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This report continues the IBM Center’s long interest in risk management with a specific focus on employing risk management strategies to reduce improper payments in the U S Department of Labor’s (DOL) Unemployment Insurance (UI) program. There is a long tradition of public management scholarship that has provided empirical support for the hypothesis that management matters for government performance. One specific management activity that has been growing in prominence in federal agencies over the last several years is risk management.

Professor Ho conducted a survey and phone interviews with city officials responsible for Big Data initiatives. Based on his research, the report presents a framework for Big Data initiatives which consists of two major cycles: the data cycle and the decision-making cycle. Each cycle is described in the report.

The authors collected data from a survey of 237 homeless program networks across the nation, as well as in-depth reviews and interviews of four CoC homeless networks in three states. While this report focuses on homeless networks, its findings and recommendations are applicable to networks in all service delivery areas.

This report continues the IBM Center’s long interest in risk management. This report, however, examines an aspect of risk management that is often overlooked: managing “organizational integrity” risks, based on a case study of four major public and private health care organizations. Professor Molina defines organizational integrity as occurring when an organization functions consistently with the purposes and values for which it was created. The report discusses two types of integrity issues an organization must monitor: integrity violations and integrity risks.