important than business requirements. Furthermore, they want their BI business requirements addressed according to their, not IT's, schedule so that they can continually address their clients' needs and avoid falling behind the competition. IT, on the other hand, is charged with maintaining law and order and insists on sticking to standard BI tools and following approved software development and project methodologies.
However, anecdotal evidence leads us to believe that with the proper BI application portfolio classification, no more than 20% of all BI applications should fall into this restricted category. We maintain that in an ideal BI environment, 80% of all BI requirements should be carried out by the business users themselves.
But what does it take for a BI tool or application to enable all types of users (casual users, power users, and executives) to self-serve for new queries, reports, analytics, and dashboards? "Intuitive" and "user friendly" are subjective terms. A point-and-click and drag-and-drop graphical user interface (GUI) may be a nirvana of intuitiveness to an information management pro who started his computer career working with punch cards or green-screen terminals, but to a younger generation of knowledge workers brought up on search GUI from Google and social media GUI from Facebook, a point-and-click GUI may not be as obvious or natural. With that in mind, in our latest Forrester Wave " Self-Service BI Platforms, Q2 2012," we evaluated:
- IBM Cognos
- Information Builders WebFOCUS
- Oracle OBIEE
- Panorama Software
- SAP BusinessObjects
- Tableau Software
- TIBCO Spotfire
- Automodeling of raw data
- Ability to create calculated measures and metrics on the fly
- Collaboration between business users and IT staff
- Data virtualisation and drill anywhere
- Prompting for columns at runtime
- Search-like GUI
- Application sandboxes
- Write back for "what if" analysis
- Exploration and discovery on raw, unmodeled data
- Optional semantic layer
- Migration of self-serviced BI app to production
Posted by Boris Evelson