I was a member of the jury of the Data Quality Award recently. One particular thing did strike me in reviewing the cases that were entered and in listening to the presentations of the nominees. When asked what they thought they could further improve, almost all nominees responded that they thought data quality wasn't on the executive radar screen enough. There was not much executive commitment.
When you think about it, this is actually rather understandable. First of all, every project in the organization claims to be strategic and in need of executive commitment. In a larger organization, I bet that if you add up all projects that claim time on the executive calendar, you end up with working hours of more than 24 hours a day! Second of all, I think it is also the nature of the subject. There is 2 ways of doing data quality: perfect, which is normal, or bad. There's hardly any way to "score" with the subject, other than when the status quo is really horrible and blood is coming out of the project in every direction. It's like the salary administration, crucial, but you can't really score points with it, perfection is the norm. Fortunately, perfection is usually the case with salary admin, however unfortunately, it is rarely the case in data quality initiatives.
I think data quality professionals mostly have themselves to blame for not being on the executive radar screen (unless they fail). Data quality projects are usually too focused on getting the customer addresses right. As important as this is, it doesn't "wow" people. Data quality should evolve beyond the customer address. Data quality professionals have a specific set of skills. They are good in detecting incorrect or incomplete data, they are able to fix it, and they are able to connect different data sources. Here are some ways to leverage those skills in more strategic ways:
Make a customer value proposition out of customer self-service. Think of advance check-in for flights, promotions to register for, order status checking, anything that makes it the best interest of the customer to deliver perfect data. The moment data quality is connected to new ways of interacting with customers, it becomes more strategic.
Broaden up the scope of data quality. Master data management is a topic very close to data quality skills. Make sure your skills are indispensable in communicating throughout the complete value chain, including partners, suppliers and customers. The moment perfect master data optimizes the value chain and contributes to operational excellence, it becomes more strategic.
Make sure you are part of Business Development initiatives. If with your specific skills you are able to piece together data during merger and acquisition due diligences, and your insights on previously unintegrated and "soft data" lead to better decisions, or equally important, faster execution, your skills have become extremely strategic.
These are your career tips for the week!
frank
Comments (1)
I'm surprised data quality on data entry hasn't got a much higher profile. A lot of the data quality vendors seem to be working on data where the horse has already bolted. There is some good simple DQ work on sites like Digg and Delicious that helps rather than hinders data entry. By comparison a lot of business data entry forms are nasty.
We had some bloggers trying to improve the profile of data quality at the "Carnival of Data Quality #1 - Make Data Quality Interesting" published on my blog just last week. You can visit it by clicking on my name, I hope some Oracle bloggers can submit to issue #2 at the DQ Trainwrecks blog.
Posted by Vincent McBurney | December 8, 2007 4:59 AM
Posted on December 8, 2007 04:59