Evolving Your Information Governance Strategy – MDM & Data Governance Summit 2013

January 9, 2014 David Williamson

Image_David Williamson at MDM & Data Governance Summit

Every year hundreds of Master Data Management and Data Governance professionals gather for a 3-day conference focused on giving attendees the keys to successfully advance their MDM to the next level.

This year, the MDM & Data Governance Summit in New York was able to deliver another amazing crowd of trend-setting vendors, thought leading speakers and eager MDM innovators. BackOffice Associates was among the many vendors looking to expand attendees’ knowledge in effective MDM and Data Governance solutions.

I had the pleasure of speaking at this year’s event with a developing topic that caught the attention of many attendees – the importance of data quality initiatives for effective Information Governance.

My presentation, Managing Your Data Quality Initiatives: An Essential Building Block for Information Governance was based upon this overall theme – the goal of Information Governance, which is simple to understand but often difficult to achieve, is to ensure the effective and efficient use of information to achieve your business objectives.

It’s hard to ignore all the hype around “Big Data”. The truth is that the volume of data is growing at staggering rates – some estimate this growth could double every 18 months and data volume is only part of the problem. It’s also about the variety of existing data, and the velocity of new data, that we need to contend with. Data exists not only within your traditional network stores, but also externally in cloud environments. This is when you need to ask yourself, with all the structured and unstructured data you’re dealing with, what data is relevant and is it valid?

Establishing an effective Information Governance strategy is critical because the reality is, the DNA of your business resides in your data. Strategic business insights, and the ability to execute critical business processes, both rely on your data being complete and accurate.

Without a proper Information Governance strategy in place, your business is at risk. Bad data will invariably lead to business process failures, lower operating efficiency and result in loss of revenue. Even worse, your business may also face significant compliance issues, or place the safety and well-being of your staff at risk. Gartner estimates that companies that aggressively address these issues of data quality will financially outperform their peers by more than 20%.

The fact is that your long term Information Governance strategy will not be defined or completed overnight.  You will need to start with small targeted areas of focus and then quickly build on the success of those early efforts to meet the demand that will invariably grow.

You will need to equip yourself with the right tools for the task, but Information Governance is about much more than just technology.

You need to define the data standards that the project will be measured against, determine the data stewards who will be tasked with upholding those standards and make sure that the improvements can be followed through easy to understand metrics.

Finally you will need to find the balance between ensuring the highest quality before new data is even introduced (Active Data Governance) and fixing the mistakes that have already been made (Passive Data Governance).

In the end, Information Governance is a not discrete event but a journey.  It will not be easy, but ultimately it will guarantee the future of your company.  With that in mind, the question should not be whether you have the time to worry about Information Governance, but how much time do you have left if you do not start to worry soon.

 

About the Author

David Williamson

David Williamson’s role as Vice President of Financial Services Industry leverages his considerable experience in data quality and data migrations for SAP and other major ERP environments. For 10+ years, Mr. Williamson has successfully led Data Governance and MDM projects at a variety of Fortune 1000 companies with the most complex data environments.

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