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Why digital transformation success will depend on data governance

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Want your digital transformation strategy to succeed? You need a rock-solid data governance framework.

The imperative is there—some 85 percent of enterprise decision makers believe they have only two years to integrate their digital initiatives before falling behind their competitors, and 27 percent view digital transformation as a matter of corporate survival, according to research by cloud services provider Advance 2000.

But regardless of the reason an organization undertakes a digital transformation—be it to glean operational insights, change the way it engages with customers or to set the stage for other emerging technologies such as machine learning and artificial intelligence—it needs reliable data as its foundation. And that requires robust data governance.

Some consider data governance essential only for cross-departmental collaboration—such as sharing patient data. But it also plays a key role in turning taking seemingly unrelated sources of data and turning into insightful sources of information.

Data governance uses a set of defined roles, processes and policies to help manage data assets and ensure their integrity, accuracy and security. Without these structures and controls, data assets lose much of their strategic value. Without effective data governance, no one can be certain about what data assets an organization has, who controls them, what information they can provide and how they should be used. Under these circumstances, a digital transformation initiative would simply break down.

Here are five steps to ensure that sound data governance underpins the organization’s digital transformation efforts.

Assess the data’s value. Begin by identifying the goals, scope and stakeholders associated with the different types of data that the organization collects. Then, create a list of possible use cases for each type of data. This will help executives estimate the data’s value and the costs associated with realizing and increasing that value.

Conduct a maturity assessment. What’s the status of the organization’s data? How clean is it? How accessible? After this has been determined, consider what needs to be done to ensure that the data can be used to support key transformation initiatives.

Develop a mission. If the goal is to prep data for use in specific applications, the data governance mission should reflect this. So should the rules, processes and standards that the data governance body adopts.

Establish a roadmap. How will the organization get from where it is to where it needs to be? That’s the purpose of a roadmap, which should spell out the approach it is going to take. For example—does it hope to roll out the data governance program with a big bang, or is it planning to phase it in more gradually? And remember, the roadmap shouldn’t end when enterprise-wide data governance takes effect. Future change management should also be part of the plan.

Bring data governance to life. To make the governance plan tangible, adopt a detailed set of guidelines and standards. Also, set a timeline for when each phase of the data governance rollout will be completed. Any management and employee training that is envisioned should be a part of this schedule. So should any plans to measure the program’s success and make any necessary course corrections.

In the end, data governance provides the same benefits it always has, including better data quality and consistency. But in a world of digital transformations, good governance helps manage unstructured data from new sources, such as those that may outside of a healthcare organization, IoT devices and the location data collected by smart phone apps. It also supports regulatory compliance efforts, such as those needed to conform with HIPAA requirements.

By making data governance the cornerstone of a digital transformation initiative, organizations can leverage the value of their data to unlock new opportunities—including support for new business models, improved customer service and using advanced analytics to generate important new cre delivery insights.

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