Of course, you're more likely to successfully engage the business when you have a strong business sponsor with a powerful ability to influence the organization. A strong, committed business sponsor can significantly affect the organization's culture. Conversely, if you suffer from a sponsorship disorder, it's even harder to obtain business acceptance. These two disorders often go hand in hand.
As previously discussed, one size doesn't fit all when it comes to analytic capabilities. You need to acknowledge the range of usage requirements and institutionalize a strategy to address the spectrum.
Similar to our discussion about business sponsor care and feeding, you need to establish a comparable program for the rest of the business community. Care and feeding commonly occurs with the initial deployment, but then we often quickly turn our attention to the next project iteration. You need to proactively conduct ongoing checkpoint reviews to remain engaged with the business. In addition, you should help the business users understand their shared responsibility for a healthy DW/BI program.
Education is a key component of deployment, but it isn't a one-time event. You need to consider ongoing needs for tool, data, and analysis education. We've worked with some organizations that include DW/BI training as part of their new hire orientation because information is a fundamental part of their culture. Not surprisingly, the DW/BI environment is broadly accepted in these companies; it's part of the way they do business.
Finally, as we described with the sponsorship disorder, communication is critical. You can't rely on the project documentation tools to communicate with all your constituencies. You need to concentrate on what's in it for them, marketing successes while managing expectations.
Contrary to popular opinion, infrastructure disorders are seldom fatal. There's often room for improvement, but it's usually an elective procedure. Despite our personal interests in this disorder, it usually doesn't warrant the attention due the others.
Symptoms. Are the DW/BI systems slow or is the data late? Is the DW/BI environment commonly described as a bundle of technical bells and whistles? Are there tool overlaps and/or voids? What about performance concerns? Performance covers a gamut of potential underlying problems: ETL processing time to get the data loaded, query result time lags, and the DW/BI development cycle time to deliver new functionality.
Treatment plans. Every DW/BI environment is based on an architectural foundation; however, it may be time to revisit your overall architecture plan. The question is whether your plan was explicitly developed, or whether it just implicitly occurred. A well thought out plan facilitates communication, minimizes surprises, and coordinates efforts.
Revisiting your technical architecture doesn't mean going out and buying all the latest, greatest technology. You need to understand the business's needs and determine the associated implications on the technical architecture in terms of the required ETL services, access/analysis services, infrastructure, and metadata. The drive toward more real-time data warehousing is a prime example of the translation from business needs into architectural requirements. Some organizations have made poor technology choices in the past. It takes courage to unload that baggage to enhance the DW/BI environment going forward.
Unfortunately, DW/BI environments aren't immune to cultural or political disorders, and there's no vaccine in development on the research horizon.
Symptoms. Symptoms of this disorder are fuzzier to articulate, especially because they typically transcend more than the DW/BI environment. Organizations with cultural/political disorders may be stymied by conflicting priorities of "doing it fast" vs. "doing it right." Similarly, they often struggle to reach consensus on tough issues, such as data standardization and process changes. Finally, more specifically related to DW/BI, many organizational cultures aren't poised to embrace analytic decision-making, especially when decisions have traditionally been based on gut feelings or intuition. Do the business users currently manage by the numbers? There's often a lack of recognition and/or willingness to champion a culture shift to more fact-based decision-making.
Treatment plans. When dealing with cultural and political disorders, you can't just duck them, much as we would like. You need to be courageous, while understanding that these disorders are difficult to overcome with trench warfare. Now is the time to call in your support group: IT management, business sponsors, and the business community. If the support group doesn't recognize the need and assume accountability for treating these disorders, then the DW/BI team is in for a long, uphill struggle. Senior business and IT management must accept its fiduciary responsibility for handling information and analytics as corporate assets. Finally, actions speak louder than words. The organization will easily see through a veil of verbal commitment if management doesn't exhibit reinforcing behaviors.
As touted by cancer experts worldwide, early detection is the best prevention. Proactively monitoring your data warehouse and business intelligence environment is the best method of ensuring its health. It's tough to prescribe a remedy if you don't know what you're suffering from. As a student commented recently, thinking about common disorders and alternative treatment plans is a "shot in the arm" for anyone who's trying to rescue a failing data warehousing project. The metaphor lives on.
Finally, remember there's nothing wrong with having a check-up and learning that you're in perfect health. In fact, that's the optimal outcome!
Ralph Kimball founder of the Kimball Group, teaches dimensional data warehouse design through Kimball University and critically reviews large data warehouse projects. He has three best-selling data warehousing books in print, including The Data Warehouse Toolkit, 2nd Edition (Wiley, 2002).
Margy Ross is president of the Kimball Group and instructor with Kimball University. She cowrote The Data Warehouse Lifecycle Toolkit (Wiley, 1998) and The Data Warehouse Toolkit, 2nd Edition.