Identifying Public Policy Problems: From Description to Diagnosis

Every government initiative, from cleaning a river to reducing road accidents, begins with one deceptively simple question: what is the actual problem we are trying to solve? The answer is rarely as obvious as it seems. A polluted river is not just dirty water; a struggling school is not just about unqualified teachers. The first stage of the policy process asks policymakers to look past the visible symptoms and ask why a problem persists, who is affected, and what forces keep it alive. This shift, from description to diagnosis, shapes every decision that follows.

Why the first step matters more than we think 🔗

Policy-making is a continuous cycle, but it has a clear starting point: the recognition that something in society needs fixing. According to the standard framework taught in public administration, the stages of the policy process begin with identifying the underlying problem, followed by determining alternatives, forecasting outcomes, selecting a policy, implementing it, and finally monitoring and evaluating results. Each stage depends on the one before it. If the problem is misdiagnosed at the start, every subsequent step, no matter how efficient, will address the wrong issue.

Think of it like medicine. A doctor who prescribes painkillers without understanding what causes the pain may offer temporary relief, but the patient remains sick. Public policy works the same way. Governments have limited resources, and every rupee spent on a poorly understood problem is a rupee diverted from a better-targeted intervention.

The cost of getting it wrong 🔗

India offers several cautionary examples of what happens when problem identification goes astray. The National Rural Health Mission was launched with great fanfare to improve rural healthcare, yet later evaluations revealed that false narratives and selective dissemination of data obscured deep structural issues such as inadequate infrastructure and workforce shortages. The programme treated visible symptoms instead of confronting the harder questions about why rural health systems were failing in the first place.

From description to diagnosis 🔗

The heart of this stage is a shift in how policymakers talk about a problem. A descriptive statement simply reports what is happening: “traffic in Delhi is terrible during peak hours” or “the Ganga is polluted.” A diagnostic statement, on the other hand, asks deeper conceptual questions: why does the problem persist despite existing regulations? What incentives push people toward harmful behaviour? What systemic gaps allow the issue to recur?

This analytical leap is what separates ordinary complaint from useful policy thinking. The same traffic congestion problem can be framed as a road capacity issue, a pricing failure where drivers don’t pay for the congestion they cause, a public transport deficiency, or a land-use problem caused by poor city planning. Each framing points toward a completely different policy intervention, from widening roads to introducing congestion pricing to expanding metro networks.

Moving beyond symptoms 🔗

A policymaker trained to diagnose rather than describe will ask a different set of questions. Instead of asking, “how much waste is being dumped in the river?” they will ask, “why do industries and municipalities continue to dump waste despite decades of regulation?” This opens up the real causes, things like weak enforcement, fragmented authority across ministries and states, low treatment capacity, or misaligned incentives for local governments.

Market failure as a diagnostic lens 🔗

One of the most widely used conceptual tools for diagnosing policy problems is the idea of market failure. This framework asks a simple question: is the free market, on its own, able to deliver the outcome society wants? When the answer is no, the government has an economic rationale to step in.

Economists generally identify four main types of market failure that justify public policy intervention. According to Weimer and Vining, market failures occur due to four reasons: public goods, externalities, natural monopolies, and information asymmetry. Each of these has very different implications for how a policy should be designed.

Externalities 🔗

An externality exists when an economic activity imposes costs or benefits on people who are not part of the original transaction. A factory that dumps effluent into a river lowers its own production costs, but the health and livelihood costs fall on the communities downstream. These costs are never reflected in the price of whatever the factory sells. Negative externalities, such as pollution, result in overproduction and harm to society, while positive externalities, such as education, lead to underproduction and lost social welfare. Diagnosing a problem as an externality points toward solutions like pollution taxes, tradable permits, or direct regulatory standards.

Public goods 🔗

Public goods are things that benefit everyone and cannot easily exclude non-payers, such as street lighting, flood control, or national defence. Markets typically underprovide them because no one can profitably charge for their use. Clean air along a riverbank is a public good in this sense, which is why private firms have no incentive to produce it on their own.

Information asymmetry 🔗

When one side of a transaction knows far more than the other, markets distort. Patients cannot always judge whether a hospital is overprescribing, students cannot always tell whether a coaching institute is genuinely good, and savers cannot always evaluate a complex financial product. Diagnosing a problem as one of information failure leads to very different policies, such as disclosure rules, licensing, or rating systems.

Monopoly power 🔗

When a single firm or a small group controls a market, prices rise and output falls below socially optimal levels. Policies here involve competition law, price regulation, or, in some cases, state ownership.

The Ganga: a diagnostic walk-through 🔗

The pollution of the Ganga is one of the clearest examples of why careful problem identification matters. At first glance, the problem is simple: the river is dirty. But diagnosing the underlying issues reveals a far more complex picture.

The sources of pollution are diverse. Every day, the main channel of the Ganga generates about 2,953 million litres of sewage, and the major pollutants include sewage, industrial waste, solid waste, agricultural run-off, open defecation, and partially cremated bodies. Each of these sources corresponds to a different form of market failure and therefore requires a different policy instrument.

