Technology + Culture equals the Formula for Data Management Success

Sumit Nijhawan
CEO & President-Infogix
Tuesday, October 20, 2015
Sumit Nijhawan
Why simply drawing conclusions from your data won't cut it.As data continues to grow at explosive rates, are you making sound business decisions based on quality data?

Is your data-driven culture driving operational processes to continually produce quality data? Working with a wide range of data intensive organizations throughout the years has made one thing certain - As Lord Kelvin coined years ago, "If you cannot measure it, you cannot improve it." That couldn't be truer when it comes to improving the quality of your data.

If you already have point solutions, created with a narrow application scope, in place to semi-automate data integrity, it's often cost prohibitive to scale it to an enterprise process level. As Albert Einstein said, "We cannot solve our problems with the same thinking we used when we created them." To take data quality to the next level requires a different approach built on a philosophy of end-to-end standardized data controls that comprise business rules-based automation and real time visibility to change the way in which we solve the problem.

To be successful, an organization must be able to measure data quality at an enterprise level as a key component of data governance. This often isn't the case from my experience. I often see KPIs on data quality that are done in silos throughout the organization, which results in organizational chaos when answering a simple question like, "What is the health/accuracy of the data across a business process?" I often get answers such as, "there are a number of discrete KPI measurements for specific systems," but seldom do I hear that there is management oversight and actionable dashboards with metrics on the data quality of the business process in its entirety.

While technology is the enabler for process change, data governance can be the vehicle to corral the organization around a new way to improve data quality. I've seen many initiatives falter because culture eats technology strategy for breakfast if everyone expects technology to be the primary driver for change. This is why data governance is a pivotal element for culture change to tie together people, process and technology.

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