When I talk to customers about dealing with poor data quality, I consistently hear something like, “We know we have data quality problems, but we can’t get the business to help take ownership and do something about it.” I think that this is taking the easy way out. Throwing your hands up in the air doesn’t make change happen – it only prolongs the pain. If you want to affect a positive change in data quality and are looking for ways to engage the business, then you should join Barbara Latulippe, Director of Enterprise Information Management for EMC and and Kristen Kokie, VP IT Enterprise Strategic Services for Informatica for our webinar on Thursday October 24th to hear how they have dealt with data quality in their combined 40+ years in IT.
Now, understandably, tackling data quality problems is no small undertaking, and it isn’t easy. In many instances, the reason why organizations choose to do nothing about data quality is that bad data has been present for so long that manual work around efforts have become ingrained in the business processes for consuming data. In these cases, changing the way people do things becomes the largest obstacle to dealing with the root cause of the issues. But that is also where you will be able to find the costs associated with bad data: lost productivity, ineffective decision making, missed opportunities, etc..
As discussed in this previous webinar,(link to replay on the bottom of the page), successfully dealing with poor data quality takes initiative, and it takes communication. IT Departments are the engineers of the business: they are the ones who understand process and workflows; they are the ones who build the integration paths between the applications and systems. Even if they don’t own the data, they do end up owning the data driven business processes that consume data. As such, IT is uniquely positioned to provide customized suggestions based off of the insight from multiple previous interactions with the data.
Bring facts to the table when talking to the business. As those who directly interact daily with data, IT is in position to measure and monitor data quality, to identify key data quality metrics; data quality scorecards and dashboards can shine a light on bad data and directly relate it to the business via the downstream workflows and business processes. Armed with hard facts about impact on specific business processes, a Business user has an easier time affixing a dollar value on the impact of that bad data. Here’s some helpful resources where you can start to build your case for improved data quality. With these tools and insight, IT can start to affect change.
Data is becoming the lifeblood of organizations and IT organizations have a huge opportunity to get closer to the business by really knowing the data of the business. While data quality invariably involves technological intervention, it is more so a process and change management issue that ends up being critical to success. The easier it is to tie bad data to specific business processes, the more constructive the conversation can be with the Business.
So, I’m a complete sucker for the courtroom scene in the Rob Reiner film “A Few Good Men” for a number of reasons: it was written by Aaron Sorkin (loved West Wing and Sports Night), it’s a classic Jack Nicholson scene, it is one of Tom Cruise’s roles where he actually does some acting, and it’s a great 6-degrees of Kevin Bacon movie (I mean, it’s got people from Demi Moore to Cuba Gooding Jr. to Kiefer Sutherland, to Noah Wylie – think of the connections you could make with just those actors). I get sucked into this scene whenever I click by it on the television. (more…)
A recent trip to a supermarket in Telluride, Colorado struck me as a funny place to find an analogy for data quality, but there it was. You see, supermarkets here require you to bring your own bags to cart your groceries home. Those brown disposable plastic bags are banned here – the town has made a firm commitment to the philosophy of Reduce, Reuse and Recycle. By adhering to this environmental philosophy, data integration teams can develop and deploy successful data quality strategies across the enterprise despite the constraints of today’s “do more with less” IT budgets.
In the decade that I’ve been in the Information Management space, I’ve noticed that success in data integration usually comes in small increments – typically on a project by project basis. However, by leveraging those small incremental successes and deploying them in a repeatable, consistent fashion – either as standardized rules sets or data services in a SOA – development teams can maximize their impact at the enterprise level.