I just finished writing the first draft of my upcoming report titled, "Creating an Enterprise Data Strategy: Managing Data as a Corporate Asset." This is a broad topic these days, even broader than just business intelligence (BI) and data warehousing. It's really about how organizations can better manage an enterprise asset--data--that most business people don't value until it's too late.
After spending more than a week reviewing notes from many interviews and trying to formulate a concise, coherent, and pragmatic analysis without creating a book, I can distill my findings into a couple of bullet points. And since I am still collecting feedback from sponsors and others, I welcome your input as well!
- Learn the Hard Way. Most business executives don't perceive data as a vital corporate asset until they've been badly burned by poor quality data. It could be that their well-publicized merger didn't deliver promised synergies due to a larger than anticipated overlap in customers or customer churn is increasing but they have no idea who is churning or why.
- The Value of Data. Certainly, there are cost savings from consolidating legacy reporting systems and independent data marts and spreadmarts. But the only way to really calculate the value of data is to understand the risks poor quality data poses to strategic projects, goals, partnerships, and decisions. Since risk is virtually invisible until something bad happens, this is why selling a data strategy is so hard to do.
- Project Alignment. Even with a catastrophic data-induced failure, the only way to cultivate data fastidiousness is one project at a time. Data governance for data governance's sake does not work. Business people must have tangible, self-evident reasons to spend time on infrastructure and service issues rather than immediate business outcomes on which they're being measured.
- Business driven. This goes without saying: data strategy and governance is not an IT project or program. Any attempt by executives to put IT in charge of this asset is doomed to fail. The business must assign top executives, subject matter experts, and business stewards to define the rules, policies, and procedures required to maintain accuracy, completeness, and timeliness of critical data elements.
- Sustainable Processes. The ultimate objective for managing any shared service is embed its care and tending into business processes that are part of the corporate culture. At this point, managing data becomes everyone's business and no one questions why it's done. If you try to change the process, people will say "This is the way we've always done it." This is a sustainable process.
- Data Defaults. In the absence of strong data governance, data always defaults to the lowest common denominator, which is first and foremost, an analyst armed with a spreadsheet, and secondly, a department head with his own IT staff and data management systems. This is kind of like the law of entropy: it takes a lot of energy to maintain order and symmetry but very little for it to devolve into randomness.
- Reconciling Extremes. The key to managing data (or any shared services or strategy) is to balance extremes by maintaining a free interplay between polar opposites. A company in which data is a free-for-all needs to impose standard processes to bring order to chaos. On the other hand, a company with a huge backlog of data projects needs to license certain people and groups to bend or break the rules for the benefit of the business.
- A Touch of Chaos. Instead of trying to beat back data chaos, BI managers should embrace it. Spreadmarts are instantiating of business requirements so use them (and the people who create them) to flesh out the enterprise BI and DW environment. "I don't think it's healthy to think that your central BI solution can do it all. The ratio I'm going for is 80% corporate, 20% niche," says Mike Masciandaro, BI Director at Dow, talking about the newest incarnation of spreadmarts: in-memory visualization tools.
- Safety Valves - Another approach to managing chaos is to coopt it. If users threaten to create independent data marts while they wait for the EDW to meet their needs, create a SWAT team to build a temporary application that meets their needs. If they complain about the fast and dirty solution (and you don't want to make it too appealing), they know there is a better solution in the offing.
- Data Tools. There has been a lot more innovation in technology than processes. So, today, organizations should strive to arm their data management teams with the proper tool for every task. And with the volume and types of data accelerating, IT professionals need every tool they can get.
So what did I miss? If you send me some tantalizing insights, I just might have to quote you in the report!
Posted May 19, 2011 9:25 AM
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