Identifying the Underlying Problem in Policy Making

Every good policy begins with a question that sounds deceptively simple: what exactly are we trying to fix? Yet this is where many well-intentioned programmes stumble. Identifying the underlying problem is the first analytic step of the policy cycle, and getting it right determines whether public money builds lasting change or merely treats symptoms. This post walks through what problem identification really involves, why it demands conceptual thinking, and how the Ganga pollution challenge illustrates every stage of this analytical work.

Why problem identification is the foundation of good policy 🔗

A policy problem is not just any inconvenience. It is a situation that causes enough dissatisfaction for citizens or groups to call on the government to find a solution. Scholars sometimes refer to this first stage as issue recognition – the point at which a problem is first noticed and perceived to have potential for government action. From stray garbage collection to nuclear non-proliferation, almost everything a government does begins with someone saying, “this cannot continue.”

But recognition alone is not enough. For an issue to move from public chatter to the formal government agenda, decision makers must be aware of the underlying problem, agree that action is possible and necessary, and accept that the solution falls within the government’s responsibility. Each of those three conditions depends on having a clear, evidence-based understanding of what the problem actually is.

The cost of getting it wrong 🔗

When policymakers diagnose the wrong problem, even well-funded programmes produce disappointing outcomes. Budgets are spent, officials are appointed, infrastructure is built – and the original issue quietly persists. A useful framework from policy analysis distinguishes between several kinds of gaps that emerge from poor diagnosis: design gaps where the policy is built on incorrect assumptions, implementation gaps where sound policy fails in execution, coverage gaps where certain populations are excluded, outcome gaps where the policy does not produce intended results, and equity gaps where benefits and burdens are unevenly distributed. Recognising which gap you are actually dealing with is the first step toward meaningful reform.

From mundane description to conceptual analysis 🔗

The most important shift at this stage is moving from describing a situation to analysing it conceptually. A descriptive statement tells you what you see. A conceptual statement tells you what is going on underneath.

Consider a common complaint: “traffic in the city is terrible during peak hours.” That is a description. The conceptual version might read: road space is an under-priced common resource, individual drivers do not bear the full social cost of congestion, and public transport supply has not kept pace with demand. Each conceptual reframing suggests a very different intervention – congestion pricing, bus rapid transit, staggered office hours, or land-use changes. The descriptive version, by contrast, leads only to vague calls for “better traffic management.”

The same logic applies to every policy area. “Our schools are failing” is a symptom. The underlying problem might be teacher absenteeism, curriculum mismatch, malnutrition in learners, low parental engagement, or some combination of these. As one public administration text notes, identifying the root cause of a problem is often tricky, and policymakers often make decisions based on incomplete knowledge of the problem’s origins. Honest conceptual analysis forces this uncertainty into the open, where it can be addressed through research, data, and stakeholder input.

Questions that sharpen the diagnosis 🔗

Analysts use a small set of questions to push past surface descriptions:

Who is affected, and how severely? What are the observable trends over time? What mechanisms – economic, institutional, behavioural, or cultural – appear to drive the outcome? Why has the market, community, or existing government action failed to resolve it? What evidence supports each of these claims?

A problem that survives this interrogation is usually well enough defined to move into the next stage of the policy cycle.

Diagnosing market failures 🔗

One of the most useful conceptual lenses for problem identification is the theory of market failure – situations in which free markets fail to allocate resources in a way that maximises social welfare. Mainstream economics recognises several classic forms.

Externalities 🔗

An externality exists when an economic activity creates costs or benefits for third parties that are not reflected in market prices. Negative externalities, such as air or water pollution, typically lead to overproduction because private costs are lower than true social costs. Positive externalities, such as vaccination or basic education, lead to under-production because individuals cannot capture the full social benefit of their actions. Diagnosing whether an externality is positive or negative, and how large it is, directly shapes the instruments a government might choose – from Pigouvian taxes to subsidies and regulatory standards.

Public goods 🔗

Public goods are non-excludable and non-rivalrous, meaning no one can be prevented from benefiting and one person’s use does not reduce availability to others. Flood protection, national defence, street lighting, and clean air all fit this description. Because private firms have little incentive to provide public goods – everyone benefits whether they pay or not – markets systematically under-provide them, creating a classic free-rider problem. The policy question then becomes how government should step in to ensure supply.

Information asymmetry 🔗

When one party in a transaction has significantly more information than the other, markets can fail. Patients cannot easily evaluate a doctor’s competence, students cannot fully assess a coaching institute’s quality, and borrowers may not understand the terms of a loan. Each of these situations calls for different policy tools – disclosure rules, accreditation systems, consumer protection laws, or public provision.

Monopoly and concentrated market power 🔗

When a single firm or a small group dominates a market, prices rise, output shrinks, and innovation slows. Competition policy, price regulation, and antitrust enforcement are all responses to this form of market failure.

