One of the reasons why organisations prefer DIBs is that the service provider gets working capital upfront, and does not have to fundraise continuously. Often, projects are funded by a few donors, each with different conditions and demands, making implementation and reporting more challenging for the nonprofit. Because the upfront capital in a DIB is unrestricted (i.e. the service provider has autonomy over how it chooses to spend that money to achieve its outcomes), there is greater flexibility and less effort required to manage a diverse pool of funders. That said, the service provider does have to spend time and effort on managing the DIB, which is a complicated and resource-intensive process. A challenge with DIBs is their high reliance on data. Since the final payout is dependent on what the data shows, there’s little room for error with data collection and quality. This also makes the process more expensive. Sometimes data is collected not just from the intervention areas, but also from areas that were left untouched—a control group—so as to make a comparison and assess the impact of the DIB. On the flip side, because a DIB is closely evaluated at different stages, there is greater transparency about the project and its outcomes, and therefore, greater accountability. At times a conflict of interest might also arise, for instance, regarding who pays the project monitor. If the outcome payer bears this expense, it’s in their interest to evaluate conservatively. But if the working capital provider is paying, the aspiration would be that the results to show that targets were achieved. Moreover, there’s the probability that if the project appears unlikely to achieve its outcomes, efforts will be increased significantly to ensure that everybody wins. One could argue that this creates an ‘artificial’ environment that may be difficult to replicate in a non-DIB setting, calling into question the true scalability of such an exercise. A study by GO Lab suggests that though evaluations of impact bonds may determine if results were achieved, they fail to prove whether they were achieved because of the SIB approach, or whether the same results could have been achieved in a more conventional setting as well.