A transparent monitoring system should be developed collaboratively with the training providers. Employment and income verification should be conducted jointly by the project team and the training providers to reduce disagreements on the results. Familiarize the training providers with the entire verification process and explicitly articulate the terms in their contracts. Be careful not to make the systems overly complex or to set targets so high that training providers would be discouraged from participating.
Performance-based contracts can work for big and small projects even in fragile settings. The Liberia and Nepal AGIs show that, with appropriate planning and systems in place, performance-based contracts can be successfully implemented. These approaches worked in the relatively small program in Liberia (targeting 2,500 young women) as well as in the Nepal AGI, which was embedded in a larger program (the AGEI targeted 4,375 girls over three years in a national program that trains 15,000 youth annually).
The ethos of performance-based project management can be adopted at all implementation levels to improve project outcomes. AGI training provider contracts include payments tied to key deliverables to ensure strong oversight in contract administration throughout the project cycle. The Liberia monitoring system, for example, which generates monthly quality ratings, also stimulates healthy competition among the service providers. Trainees participate in performance-based stipend and savings schemes, as well as regular attendance and contests, and business plan competitions.
Results-based approaches can encourage training providers to assume greater responsibility for achieving employment outcomes. Most training providers are accustomed to delivering an output (such as a certain number of training hours) rather than an outcome (such as job placement). For example, the Liberia and Nepal pilots used innovative performance-based incentive schemes to encourage training providers to do their absolute best to help graduates find jobs or be successful in their businesses, as follows:
Both models seem to have worked well; most service providers were able to access the withheld payment/outcome payments. In Liberia, however, the points received after the verification process were lower than the placement rates reported by the service providers, signaling the need for good verification (see Verifying Employment). The positive results are validated by impact evaluations, showing large and economically significant impacts on employment and earnings.
Results-Based Contracting |
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Strategy | Resources and Tools |
Results-based contracting encourages training providers to be more proactive and to offer training for their participants only in trades where they expect to find jobs and helps to change the mindset toward delivering employment outcomes instead of ending at training delivery. |
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Incentive schemes should be monitored closely for unintended consequences and ensure that a focus on results does not promote exclusion of those who are more difficult to place. Projects should beware of potential risks and have mitigating measures in place.
Incentive Scheme Risks and Mitigating Measures | |
Risks | Mitigating Measures |
Training providers may collude with employers to overreport outcomes. | A robust and transparent verification process is required to minimize misreporting. In the AGI pilots, verification is based on a randomized, stratified sample of trainees (for example, 25 percent in Liberia, 30 percent in Nepal). Reported outcomes are verified among the random sample by talking with employers, nearby market women, and community members, and by accessing the trainee’s business records. The percentage of employed youth in the sample is extrapolated to the whole population claimed to be employed by the training provider and is used as a basis for the final outcome payment. Any inaccurate claims by the training providers proportionally reduce their payment and can jeopardize their eligibility to participate in future trainings. |
Training providers may discourage poor performers to drop out of the training so they can be replaced with better performers. | Monitoring systems should collect data at the individual level—not just at the classroom level—from start to finish of the project cycle. Data include individual-level data on recruitment, attendance during training, training completion, and posttraining activities. Individual-level monitoring data allow projects to identify dropouts and hold providers accountable for training and placing the same individuals who were originally recruited. |
Training providers could select beneficiaries who appear more “employable,” thereby neglecting more vulnerable girls. | For instance, the Nepal AGI deals with the risk of selecting only the most employable girls ("cream skimming") with a differential pricing mechanism that awards a higher incentive to providers who agree to train (and place) more disadvantaged groups, according to established vulnerability criteria. The highest incentive is awarded for training and placing the most disadvantaged; incentives are gradually lowered for less prioritized groups. The incentives must be defined carefully—too low and they will not be effective, and too high incentives could lead to exclusive targeting of the most disadvantaged group, which might result in low employment rates. In Nepal, the combination of a results-based system with a progressive incentive scheme ensures that training providers with the capacity to work with vulnerable groups will likely opt to do so. |
For more information on how the AGI pilots in Liberia and Nepal implemented results-based incentive schemes, see: AGI Learning from Practice Note on Results-Based Approaches to Improve Inclusion and Job Placement | World Bank | 2014.