What does the word transparency mean within the data management profession? Transparency is the degree to which your organization communicates to your producers and consumers of data management information. It's easy to declare that you are open when in reality you are not. You are not open because you protect the very essence of your existence through various means of command and control. Take the simplest example - metadata. For years, I have heard from data professionals that metadata is a database technology and not to be used by other technology groups. Metadata is data about data and nothing else. You cannot use metadata to describe Web pages, services or systems. Why? Not because there isn't a tremendous amount of value in the metadata, but rather, because data professionals are the only ones with the expertise. Of course, that's unfair. Or is it?

One of the main benefits of transparency is accountability and the inability to hide behind a process or technology. We want to have public discussions and share knowledge about the data environment, not close it down and protect it. We are addicted to email, which is a one-to-one communication medium, and repository applications, which are one-to-many communications. The data model is a one-to-many communication medium, although in most companies it's more like one-to-few. These are legacy type communication media that must be transformed within the next few years.

When you open up your organization, then you allow a deep visibility into your processes and deliverables. For your customers, you can show how you delivered the products and services. This allows another set of eyes to evaluate your business model as well as develops deeper relationships with your customers. Hence, you develop trust and partnerships with the very group that generates value from your efforts. Most of us have producers that we serve alongside consumers. Producers want to see inside your group as well. What are you doing with the data definitions or business rules you collected? How and where is the information being accessed by your customer base? We create bonds and actually act as an intermediary, not as a barrier to progression.

Here are a few key reasons that data management organizations need to get transparent.

Transparency engages the enterprise. One of the most important aspects of productivity is to engage the passion of every employee. It you can tap the energy and get focused on a specific business objective, magic happens. Social software engages employees in a conversation, which, in turn, will engage them into the data business. Data professionals want to be part of something bigger than themselves, and this communication medium will provide that opportunity.

Open organizations perform better than closed ones. Clearly, when you get more people involved and share information, the level of productivity increases. The more people contribute to the body of knowledge, the better the information provided will become. There are hundreds, if not thousands, that have data experience within your enterprise. Due to mergers or priorities, they may not have direct responsibility for the data management function. However, their experience can be invaluable to the overall project.

Transparent groups generate more value to a wider audience. If you study the actual usage of data management deliverables, you will have to admit that the usage is quite low. In most cases, very low usage doesn't really enable a huge amount of reuse or knowledge exchange. Like Wikipedia, the more people that access and update information, the higher the quality of information that emerges. Data management deliverables evolve to what the customer needs, not what we tell them they need.

Transparency lowers the cost of data management. Cutting costs is a central theme of business and IT today. Data management can be expensive, depending on the size of the program and resources required. Utilizing collaborative applications lowers the cost of business by improving productivity, increasing the speed of delivery and eliminating corporate friction. Social networking tools allow you to locate other resources that can help you or communicate your message.

Data Quality Improves with Many Eyes

In the open source world, they have a saying, "All bugs are shallow with many eyes." Basically, this means that if you have enough people looking at a problem, then the solution will be straightforward. With a distributed workload, no single person will be burdened by the entire issue. The same thing applies in the data management world. How long would it take you to locate a data quality problem if 5,000 people are looking for it? I remember my very first data quality audit, where we created a collection of 20 edits for the customer master file. The problems were so bad that we generated 15,000 edit cards. One afternoon, all 125 employees spent two hours fixing and correcting the problems. From then on, we only had about 10 errors per day and a near perfect data environment.

Transparency is the key for long-term value-add for the data management organization. Change is coming; you can either be on the leading edge or wait till management thinks it's a good idea. Hopefully, it won't be too late by the time they come around. 

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