Every agency’s data journey is different. It often varies based on mission, culture, internal processes and workforce skill sets. But there’s a common challenge that isn’t unique to any one agency, large or small.
“The issue is that agencies often have isolated applications that only address specific needs. However, to find real value in that data, they need to move toward an interconnected set of solutions that enable them to take advantage of artificial intelligence (AI).” – David Bargh, Cloud Solution Manager at SAP National Security Services (NS2)
Real value has come in the form of augmenting critical decision-making across mission areas, Bargh said. He has seen the firsthand benefits of improved services as agencies integrate AI into their modernization efforts. At SAP NS2, the team collaborates with government customers to offer an array of analytic solutions that create a data environment conducive to security, productivity and interoperability.
Bargh detailed three key areas that agencies should prioritize to deliver data-driven outcomes.
1. Data integration
Bringing data together across all functional lines of business and mission areas to achieve a single view of agency performance is vital, Bargh said.
“A key challenge that we see in many agencies is integration,” he said. “An actionable step there is to provide or have a data platform available so you can put information into context.”
For example, agencies must understand their budgets — whether for travel or training expenses — in greater detail. Just knowing what you spend on training isn’t enough. How do those costs break down across lines of business, and can you quickly reallocate funding if needed?
2. Areas of improvement
“Most agencies today can meet their responsibilities, but how do they improve and reimagine success?” Bargh said. “The greatest area that I’ve seen for improving and expanding services is artificial intelligence.”
It’s not just about having a great data platform or great integration. How are you going to analyze that data? Using AI, agencies can learn and glean insights from their data, ultimately making better decisions.
Back to the budget example mentioned in the previous section, AI can play a critical role in making reallocation decisions and projections based on current and historical data and other factors.
3. Augmenting decision-making
The ultimate goal for agencies is to make sound decisions in a timely manner.
Whether the end user is a doctor providing patient diagnoses, a field office worker making environmental decisions or a soldier needing real-time data feeds, the margin for error is slim. They need reliable information to augment their current knowledge about a situation or issue, Bargh said.
As agencies grapple with the increasing number of retirement-eligible employees, they’ll also need sound and timely data to make workforce decisions and address knowledge gaps.
Agencies’ data journeys often differ, but the building blocks for success remain the same, Bargh said. “Real value is achieved when agencies can connect their data, apply AI to that data and augment their decision-making.”
This article is an excerpt from GovLoop’s new guide, “Agency of the Future: Common Misconceptions Holding You Back and How to Break Free.” Download the full guide here.