I recently had to appear in court due to my failure to display my insurance information during a routine traffic stop. I was not able to pay the fine online due to the nature of the violation. As someone who thinks about data management and data quality on a daily basis, I had obviously done a bad job of correctly migrating my data (my insurance card) from one location to another (between my old and new wallet). However, my later experience at the courthouse provided some interesting insight into the natural trend to allow our processes to degrade without review or reassessment.
I arrived almost an hour early to find a long line of fellow violators ahead of me . After providing our violation information we were given numbers (mine was 29). We then sat and waited for the proceedings to begin. During this time, some of us discussed the events that led us to this moment in time. Some took responsibility for their actions while others claimed that they had been entrapped. . Still others bragged that they had been given a slap on the wrist and had gotten away with far worse. I guess this is the usual behavior of criminals when they congregate or at least that is what a lifetime of prison movies and television police procedurals had lead me to believe.
Eventually the judge arrived and the court session began. I was shocked to discover that the judge immediately called a case which appeared to have a long history and involved negotiating payment schedules between two small business proprietors. This first case took about 20 minutes to hear. It was followed by cases involving domestic abuse and public drunkenness. Between these cases, the more minor violations were called. Hours passed while I waited for my number to be called. Once called, I quickly pled guilty and provided the necessary documentation, at which point I moved over to the payment line. Once again, there was a single line at the payment counter. Whether we were scheduling payments for thousands of dollars in fines, or renegotiating scheduled payments, or simply swiping our credit cards for a one time payment, we all waited on the same line and were given the same priority. There were many angry tax payers on that line by the end of the long day.
We have all probably had a similar experience, whether it is in dealing with a government agency or the technical support staff of our cable provider. In this case, it appeared that the process had been designed to fill in the day as best as possible. To allow the employees to keep their day occupied from opening to closing. But little attention has been paid to the experience of the client.
Perhaps this had been a good model at some point, but clearly it had not been adapted to the changes to the market and to the conditions around them.
I bring up this anecdote because this is what occurs every day in our corporate lives. We simply follow a pattern of behavior that was established when our business was significantly different. By not reassessing what our business is today and looking at our process with new eyes, we run the risk of misuse and poor allocation of our resources. Every day, we see processes that can be improved, yet we fail to act and make necessary changes. There always seems to be a reason to delay, or a reason to wait for someone else to change the culture, but the reality is that everyone needs to participate in the process.
Which brings me back to the topic of data quality and governance; in this uncertain business climate it may be very hard to begin a new initiative or gain any traction in implementing a complex new data quality initiative but by identifying and fully leveraging our existing assets we may find that we can get most of the way there with relatively little added effort.
So what are some general strategies that anyone can implement to assess and improve their data quality initiatives?
First, identify your assets. You are already managing data. The problem is that you are doing it informally. As part of a data management initiative you will need to structure your efforts. An initial assessment will allow you to discover what you are doing right and wrong. You’ll also be able to identify those thought leaders in your process who will be formally enabled to monitor progress and enforce your standards going forward.
Second, instill definitions and standards. Definitions must exist at an enterprise level. Without a strong foundation of metadata standards you cannot begin to properly align your efforts across the enterprise. Imagine hiring a consulting team to build your data warehouse. Upon arrival, the team finds a universal taxonomy across all data sources. This will greatly enhance their efforts and minimize cost overruns for your project. True universal and strongly-enforced metadata standards may not always be possible. Corporations merge and there are cultural and linguistic barriers. However, there must still be standardization within individual silos. Once these are defined and enforced, mapping across them is far simpler. Despite the complexity of this endeavor, the job is far more difficult for some external service provider with no relationship to your data. Too often, the expectation is that a third-party will be left responsible for this crucial step, even though they have no relationship with the enterprise’s data. This can lead to significant complications during data integration. Just search Google for “Nike and i2” for a very public example of such a situation.
This leads us to our third point, which is possibly the most complex – Enable cultural change. To implement a true change to our business process, you need to get everyone on board. We all know how hard it can be. Some will see any change to your business process as a threat to their current status, while others will simply push back against a new process that may disturb their comfort with the current system. Meanwhile, management may assume that any change of process will lead to a new department and expensive new resources down the line. But there are simple changes that can be implemented that are unobtrusive and can reap significant rewards.
A case in point is the position of the Director of National Intelligence. The 16 different US intelligence agencies are notoriously uncooperative. This combative culture leads members of the different organization to be competitive and proprietary about data. This silo mentality prevented the sharing of urgent information. Following the September 11th attacks, a new office was defined for a Director of National Intelligence. While there has been continuing push-back from the various agencies, and the position has been difficult to keep filled, there has nonetheless been a huge improvement in collaboration. The primary reason for this was the creation of “A Space”, an online forum where roughly 1,000 intelligence analysts post, share and evaluate each other's data daily. A CIA veteran Paul Pillar states in an interview with NPR earlier this year, "There is absolutely no question that the amount of collaboration is far more extensive than it ever was in the 38 years that I spent in the intelligence community."
This example makes the point that even the most entrenched cultures can change, if a collaborative space is created and maintained to allow the process to take shape. Building and maintaining such a space will encourage participation.
We live in an age in which the market is ever changing. Old business paradigms are shifting. Businesses need to be able to move with agility. Often times, a simple redesign of a current process can deliver a desirable result – with little added effort or cost. It is the same with your data quality initiatives. Take ownership of your data and reassess your current data management process and you may be surprised to find that you are closer to your goals than you think.
