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MeriTalk

Eliminating Silos in IT/OT Cybersecurity Is a Funding Challenge, Not a Technical One The FedRAMP High Supply Crisis Is a Federal Security Problem – Not a Procurement Footnote How More Tightly Focused Software Development Initiatives Will Unlock Innovation Across Government Transforming Federal Cybersecurity Through Private Sector Innovation Evolving Zero Trust and Embedded AI – Federal Government Cybersecurity Predictions for 2026 Unlocking AI’s Potential in High-Assurance Environments Accelerate Agentic AI in the Federal Government: Top Takeaways Why Congress Must Reauthorize the Technology Modernization Fund Make Cybersecurity a Key Ingredient of Modernization How Spectro Cloud’s PaletteAI Secure helps agencies scale AI securely, compliantly, and confidently Fix the Foundation: How Hybrid Cloud and Trusted Data Enable Government AI New Google Workspace Cost-Saving Offer Available for U.S. Federal Government Reinventing FedRAMP in the Age of AI Balancing Security and Efficiency: The Federal IT Dilemma in the AI Era Meeting Evolving State and Local Cyber Threats AI Is the Solution to Stop AI Data Theft Enhancing U.S. Government Operations with AI and Human-Centered Design How FinOps Can Help Agencies Slash Cloud Costs in 5 Steps Will Quantum Computing Weaken or Strengthen Cybersecurity of Federal Systems? Improving Citizen and Federal Employee Experience with Virtual AI Assistants Strategies for Securing the Federal Supply Chain Reframing the U.S. Government’s Approach to Cybersecurity Oversight Three Steps Agencies Can Take to Meet Government’s AI Requirements The Impact of NIST’s PQC Standardization on the Federal Cybersecurity Ecosystem Generative AI is Revolutionizing Federal Government Operations NIST’s new PQC Algorithms and What They Mean for Federal Agencies Addressing the U.S. Quantum Labor Shortage Before It’s Too Late How a Community Vigil Approach and Secure by Design are Critical to Software Cybersecurity Addressing the Talent Shortage: How Digital Government Improves Satisfaction, Retention Here’s What We Can Learn (and Do) About Cybercrime from FBI’s Latest Internet Crime Report Implementing AI Assurance Safeguards Before OMB’s December Deadline The Next AI Wave: Quantum AI CDM’s Evolution to Non-Traditional Technology: Why Now and How Will it Succeed? 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Increasing Equity Through Data and Customer Experience
MeriTalk Sta · 2022-09-21 · via MeriTalk

By: Santiago Milian, Principal, Booz Allen; and Jenna Petersen, senior lead technologist, Booz Allen

From housing assistance to community health to closing the digital divide, equity is on the agenda of multiple Federal agencies. But making Federal services more equitable demands a close look at how constituents experience them.

Do services address the full breadth of a constituent’s challenges and needs? Are people able to get what they need with minimal delays and frustration? And are programs being tracked and held accountable for results?

Progress – and Gaps – in Customer Experience

Federal agencies have been improving in these areas. For the second year in a row – and even during a global pandemic and political turbulence – Federal agencies have improved their collective scores for customer experience (CX), according to a 2021 Forrester report. But the average Federal CX score – 62.6 out of 100 points – still lags behind the private sector average by a full 10.7 points.

These metrics matter. When private sector companies fall behind, they know immediately through their revenues and stock prices. Public sector organizations must also track progress to gain and retain trust amongst the public, maintain accountability, and shape future funding decisions related to CX and equity.

This is where data collection and analysis come in, increasing program accountability and transparency in order to improve the public’s trust and confidence. But tracking CX progress is just one way in which data can lead to greater equity in Federal services.

Data Ensures Services Reflect the Full Complexity of Needs

Many factors affect how a person experiences inequity. Consider, for example, the homebuying experience. What’s holding underserved homebuyers back from their goals, and how can a Federal program help?

Potential homebuyers may lack the kind of support network that helps establish credit history or overcome weaker credit ratings. They may experience racism or unconscious bias from lenders, real estate professionals, and appraisers, or may simply fall victim to the systemic biases built into the credit system itself. Based on their personal experiences or those of their close personal networks, they may not see homeownership as an achievable goal or a means toward financial security, or they may not trust in the underlying systems that support the homeownership ecosystem.

Data, both qualitative and quantitative, helps Federal agencies understand how inequities persist, how they affect people’s lives, and how they can be overcome. Among these complexities, Black women may face different challenges than Black men due to the intersectionality of race and gender. People with multiple underserved identities often face multiple burdens. Analyzing intersectional data ensures that constituents with multiple identities and challenges have their unique needs met, too.

In short, data helps Federal agencies center underserved constituents in their efforts—one of the core tenets of equity.

Lowering the ‘Time Tax’ With Data and Trust

Equitable services are easy for people to access. To find out how a program rates in this area, consider the following questions. Are eligibility criteria transparent? Is maintaining eligibility burdensome? Do those in most need know what’s available?

Difficulty navigating the issues above results in a “time tax” of delays and frustrations. This time tax is often highest for those with the fewest resources.

Federal agencies can use data to reduce the time tax, creating a comprehensive picture of challenges, needs, services constituents already participate in, services they’ve applied for, and services they are eligible for. With all of this information in one place like a cross-government CRM, the government can use this data to proactively serve customers with all the benefits for which they are eligible.

Meanwhile, staff can use pre-existing data and cross-agency collaboration to process applications and approvals more swiftly. Take, for example, the rapid mailing of millions of stimulus checks during the COVID-19 pandemic. Thanks to IRS data, the government already knew about income – and this saved administrative staff and recipients time and hassle.

Making this work requires trust. Agencies must engage more directly and meaningfully with traditionally underserved populations. They will need to understand their perspectives, challenges, and drivers for their behavior, and they will need to rebuild trust such that the traditionally underserved are willing to engage once again. Finally, agencies must be transparent about data collection and use: allaying fears of discrimination and communicating the benefits of data sharing.

With these tactics and caveats in mind, Federal agencies can turn knowledge into power, to deliver the American people more equitable experiences and more responsive services.