I've probably seen more than a hundred press releases promising products that will "put powerful yet intuitive reporting and analysis in the hands of business users." When I covered the content management market on a daily basis (a few years back), the PR mantra was "make everyone in the organization a content contributor." All too often, these types of products aren't all that easy or intuitive.

I was reminded of these promises as I researched this week's " In-Depth Analysis story, centered around an AberdeenGroup BI study released last week. The baseline assumption of the study is that companies want to improve access to actionable information, but the 370 study respondents reported these top-five obstacles:

#1. Lack of BI skill sets (among business users)
#2. Inability to integrate data from all sources
#3. Data quality problems
#4. Lack of IT skills (developers and admins)
#5. Lengthy implementation projects

Despite the many promises about easy-to-use products that will help spread BI enterprisewide, we're still well shy of where we'd all like to be. As Cindi Howson observed earlier this year, "front-line workers and middle managers express exasperation at the state of many BI tools. Can't someone make it look like Google? Or iPod? Give me a gadget on my Blackberry?"

One of the conclusions of Aberdeen's study is that "best-in-class" organizations — those succeeding in improving access to data while meeting BI project budgets and deadlines — are more likely to turn to embedded BI (inside ERP, CRM and other apps), outsourcing and SaaS/On-demand offerings. They're buying rather than building not only to avoid complexity and cost, but also to cover a big gap in BI and IT skills.

Maybe if products truly were easier to use and to deploy, organizations wouldn't be struggling with a skills gap, but I don’t know of many alternatives that could be described as Google- or iPod-easy. The allure of SaaS-Based BI — as well as of alternatives such as data warehouse, BI and integration appliances — is that it promises simplicity. Casual Male and Anchor blue ship their data off at night and merchandisers get their reports the next morning. The skill, experience and expensive software is all behind the scenes at the SaaS vendor.

The tradeoff in taking these "easy" routes may be the creation of yet more silos and multiple versions of the truth. In this article, Joy Mundy of Kimball Group argues that analytic apps (or "smart apps" as she calls them) must have the solid foundation of an enterprise data warehouse and data quality programs. The same advice surely applies to SaaS-based approaches.

In short, unless it's a very simple, straightforward reporting need that's not interconnected with all sorts of other data and interrelated analyses, it's probably impossible to avoid complexity somewhere along the way. The practitioners who succeed will be those who can hide the complexity from end users and make things look easy. That's where experience comes in, one of the biggest differences Aberdeen spotted between best-in-class organizations and the average and "laggard" companies.

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