Applying market failure analysis to Ganga pollution 🔗

The Ganga is arguably the most instructive case study in problem identification available. It is a river that supplies water to roughly 40% of India’s population across 11 states and serves an estimated 500 million people. Its pollution has been on the national agenda for four decades, yet progress has been uneven. Why?

The descriptive statement is obvious: the river is dirty. The conceptual analysis reveals layered, overlapping market failures.

A cascade of externalities 🔗

Factories discharging effluents, farms flushing chemical run-off, and municipalities releasing untreated sewage all impose costs on downstream communities that do not enter any market price. These are textbook negative externalities. Roughly 12,000 million litres per day of sewage is generated in the Ganga basin, against installed treatment capacity of about 4,000 MLD, with around 3,000 MLD discharged directly into the main stem of the river against barely 1,000 MLD of treatment capacity created over the decades. The scale reveals how long these external costs have gone uncorrected.

Clean water as a public good 🔗

A clean river is largely non-excludable – you cannot easily fence off the benefits of clean water from any user in the basin. This creates the classic free-rider dynamic. States, cities, and industries all benefit from a cleaner Ganga, but each has limited incentive to bear the costs individually.

Information gaps 🔗

Many users of the river, including pilgrims and residents, may not have reliable information about the specific health risks from bathing in or consuming polluted water. Industrial compliance data has historically been patchy. The Central Pollution Control Board continues to identify industrial waste as a major pollutant, and analyses have noted that more than 450 industries have failed to meet pollution norms.

Coordination failure 🔗

The Ganga basin cuts across multiple states, each with its own priorities and fiscal capacity. No single authority historically had the mandate or resources to act coherently across the basin. Earlier efforts such as the Ganga Action Plan of 1985 built sewage treatment plants in class I and II cities but under-performed because of poor maintenance, inconsistent electricity, and weak coordination across states.

Each of these diagnoses points to a different kind of instrument. Externalities need regulation, pricing, or pollution taxes. Public goods need public investment. Information gaps need monitoring and disclosure. Coordination failures need basin-level institutions.

From problem to clear objectives 🔗

Once the underlying problem is properly diagnosed, the next analytic task is defining objectives. Good objectives are specific, measurable, achievable, relevant, and time-bound. They translate a conceptual diagnosis into something against which success can be judged.

The Namami Gange Programme, approved in June 2014 with a budget outlay of Rs. 20,000 crore, was built around the twin objectives of effective abatement of pollution and conservation and rejuvenation of the National River Ganga. Note how the objectives map directly onto the diagnostic framework. Pollution abatement targets the externality problem. Conservation and rejuvenation address the public-good dimension. The programme’s four pillars – Nirmal Ganga for pollution abatement, Aviral Ganga for ecology and flow, Jan Ganga for public participation, and Gyan Ganga for research and evidence-based policy – reflect an attempt to attack multiple market failures simultaneously.

Measurable targets matter 🔗

Clear objectives also create political accountability. Recent investment under the National Ganga Plan aims to enhance sewage treatment capacity, improve water quality, and regulate industrial waste discharge to achieve prescribed bathing standards by 2025. Whether these targets are met is a separate question – the point is that they exist and can be tracked. A policy with only a vague aspiration to “clean the river” would be impossible to evaluate or correct.

What careful problem identification makes possible 🔗

Good problem identification is not a bureaucratic ritual. It is the step that determines whether everything downstream in the policy cycle – formulation, implementation, evaluation – has a chance of succeeding. Resources are always limited. Public support depends on clearly articulated problems. Solutions depend on correct diagnosis, in exactly the way a treatment depends on an accurate medical diagnosis.

The Ganga case also shows why this stage must remain open to revision. New data, shifting climate patterns, and evolving urban demographics can change the nature of the underlying problem. The best policy analysts treat problem identification not as a one-time exercise but as a continuous conversation between evidence and action.

What do you think? When you look at a public problem in your own city – traffic, air quality, school performance, drinking water – can you separate the visible symptoms from the underlying market failures driving them? And how might clearer problem identification change the policies you would recommend?

References

1. https://open.maricopa.edu/pad100/chapter/45-understanding-and-identifying-problems-public-policy-textbook/
2. https://link.springer.com/chapter/10.1007/978-3-319-72368-6_10
3. https://govcentre.org/diagnosing-the-gaps-identifying-and-solving-policy-problems/
4. https://en.wikipedia.org/wiki/Market_failure
5. https://pressbooks.cuny.edu/berch/chapter/__unknown__-5/
6. https://en.wikipedia.org/wiki/Pollution_of_the_Ganges
7. https://anantamias.com/ganga-pollution/
8. https://www.impriindia.com/insights/namami-gange-programme-ngp/
9. https://nmcg.nic.in/NamamiGanga.aspx
10. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2109078