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The Government Performance Logic Model

The Institute has defined and refined a proven methodology for measuring government performance: The Logic Model. This prospectus (in PDF format) provides an overview of how the Logic Model works and how it can benefit your agency’s efforts to define, plan for, manage, and measure program performance.

Applying the Logic Model to Your Agency's Challenges

While the Logic Model has been used to devise implementation strategies and performance measures for myriad government management challenges, four applications of the Logic Model have been the most popular. Each Logic Model session begins with comprehensive training for program participants in the fundamentals of performance measurement. Then, specific application training is provided to bridge performance measurement with the management challenge being addressed by program participants.

Performance-Based Budgeting
The PBB Logic Model session provides a concrete approach to linking resources to results through performance budgeting. This session begins with a review of federal (or state/local) guidance for performance budgeting, as well as examples from several programs. Then, participants work through the logic model defining outcomes, intermediate outcomes for program strategies, and program outputs. In some sessions, managers are asked to select work processes to which they “cost” their activities using an approach similar to Activity-Based Costing. The result is the alignment of performance and costs of a program in a formal budget justification. Typical PBB Deliverables:
• Program Performance Measurements
• Performance Justification for the Budget
• Self Assessment Score from OMB’s Program Assessment Rating Tool - PART
• Activity-Based Costing Work Processes for Program Cost Alignment to Results

Performance-Based Consulting
During this session, the PBC Logic Model is used to link contracting and acquisition functions to program results. This session begins with training on the “7 Steps for Creating Performance-Based Contracts” developed by a consortium of federal agencies. Then participants are asked to either work on their own contracts or use a case study contract to develop a performance-based Statement of Work or Statement of Objective. Participants are also assisted in selecting what performance measures to use in the solicitation and the contract vehicle and how to structure contract incentives. Typical PBC Deliverables:
• Statement of Work
• Statement of Objective
• Performance Measurements Linking Contract to Program Results
• Worksheet Applying Incentives to Contract Vehicle

Human Resources Management
Workforce assessments, human capital plans, recruitment and retention, and employee evaluation initiatives all depend on aligning workforce capacities to mission results. The HRM Logic Model session address all four of these aspects of effective human resource management in government. Participants evaluate strategies and goals of programs to determine necessary skill sets and workforce competencies. Measures for recruitment and retention are applied to implement the human capital plan. In some sessions, participants create actual employee performance contracts.

Typical HRM Deliverables:
• HR Performance Measures
• SES/Executive Performance Plans
• Employee Performance Evaluation Plans
• Human Capital Plans
• Data Blueprint for Workforce Analysis


Information Technology/e-Government
Information technology is an important, but expensive tool used to deliver mission results. The IT/e-Gov Logic Model session begins with training on an IT Capital Planning and Measurement framework developed through agency surveys, GAO, OMB and CIO Council efforts. Then the session turns to a specific IT investment initiative or contract for the development of performance measures aligned to program results. In some sessions, participants work through an actual OMB Exhibit 300 or performance-based IT contract model. Typical IT/e-Gov Deliverables:
• e-Gov Performance Measures
• IT Performance Standards
• IT Capital Plan
• Budget/OMB Exhibit 300 Justification

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