Self-service BI is the holy grail of business intelligence practitioners. It promises to empower business users to create their own reports without relying on the IT department, which may takes days, weeks, or even months to fulfill user requests. With self-service BI everybody wins: business users get the information they need, when they want it, how they want it; the IT department reduces its backlog of requests and can focus on more value-added projects.
The Dark Side of Self-Service BI
Or so the theory goes. In my experience, self-service BI tools often exacerbate the problem they're designed to solve. On one hand, most business users find the tools too difficult to use and revert to asking the IT department for custom reports, or worse yet, do without solid information when making decisions, relying largely on gut feel. On the other, a few tech-savvy users overuse the tools, creating report chaos, or worse yet, use the tools to submit runaway queries bog down performance of the data warehouse. This further alienates the majority of users who find the BI environment less friendly than before the advent of self-service BI.
Know Your Users
Before purchasing BI tools, companies need to take an inventory of business users and classify them by their styles of interacting with information for decision making. In general, there are two classes of users: casual users and power users. (See table 1.)
Casual Users. Casual users use information to do their jobs. They are executives, managers, field and operations staff, and even customers and suppliers. Eighty percent of the time casual users simply want to consume information created by power users; they are passive recipients of information who use data to support their daily tasks and decisions. Ideally, casual users consume information that is "tailored" to their roles usually in the form of a report or dashboard whose data is sourced from a data warehouse or data mart.
Power Users. Power users, on the other hand, are business users for whom information is their job. They are super users, business analysts (a.k.a. Excel jockeys), analytical modelers (i.e., SAS and SPSS developers), and IT professionals. Power users spend 100% of their time producing information, either for themselves or others. They usually access data in an ad hoc, exploratory fashion using powerful analytical and authoring tools that source data from both the data warehouse and other systems, both inside and outside the organization.
The Missing 20 Percent
Given this dichotomy, it's fair to say that casual and power users represent two distinct user populations that require different sets of tools and even architectures to support their information habits. However, reality is not quite this simple. That's because 20% of the time casual users need information that is not available in the standard, tailored content available to them. In these situations, they need to become "producers." Unfortunately, casual users by definition don't have the skills to produce information, nor do they want to take the time to learn producer skills.
The Role of Super Users. Many organizations rely on "super users" to plug this "information gap." Super users are business users in each department who gravitate to information technology and quickly become the "go to" people that colleagues rely upon to create custom views and reports. Supers are absolutely critical to the success of any self-service BI initiative. The smartest BI directors find out who the super users are in each department and make them an extension of their BI teams and Competency Centers. They provide first-level support to the super users and recruit them to serve on the BI working committee to guide BI development, select products, and shape the roadmap. Super users are critical to the success of any self-service BI initiative.
BI Tool Capabilities
Hierarchies of Consumer and Producer Functionality. At the same time, the current generation of BI tools is moving the needle on what various classes of business users can do for themselves. Table 2 shows a hierarchy of functionality available to casual and power users that some BI tools now support.
An executive, for example, may only want to view static reports and dashboards or perhaps print them out. But over time, the executive may want to navigate a dashboard by drilling down predefined paths or applying predefined filters. A manager may want to view and navigate data as well as modify it (i.e., add/delete columns, rank/sort data, change chart types, etc.) and perhaps even explore data dimensionally via a visualization or search module.
On the power user side, a super user may first produce reports by assembling them from a library of reporting gadgets, which consist of tables, charts, and filters gleaned from existing reports and dashboards. At some point, they may graduate to crafting reports from data objects embedded in a semantic layer, or perhaps even source data and then model and transform it into data objects of their own. Overall, BI tools are making it easier for casual users to become more analytical and power users to develop more sophisticated reports without IT assistance.
Finding the Comfort Zone
It's important to recognize that no user wants or needs all the functionality listed in table 2, except for perhaps the most sophisticated power user. Every user eventually settles into a comfort zone of functionality that they need and use. Over time, users may evolve their skill sets as they become more familiar with the tool and data environment.
Thus, self-service BI tools don't overwhelm business users with too much functionality at once. They only expose functionality to users when they need it and are ready to use it. Much of this type of tailored delivery can be administered through role-based authentication. But the best BI tools build dynamic displays that put additional functionality at users' fingertips so it's available as soon as they want it; otherwise they might never know to ask for it.
Summary. The key to self service BI is threefold: 1) know your users and their BI functionality "comfort zones." 2) Create a network of super users to address the 20% of casual user requirements for ad hoc information that can't be met with standard content and 3) purchase BI tools that expose BI functionality on demand.
Posted January 13, 2011 2:40 PM
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