The biggest promise of technology in development is, perhaps, that it can provide us access to consistent, actionable and reliable data on investments and results. However, somewhat shockingly, we in development have not fully capitalized on this promise as compared to the private sector. Would you invest your precious pension hoping you will get something back but without having any reliable data on the rate of return or how risky your investment is? If you have two job applicants, one who is a methamphetamine addict and the other is one who has a solid work history and great references, would you give equal preference to both? If your answer to either is no, then take a look at the field of international development and consider the following:
- Surprising lack of consistent, reliable data on development effectiveness: Among the various sectoral interventions, we have no uniformly reliable data on the effectiveness of every dollar spent. For example of every dollar spent in infrastructure programs in sub-Saharan Africa, how many cents are effective? Based on the same assumptions, do we have a comparable number for South East Asia? In other words why don’t we have more data on possible development investments and the associated costs, benefits/returns and risks?
- Failure to look at development effectiveness evidence at the planning stage: Very few development programs look at the effectiveness evidence before the selection of a particular intervention. Say, a sectoral intervention A in a particular region has a history of positive outcomes (due to attributable factors such as well performing implementation agencies) as opposed to another intervention B where chances of improved outcomes are foggy. Given the same needs (roughly) why shouldn’t we route funds to A instead of B in the planning stage? Why should we give equal preference to both based purely on need?