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Establishing a roadmap for government data analytics
It takes less time than you think
By: Erin Stevens, Systems Integration Manager, SAS
Lately, there has been a great deal of emphasis placed on the government’s need to harness the power of “big data” and “analytics” – for everything from the early detection of global and insider threats to entitlement and tax fraud.
In fact, the 2010 Government Performance and Results Modernization Act (GPRA) turns advancing government data analytics from a desire to a mandate. After all, the public sector could save billions of dollars annually if it harnessed the latest string of innovative analytics and data management techniques.
Technologies such as grid, cloud, in-memory processing and data visualization help organizations get more from their data.
For the uninitiated, the thought of adopting government data analytics can seem like a daunting undertaking – especially within the federal IT sphere, where actions that are not expressly permitted are often forbidden. It isn’t easy to identify the appropriate analytics-based solution among all the variables, tools and technologies. And that’s before you even consider an agency’s specific needs and compliance mandates.
Even when a government agency is successful in its identification of proper solutions, it has to overcome some amount of institutional inertia. This deeply ingrained attachment to “the way things have always been done” can be strong, even if these traditional approaches no longer support the agency's mission.
Create a strategy for government data analytics
Before an agency can identify a technology that meets its unique mission, it must first look inward. It must migrate itself to a more permissive IT culture and facilitate the mind-meld that is necessary to build a common, innovative vision.
This realignment taps into previously unengaged stakeholders to better understand an agency’s needs and uncover clues as to how analytics might further strategic goals. This leaves the agency well-positioned to craft a unique strategy and adopt a modern IT mindset. Organizational education also frees up IT managers to prioritize more high-level, strategic decisions about compliance and security.
An organization with a grasp on where it could benefit from analytics can then organize a steering team to map out more agile practices and support the further evolution of processes. For example, a working group can include an enterprise architect, a systems engineer with a background in fraud detection, an account executive with operations experience and a data management subject matter expert.
Private-sector partners can also provide an additional scope of work and subject matter expertise (such as fraud, logistics, national security or insider threat). Thus, agencies can consider their existing tools and processes against potential infrastructure hardware and analytics software in an informed and holistic way. The goal is a predictive “analytics factory” that formalizes ongoing processes for analytic data preparation, model building, model management and deployment. The agency can then quickly identify questions, attain solutions and streamline improvements.
Through the development of an “analytics road map,” the agency emerges with:
- Documentation of its current analytic outputs, processes and architecture.
- Future vision.
- A higher level of education and support across the organization.
The assessment also allows government agencies to find technologies that best exploit data at their disposal. For example, technologies such as grid, cloud, in-memory processing and data visualization help organizations get more from their data by increasing processing speeds, improving user access to analytics and visually analyzing complex data.
Prescribing a set of analytics solutions that best suits an agency’s unique needs not only empowers the development of a long-term strategic data road map, it frees up human capital to focus on their federal mission, whatever it may be.