How Quality Data Equips Federal Leaders for OMB’s Reorganization Plans

The recent Office of Management and Budget memorandum (M-17-22), requiring a comprehensive federal government reform plan, is a clear signal to every federal leader for the need to prepare for deep and lasting changes to how we do business. We see this as a rare opportunity with just the right conditions for bold leadership.

By offering significant political cover, the OMB order creates the ideal environment for proactive leaders to re-examine the fundamentals of our government’s operational capabilities, performance management and outcomes. It opens the door for us to challenge some of the most intractable barriers to federal government reform.

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To support federal leaders as they respond to the OMB order and implement the requirements that will follow, we co-authored the paper, Data Powered Leadership Reform: A Business Case for Federal Operational Improvements Enabled by Quality Data.

We address four key issues in government management: The broader business case for improving federal workflows, the importance of secure and shared quality data to support this reform work, the realities of federal bureaucratization as a defined management concept and specific policy recommendations for federal leadership to act upon.

One of the persistent problems we address is the prevalence of inadequate operational data. As a result, federal leaders are forced to work around the data, rather than use the data to improve their operations.

Federal leaders pursue quality data for basic management needs, such as evaluating cause-effect in performance or testing alternative operational designs. Leaders need data to know how their changes in operational or structural designs will affect employees’ performance, the cost of operations, the delivery of services and the impact of service outcomes on citizens.

Improvements are simply not possible without quality, verified data, which has three main characteristics:

1. Accurate

Data accurately represent specific measures of objects, times, places and actions, and those measures can be verified as accurate and trustworthy. Descriptive information is not necessarily data and to rely on arbitrary descriptions without verifiable measures is to allow for operational ambiguity and misrepresentation of facts.

2. Consistent

Data are formatted consistently to ensure measures have the same meaning, regardless of management differences in operations or organizations. Standard data are essential to making data useful. Units of measures and rules for rounding numbers must be the same within and across all operations.

3. Controlled

The handling of the data is controlled to prevent human errors or adulteration. The basic requirement of information technology is to control the data so that it follows a consistent format and is reliably accurate. At a minimum, every data collection should be technically controlled to prevent errors, and once collected and verified, alterations should not be possible to suit arbitrary interests.

These characteristics align with both generally accepted principles of quality data and federally recognized core principles of open data.

The new administration can support agency innovation and accountability by facilitating data standard setting activities and governance processes, simplified and consistent executive reporting that relies on source level data instead of reporting writing exercises, and governmentwide coordination through OMB. We also point to specific and successful federal data standard setting work that OMB should leverage governmentwide to empower efficient and effective management.

We hope this paper will help equip today’s federal leadership with a defined framework for necessary and bold improvements. Our recommendations should also provide OMB with specific actions that they can take to support federal leaders in this reorganization work.

We come from different backgrounds, but share a commitment to see our federal leaders equipped to achieve their agency missions and provide valuable services to U.S. citizens.

Dr. David Paschane is the CEO and lead scientist of Aplin Labs.

Christian Hoehner is a policy director for the Data Coalition.

Dr. Kevin Kosar is the vice president of policy for R Street Institute.

Dr. Eric Hannel is a strategic consultant of Aplin Labs.