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Four challenges to building capacity in government

Madhav Seth 10 October 2019

Challenges and roadblocks to helping government leaders build new data and evidence skills

IDinsight’s Vinod Sharma facilitates a workshop on data use for health and nutrition officials in Ranchi, Jharkhand. ©IDinsight/Aditi Gupta

Organisations globally invest in capacity building to share valuable knowledge and skills that can be transformative — but often overlooked are the many challenges to doing it well. For those looking to strengthen decision-makers’ ability to use evidence, capacity building can seem like a logical next step after working with a partner to enhance their data use. IDinsight’s Capacity Building team in India has spent more than eight months working with government officials, supporting them to increase their use of data for decision-making. During these months we have encountered four fundamental challenges that have caused us to question the utility of capacity-building efforts. We experienced these challenges in the nutrition sector, but they will likely apply to other sectors as well.

Challenge 1: It is surprisingly difficult to know whose skills we should be developing.

The Indian government is a large and complex institution. It is sometimes so complex that it can be difficult to identify, without undertaking an extensive stakeholder mapping exercise, who is responsible for which activities. Even if you manage to identify the relevant department, it can be remarkably challenging to know who within that department you should concentrate your efforts on. If you focus too much on district and sub-district officials, you risk missing structural factors, like staffing and funding, that inhibit sustainable capacity building. In our work, we noticed that in focusing on the skills district officials needed to become better consumers of data, we had missed the fact that most of the relevant positions we were targeting had a 30–40 percent staff vacancy rate. Focus too much on higher level, state and national officials, and you risk losing out on helping staff on the ground build their skills and adapt them to address certain sensitivities. For example, we initially thought we should work on creating dashboards that would better inform national-level policymakers. However, through our field visits we realised that the more pressing need was to improve the training given to data collectors so that the quality of data being analysed was more usable. Capacity builders that have limited resources will often be forced to target just one or two steps in the government’s hierarchy. In turn, they will find that this choice imposes limits on the extent of social impact they can hope to achieve.

Challenge 2: It is surprisingly difficult to define a clear goal for capacity building.

Capacity building can either be in-depth (with a focus on establishing a deep understanding of Monitoring and Evaluation concepts) or light (with a focus on increasing awareness of the benefits of using data). In-depth capacity building efforts are necessarily limited in scope — not everyone wants or needs to be trained on the intricacies of, for example, impact evaluation. Lighter capacity-building efforts can reach a wide audience but may lack the depth to make a meaningful impact on the way officials think about problems. On our capacity building team, we decided to focus on light capacity building efforts, as we wanted to maximise the number of officials we could reach within the time we had. While it seems like our sessions have mostly been well-received, it remains to be seen whether they will have a long-term impact on the way government officials approach their job. For example, we received extremely positive feedback from a district’s nutrition department on our data use and data quality sessions. We felt good about our material too, having noticed high levels of engagement from most participants throughout the sessions. However, we do not know whether three months from now (let alone three years from now), the participants will remember what we covered in our session, or whether they will use it in their day-to-day work.

Challenge 3: There can be strong disincentives to collect quality data in the government. 

Using data to improve decision-making assumes that the data being used is accurate. However, this is not always the case. All of the officials we interviewed talked about the pressure they were under to meet targets every month. In most cases, these targets seemed unachievable. An official mentioned how he received directives from the state government to reduce stunting by 4 per cent per year in his district. He said that the rate of stunting had been reducing at 1.5–2 per cent per year for the last three years. In effect, he was being asked to double his results without any corresponding increase in resources. He was also tasked with measuring his own performance, i.e. — collecting the data on which he would be evaluated. He asked us what we thought he and his staff would do, given environment, when it was time to enter data for the district into the system. Another official we interviewed said that he was told to “do whatever he had to do” to meet his targets for each month. Government officials across departments are likely facing similar pressures, suggesting that significant amounts of data entered into administrative systems are potentially falsified. The likelihood that administrative data collected by the government can be false raises the question of whether we should be encouraging governments to use this data at all.

Challenge 4: There are significant systemic constraints to the regular use of data in the government.

The first constraint keeping government officials from regularly using data is infrastructure. Many government offices at the district and sub-district level simply do not have the infrastructure (computers, phones, internet, electricity) required to be able to integrate data use into their daily jobs. The second constraint is not having enough people. Many offices operate with a 30–60 per cent staff vacancy rate. If one person is doing the job of two people, incorporating data into decision-making, much less taking the time to learn how to do so, may not be seen as the most pressing need for the government department. Sustainable and relevant capacity building efforts must not only increase the quality of work government officials do but also reduce the amount of work these officials are expected to do.

There are no easy solutions and a number of partners are working to address these challenges. Resolving them relies on deep structural and political reform. Capacity building in some form will always be necessary, but serious thought must be given to its inherent challenges to ensure that efforts are as relevant and useful as possible.

This is the first in a series of blog posts about Capacity Building.