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Charting the Chief Data Officer’s Path to Success

A lot of obstacles need to be overcome to bring the power of data and analytics to government, but it's doable.

Many state and local government leaders have begun to embrace the promise of harnessing data to improve their jurisdictions' operations, fight fraud and better serve citizens. Examples abound: One state agency, for example, now can track spikes in patient symptoms to signal a possible epidemic -- or even a bioterrorist attack. Several cities now use algorithms to analyze crime data to predict where crime may occur next. And many revenue departments are fighting fraud and boosting tax compliance through data and analytics.

But for every successful data and analytics initiative, many other government agencies struggle with the most fundamental element: capturing accurate and timely data. Poor data leads to poor analytics, erroneous conclusions and bad policy.

To help ensure that their data and analytics programs deliver results, many states and municipalities have wisely begun to hire chief data officers. A CDO's duties typically include acting as the jurisdiction's chief data and analytics evangelist, but other essential responsibilities include promoting data sharing internally and externally, coordinating initiatives across departments and agencies, and seeing that these entities adhere to standards.

As anyone who has spent time in government knows, those are serious challenges, ones likely to involve bureaucratic obstacles ranging from institutional inertia to turf protection to internal politics. For CDOs embarking on a data and analytics program, here are a few key steps aimed at overcoming those kinds of challenges:

Create a written vision statement and communicate it to your organization: The statement should take into account executive or legislative goals and should be validated by the CDO's boss -- a governor, mayor or other senior executive. Seeking and maintaining executive support is the only way a CDO can succeed. Once the vision statement is approved, it should be posted on the organization's website and widely distributed.

Form a working group that will help develop a strategy: Find representatives from various agencies and organizations who understand the value of data and analytics for improving services and can provide input on possible test cases that could prove useful, identify their organizations' data and analytics assets, provide insights on their organizations' data-sharing culture, and make decisions on behalf of their organizations.

Inventory data assets: Any effective strategy requires that the CDO identify all of the data assets in place, under development and planned for the future. In doing so, a CDO should ask a number of key questions, starting with: What organizational components are in place to address data governance, data management and data analytics? Are the data assets internal or external? Are there memoranda of understanding or other agreements in place regarding sharing data? What technology is in place to support data and analytics processes? What techniques are being used to extract value from the data?

Understand existing data and analytics initiatives: This is important for a number of reasons, including the fact it may reveal synergies that can be built upon going forward and also may help avoid a circumstance where two agencies may be purchasing the same research content.

Identify opportunities to exploit data and analytics assets: A CDO should ask some key questions before selecting an initial data and analytics project, including: Does the project fit within the executive or legislative goals? Can it demonstrate value, and how quickly? Can existing projects be combined, and can a new project's results be used by more than one agency? Is there a clear business case? Will the project's results be sustainable, or is it a one-time insight? A CDO needs to find a balance between a project that can show quick results but may not be sustainable compared to a project requiring an infrastructure build-out that may be sustainable but could take too long to pay off.

Select and execute a pilot project: A well-designed pilot will demonstrate the benefits of data and analytics and prompt long-term buy-in from leadership. Lessons learned will help spread the use of the program to other agencies and departments.

Once that begins to happen, it's only a matter of time before an appreciation for the power of data and analytics can become ingrained in the culture of a government enterprise. The potential benefits -- providing solid results that benefit citizens -- are enormous.

This story was originally published by Governing.

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