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The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.
By Amy Johnson
November 13, 2015
A September 2005 Government Accountability Office (GAO) report, “Managing for Results: Enhancing Agency Use of Performance Information for Management Decision Making,” highlights practices that “can enhance or facilitate greater use of performance information.” A second GAO report produced in September 2014 validates the importance of these practices in creating a culture that supports the use of data in decision-making. While these reports may not be new, the practices are still relevant. What are these practices and who has responsibility for their development, implementation and maintenance within an organization?
Practice 1: Aligning Agencywide Goals, Objectives and Measures
Individuals with programmatic expertise play a critical role in helping define what to measure and optimal levels of performance. They own the systems of inputs, activities, outputs and outcomes that serve as the foundation for identifying relevant performance measures and understanding the relationships among them and the alignment to the organization’s mission and goals. Some organizations find it helpful to enlist the assistance of a strategy consultant in the stand-up of an initial measurement framework. The strategy consultant can guide program experts in a review of all of the data associated with the systems that surround the activities these experts own. Together, the expert and the strategy consultant identify which data are truly meaningful and provide value for decision-making and which data is really just “exhaust.”
Practice 2: Improving the Usefulness of Performance Information
Individuals who engage in activities that create data need to be careful in their delivery to ensure data accurately reflects actions and status. They have responsibility for helping to ensure “good” data.
Those with responsibility for collecting data need to define and document repeatable processes to ensure data come from the same place, through the same methods and then processed in the same way every time. Expertise in information technology can be leveraged at this point to automate data collection where possible. Automation allows for standardization of processes, which reduces the likelihood of variability in methods and techniques used in the collection phase. This is important because when variability is introduced managers lose the ability to compare data. Variability in data collection methods makes it difficult to determine if changes are the result of a legitimate change in performance or the unintended consequence of a change in the method.
Practice 3: Developing Agency Capacity to Use Performance Information
Managers need to be supported as they learn what is important to ask of the data and which data to focus on based on what it really measures. They need to be able to put that data into the right context to understand what it means about performance. Managers need access to tools as well as training to build skills to effectively use data.
Practice 4: Demonstrating Management Commitment
Top leadership review and use of performance information establishes the expectation for data-driven decision-making. Leadership needs to consider data when making decisions and make a practice of doing this with a high degree of visibility. In doing so, they underscore the value they place on the use of data and the need for everyone to do their part to ensure it is reliable. When leaders fail to consider data, they undermine efforts to establish performance management practices as part of the operational tempo and culture.
Practice 5: Communicating Performance Information Frequently and Effectively
If the use of data as a regular input to decision-making and management strategy is to take hold with depth and breadth within an organization, it must become part of the ongoing dialogue. Managers at all levels within the organization need to schedule regular reviews with staff or teams to look at data and discuss implications for organizational, operational and/or program performance. As evidenced by the “STAT” movement, government organizations and teams at all levels—federal, state and local—have increasingly made regular and frequent meetings with relevant stakeholders for the purposes of data-driven reviews and problem-solving. This is a good start. However, requests for “the data” should also become the standard in informal conversations that result in decisions and recommendations as well.
Sound performance management as part of standard organizational operations does not just happen. It takes the combined discipline, thought and effort of a variety of stakeholders across an organization to create a rhythm for collecting and using performance information as part of regular business operations. It takes a village.
Author: Amy Johnson has almost 20 years of experience working with public and private sector clients in the areas of program and process evaluation, strategic planning and organizational performance management. She serves as the director for Nonprofit and Civilian Government Programs at Coverent, a consulting firm focused on helping clients to use data analytics to measure program performance and maximize mission impact. Contact at [email protected]