Industrial effluent from tanneries, paper mills, and textile units is a textbook negative externality. Factories gain from cheap disposal while health and ecological costs fall on communities along the river. Solutions proposed over the years have included demolishing upstream dams to increase dry-season flow, constructing new reservoirs to provide dilution water, and investing in substantial new infrastructure to treat sewage and industrial waste throughout the catchment area. Domestic sewage, by contrast, reflects both a public goods failure and an infrastructure gap. Over 75 percent of the sewage generated in towns and cities along the Ganga flows untreated into the river. Ritual and cultural practices add yet another layer, one that cannot be addressed through taxes or regulation alone and requires community engagement.

Why earlier programmes struggled 🔗

Before the current flagship initiative, earlier efforts such as the Ganga Action Plan and the National River Conservation Plan focused narrowly on specific towns and end-of-pipe treatment. The Namami Gange Programme, approved in June 2014 with a budget of ₹20,000 crore, was designed around the twin objectives of effectively abating pollution and conserving and rejuvenating the national river. The shift from a town-centric approach to a basin-wide framework reflected a better diagnosis of the problem: pollution in the Ganga is not a local issue but a systemic one that flows across states, sectors, and jurisdictions.

Yet the diagnosis is still evolving. The Central Pollution Control Board identifies industrial waste as a major pollutant still, and PRS Legislative Research has noted that more than 450 industries have failed to meet pollution norms. This tells policymakers that even with a better framework, enforcement gaps and compliance failures need to be treated as separate problems with their own solutions.

Setting clear objectives 🔗

Once a problem has been diagnosed, the next task is to set clear objectives. Vague goals like “clean the river” or “reduce poverty” cannot guide implementation or be meaningfully evaluated. Objectives need to be specific, measurable, and linked directly to the diagnosis.

For the Ganga, this meant breaking the larger goal into concrete targets: improving water quality to bathing standards, reducing industrial effluent discharge, expanding sewage treatment capacity, and protecting biodiversity. Investment under the current phase aims to enhance sewage treatment capacity, improve water quality, and regulate industrial waste discharge. Each objective corresponds to a particular form of market failure and a particular policy instrument.

What makes objectives workable 🔗

Good policy objectives share a few features. They are measurable, so that progress can be tracked. They are time-bound, so that accountability is possible. They address root causes rather than symptoms. And they are realistic given the available resources and political environment. When any of these elements is missing, implementation tends to drift, and evaluation becomes a matter of opinion rather than evidence.

Common pitfalls in problem identification 🔗

Even experienced policymakers fall into predictable traps at this stage. One of the most common is solution-first thinking, where a favoured technology, scheme, or ideology is chosen before the problem is fully understood, and the problem is then defined to fit the preferred solution. Another is political framing, where sensitive causes are quietly left out of the diagnosis because naming them is inconvenient.

A third pitfall is the disciplinary lens. An economist may see Ganga pollution as a market failure, a public health specialist may see it as a disease burden, and a cultural scholar may see it as a question of ritual practice. All three framings contain truth, and none of them is complete on its own. Good problem identification requires drawing on multiple perspectives rather than collapsing a complex issue into a single frame.

Finally, there is the problem of structural fragmentation in Indian policy-making itself. One of the main problems with policy-making in India is extreme fragmentation in the structure, which fails to recognise that actions taken in one sector have serious implications on another and may work at cross purposes with the policies of other sectors. When different ministries define the same problem differently, even a good diagnosis at one level can be lost in the gaps between departments.

From diagnosis to design 🔗

The payoff from careful problem identification is that it sharpens every subsequent stage of the policy cycle. When the problem is well diagnosed, policy alternatives can be compared on their merits. Forecasting becomes grounded in a real theory of change. Implementation agencies know what success looks like. And evaluation has a clear benchmark against which to measure progress.

In a country as large and diverse as India, where policy problems cut across states, sectors, and communities, this first step is often the hardest. But the time spent in diagnosis is never wasted. It is the foundation on which every effective public policy is built.

What do you think? When you look at a current public issue, say, urban air pollution, traffic congestion, or the quality of government schools, what market failures do you see at work? And do you think Indian policymakers spend enough time diagnosing problems before reaching for solutions?

References

1. https://www.egyankosh.ac.in/bitstream/123456789/76653/1/Unit-3.pdf
2. https://www.ispp.org.in/five-key-reasons-for-public-policy-failures-in-india/
3. https://open.maricopa.edu/pad100/chapter/30-market-failures-public-policy-textbook/
4. https://maseconomics.com/market-failure-and-externalities-understanding-inefficiencies-in-markets/
5. https://www.impriindia.com/insights/namami-gange-programme-ngp/
6. https://en.wikipedia.org/wiki/Pollution_of_the_Ganges
7. https://www.ifc.org/en/stories/2023/breathing-life-back-into-the-ganga
8. https://nmcg.nic.in/NamamiGanga.aspx
9. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2109078
10. https://iasscore.in/topical-analysis/issue-in-policies-and-programes