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India’s march towards a $5 trillion economy hinges on infrastructure. A bulk of the discussions on it are centred around two big questions: (a) Is India investing adequately in infrastructure?; and (b) are our investments yielding completed projects on time? The first question has been debated for years and is unlikely to yield conclusive answers, given the dynamic relationship between economic growth and demand for infrastructure. The second must be accorded high priority in an economy striving to make efficient use of the available capital. The timely completion of infra projects requires regular monitoring and time-to-time course corrections. Such monitoring is a regular process that systematically collects data on specified indicators of the extent of progress. This is a demanding task that has been rather neglected in the past, as traditional ‘implementation monitoring’ is primarily concerned with activities, inputs and immediate outputs.
While there exist multiple sources of data on the progress of projects within the government, timely availability of high-quality data from a dedicated credible source will reduce the need for additional agencies for data collection. It will also provide greater depth, as such agencies would be able to collect information on a regular basis, while evaluators typically only collect data at set points.
A concerted effort towards generating quality data on the state of infra projects should encompass three attributes. First, there is dire need for accuracy, in terms of how well the data describes the real state of progress. Inaccurate data creates problems, as it leads to incorrect conclusions and stalls the announcement of new projects. Second, there should be completeness in the data collected; that is, everything that is supposed to be collected should be available. If data is incomplete, it does not yield usable insights, often leading to time and cost over-runs. Hence, it is important to set goals for data collection in the right format. Third, a much needed attribute is timeliness; that is, the reported data must not be outdated. Data becomes less useful and less accurate as time goes on. Stale data can lead to actions taken that do not reflect the current reality.
The importance of timely data on project status rises if one considers the multiplicity of implementing agencies. Broadly, we could classify big infra projects as implemented by the Centre, states, both combined and private agencies, with varying levels of accountability for completion, across sectors. Given this milieu, improved data quality would lead to better decision-making across governments, decrease risk and help improve India’s record of timely completion. However, collecting high-quality data can be a challenge, as the agencies involved require better coordination and integration of data systems across various departments or ministries. It may also require proper tools or processes put in place.
Given that much of the monitoring takes place at Centre’s level and the bulk of data generation takes place in states, there exists a need for a concerted effort to coordinate data collection and reporting and improve data quality. This requires a data collection plan to determine the kind of data we need. Any such plan should also define the roles of all personnel involved in collecting the data; it must also establish clear processes for how they communicate between departments on data-related matters so that confusion does not arise. Setting data quality standards should also be an integral part of the data collection plan. This requires clarity on what data to keep, what to get rid of, and what to correct for the sake of consistency across ministries and departments. As data on project progress and budgets undergoes revisions, a set of guidelines for data correction should be evolved; we need conventions and uniform practices for data correction. These must define who is responsible for correcting and refining data and the methods they should use to fix it.
A robust data system would ensure that targets of the National Infrastructure Pipeline are achieved. The challenge lies in data integration and distribution across various tiers of governments, ministries and departments, as data quality issues may emerge in this process, especially if software platforms differ. It is equally important for states to report data on time. The opportunity cost of capital for projects vulnerable to time and cost over-runs must be emphasized to nudge states on that score. We also need reliable reports on the factors hampering the progress of big projects. An inventory of these factors would help decision makers to delineate patterns and account for these right from the project planning stage.
The ease of living and doing business depends critically on infrastructure available in our economy. Given the gestation periods of mega projects, timely monitoring and progress rectifications are imperative. Private entities have their own mechanisms to ensure timely project completion, the good practices of which could be adopted by the government. Considering the extent of debt financing in infra projects and cost inflation, the direct costs of project delays mount over time, and if we account for indirect costs too, then the accumulated depletion of economic benefits is unpardonably steep. Monitoring is an attempt to plug these leakages and all stakeholders will need to work in tandem for its success. A prerequisite for successful monitoring is timely availability of data. But data is only useful if it is of high quality. Bad data is inconsequential at best when we monitor large infrastructure projects, a fact that our generators of data must appreciate.
These are the author’s personal views.
M. Suresh Babu is advisor to the Prime Minister’s Economic Advisory Council and professor of economics at IIT Madras
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