Spring Clean Your Data

Evolve Your Data From a By-Product to an Asset


In the early days of data management (let’s say the 1990s-2000s. A lifetime ago - if you’re a millennial!) data quality was a cog in IT’s gears to support each incremental and ultimately disappointing attempt to get the business to start embracing that massive data warehouse investment.   Data quality was a tool, but not yet a discipline, because data was an organizational by-product - not an enterprise asset.

Fast-forward to today and there’s not an industry in existence that hasn’t been disrupted or transformed by the explosion of data in one way or another. Conventional wisdom says those companies that can most efficiently and effectively harness the power of that data will dominate their markets.  

So how do we get started with this “harnessing the power of data” concept?

Well as Uncle Ben told Peter Parker (aka Spider-Man), “with great power comes great responsibility.”   Unfortunately, the data captured and available to your organization isn’t magically fit-for-use just because business leaders are ready to use it. Like any enterprise asset, data must be effectively – and responsibly - governed and managed. A key to data governance success must be for data quality to become a valued and embedded competency across the organization. But for most organizations, it will be a daunting challenge to remove the data quality blinders that have been worn for many years.

The key is to avoid the trap of hoping to sell a business case for a standalone data governance, data quality or master data management investment. Data is an enabler – not the thing you’re trying to achieve.

The secret to success is to understand your organization’s key strategic imperatives that already command strong business sponsorship and support. Common initiatives across many organizations include customer-centricity, regulatory compliance, application consolidation, advanced analytics, etc. Identify the key strategic imperatives within your organization and evangelize the need to incorporate data quality competencies and investments as a critical success factor.   The best way to accomplish that is to convince senior leadership to require measurement of the quality and security of critical data as a key performance metric for the initiative to be considered a success.

Good luck!

The march toward exascale computers
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