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1 Jun 2023 | |
CX & Trust |
Executive Summary
The U.S. government is ever-evolving and constantly improving. An intentional focus on the customer – or how individual citizens experience their government – ensures programs are designed well with the ultimate outcomes in mind. If successful, these efforts can also protect public trust in democratic institutions by demonstrating that the government serves its people as intended.
In recent years the Executive Branch prioritized efforts to improve the customer experience (CX). Notably in 2021, President Joe Biden signed an Executive Order (EO) that placed Customer Experience at the center of many federal agencies’ priorities. The EO recognized the complexity of the challenges facing the American people, and the opportunities for the government to better serve people and address various crises at the same time. In implementing the EO and other CX or government experience (GX) initiatives, agencies are prioritizing building capacity around leadership, CX strategies, resources, and communities of practice for staff. There are also identified barriers to these efforts: mission complexity, agility amidst changing trends, data sharing and collection, agency coordination, and resource gaps.
As agencies are building capacity, despite the challenges, there have been notable successes in the CX and GX stories:
Transportation Security Administration has been collecting data to better understand CX and develop a customer-centered approach, and TSA is also providing training and screening on CX across the entire workforce.
Looking across the examples and based on interviews conducted, there are five key recommendations about implementing effective CX initiatives in government agencies today:
Recommendation #1: Evaluation design experts should be consulted in the design of future CX analyses. Aligning with agency Evaluation Officers will ensure the CX activities can be part of agency evaluation plans and multi-year learning agendas and can help design data collection plans that emphasize longer-term outcomes.
Recommendation #2: Agency Chief Data Officers (CDO) should play a formal consultative role in the design of the CX projects. Ensuring the CDOs and the implementation of the Federal Data Strategy are prioritized as part of the overall strategy and resourcing equation will also ensure that the CX projects receive the support needed for data capabilities. In addition, agency CDOs should incorporate CX activities in agency data strategies.
Recommendation #3: Consult with federal statistical officials and experts on CX survey designs. Conducting surveys and burdening the American people with data collections is not a matter of convenience – it is a priority that the information collected matters, is useful, and will be used. To improve the usefulness of CX surveys, CX teams should collaborate with the agency’s statistical official to appropriately design surveys.
Recommendation #4: Agencies should consider the diversity of the American public when collecting data. When agencies are collecting new data from the American public to support CX initiatives or to measure outcomes from the initiatives, they should consider specifically that there are different subpopulations of the American population.
Recommendation #5: Agencies should align tools to be adaptable and ready to support adoption of artificial intelligence capabilities. With the emergence of new capabilities for artificial intelligence (AI) that are rapidly coming online in public and private sectors, agencies should prepare the CX and GX initiatives to adapt AI capabilities quickly, including by ensuring data quality and open data assets are prepared for relevant migrations.
The current efforts to promote user-center and human-centered design for CX and GX initiatives in the public sector are a promising approach for promoting public trust in democratic institutions. These approaches can still be continually strengthened. Continued efforts will be needed to ensure customers and citizens benefit and truly experience their government as intended.
Project Team
Disclaimer
This paper is a product of the Data Foundation, sponsored by Informatica and TD Synnex. The findings and conclusions do not necessarily reflect the views or opinions of the Data Foundation, its funders and sponsors, or its board of directors.
© 2023 Data Foundation. All rights reserved. This content is for general informational purposes only and should not be used as a substitute for consultation with professional advisors.
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