Apply the Hundred-Rupee Test to Simplify Government Services

Many government processes impose an administrative burden disproportionate to the value or risk of the decision involved.

A relatively simple citizen request may require multiple forms, documents, physical visits, verifications and layers of approval. In some cases, the combined cost of citizens’ time and government administration may be greater than the value of the service or transaction itself.

The problem is not simply a lack of digitisation. Digitising an unnecessarily complicated procedure does not make it a good procedure.

Many traditional processes have simply moved from paper to online portals without asking whether all the documents, approvals and verifications are still necessary.

This creates three costs simultaneously:

Citizens lose time → Officials spend time on routine transactions → Government carries unnecessary administrative cost

The deeper problem is an administrative model that often assumes verification before trust, approval before action and process compliance before outcomes.

Every high-volume government service should therefore face a simple test:

Does the time, paperwork and administrative cost required to deliver the service make sense relative to its value and risk?

If not, the process should be redesigned.

The ₹100 in the Hundred-Rupee Test is therefore not intended as a literal financial threshold. It represents a principle: the administrative burden imposed by government should be proportionate to the value and risk of the decision being made.

India should systematically review high-volume citizen-facing government processes using a Hundred-Rupee Test, supported by digital infrastructure, data and AI where appropriate.

Each process should be measured for:

Administrative Cost → Documents Required → Number of Approvals → Citizen Visits → Processing Time → Risk

Low-risk processes with disproportionate administrative burdens should then be redesigned.

Trust First, Verify Based on Risk

Government should move away from manually scrutinizing every routine transaction.

Low-risk cases should increasingly be processed automatically or with minimal intervention, while higher-risk or unusual cases receive greater scrutiny.

The World Bank has documented the broader principle of risk-based regulation, in which government directs regulatory resources according to actual risk rather than applying the same level of control to every case.

AI and data analytics can assist by identifying unusual patterns or inconsistencies for human review.

The principle should be:

Routine Case → Fast Processing

Unusual or High-Risk Case → Additional Verification

Ask Citizens for Information Only Once

If reliable information already exists in an authorized government database, another department should not repeatedly require citizens to submit the same information.

Subject to privacy, security and legal safeguards, government systems should retrieve verified information from authoritative sources rather than making citizens repeatedly prove facts the government already knows.

The principle should be:

Tell Government Once → Government Reuses Verified Information

Move Decisions Closer to the Frontline

Routine matters should not travel through several administrative levels merely because that is how the process has historically operated.

Frontline officials should receive clearly defined authority to approve routine matters within established limits.

Digital audit trails, random audits and risk-based review can provide accountability after decisions are made.

Delegation should reduce unnecessary approvals without reducing accountability.

Move From Applications to Automatic Entitlements

Where government already possesses sufficient verified information to determine eligibility, citizens should not always have to discover a scheme, understand its requirements, complete an application and submit information government already possesses.

Services should progressively become entitlement-based and proactive where appropriate.

If the government already knows that someone qualifies for a service, the system should be capable of informing the person—or, where legally and operationally appropriate, initiating delivery—rather than waiting for the citizen to navigate the bureaucracy.

Let Citizens Describe What They Need

Citizens should not need to understand the structure of government in order to receive a government service.

Conversational digital systems can increasingly allow someone to explain a problem in an Indian language through text or voice.

The system could then identify the appropriate service, retrieve authorized verified information, ask only for missing information and route the request appropriately.

The burden of understanding government machinery should increasingly shift from the citizen to the system.

Use AI to Assist, Not Automatically Decide Everything

AI can help translate languages, interpret requests, identify missing information, route cases, detect anomalies and assist officials.

But consequential decisions affecting rights, benefits, penalties or eligibility should retain appropriate human review and appeal mechanisms.

AI should therefore be used primarily to remove administrative work and direct human attention where judgment is actually required.

Start With 10–20 Services and Measure the Results

The reform should begin with a pilot involving 10–20 high-volume, relatively low-risk government services.

Before redesign, government should measure:

Cost per Transaction → Processing Time → Documents → Approvals → Citizen Visits → Error/Fraud Rate

The process should then be simplified and the same measures collected afterward.

Successful reforms can subsequently be expanded across departments and states.

The proposal works because it does not require government to build an entirely new administrative architecture. It changes the way existing digital capabilities are used.

Government already possesses large amounts of verified data, digital records, electronic workflows and transaction histories. These capabilities can increasingly be used to simplify routine processes rather than merely digitise existing bureaucracy.

AI adds another layer of opportunity. It can help interpret citizen requests, retrieve available information, identify missing information, translate languages, detect unusual patterns and direct human attention towards cases that genuinely require scrutiny or judgement.

This can also make government services more accessible. Voice interfaces, translation, conversational systems and assisted reading can allow people to interact with digital services without needing high levels of formal literacy, English proficiency or familiarity with bureaucratic terminology.

A citizen should increasingly be able to explain a need in their own language, through voice or text, while the system identifies the appropriate service and administrative process.

The burden of understanding government machinery should gradually shift from the citizen to the system.

The Hundred-Rupee Test also creates a measurable discipline for administrative reform. Instead of asking whether a department has digitised a service, government can ask:

Have approvals reduced? → Have citizen visits reduced? → Has processing time fallen? → Has administrative cost declined? → Has access improved?

This shifts the measure of success from technology adoption to actual outcomes.

The approach can also give frontline officials greater authority without eliminating accountability. Routine decisions can be delegated within clearly defined limits, while digital audit trails and risk-based scrutiny can identify unusual cases for subsequent review.

The underlying administrative shift is:

Permission → Empowerment
Repeated Verification → Trusted Data
Universal Scrutiny → Exception-Based Scrutiny
Application → Anticipation
Literacy Barriers → Conversational Access
Process Compliance → Measurable Outcomes

Estonia: A Real-World Example

Estonia demonstrates several of these principles in practice.

Its digital-government model follows a “once-only” principle: citizens should not have to repeatedly provide information that government already possesses. Authorized public systems can securely reuse verified information rather than requiring citizens to submit the same documents to different agencies.

Estonia’s X-Road infrastructure enables government databases to exchange information securely. Estonia has also developed proactive government services, where services can be initiated based on information government already holds rather than requiring citizens to discover and apply for every service themselves.

The European Commission reported that Estonia’s X-Road system was estimated to save the equivalent of 2,589 years of working time on citizen service requests in 2024.

The broader lesson for India is not to copy Estonia’s technology or administrative structure. It is to apply the same underlying discipline to India’s own digital infrastructure:

Do not merely digitise an existing procedure. Ask whether every step of that procedure is necessary in the first place.

Success should therefore be measured through:

Fewer Documents → Fewer Approvals → Fewer Visits → Faster Decisions → Lower Administrative Cost → Better Citizen Experience

Technology—including AI—should support that objective rather than become the objective itself.

The Hundred-Rupee Test ultimately asks government a very simple question:

If administering a routine decision costs government and the citizen more than the value or risk involved, why are we still administering it that way?

That is the question that can turn digital government into simpler government.