Methods of Problem-Solving

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๐Ÿ“˜ 8.5 Methods of Problem-Solving


๐Ÿ” What is a Problem-Solving Method?

A problem-solving method is a structured or unstructured cognitive strategy employed by individuals to overcome obstacles and reach desired goals. Different situations call for different approaches.


๐Ÿง  Common Methods of Problem Solving


1. Trial and Error

  • Definition: Trying different solutions until one works.
  • Use Case: Works best in simple or novel situations with few consequences.
  • Example: A technician trying different wire configurations to fix a circuit.
  • UPSC Governance Analogy: An IAS probationer experimenting with various public grievance redressal platforms until one is most effective in a district.

2. Algorithm

  • Definition: A step-by-step procedure guaranteed to produce the correct solution.
  • Use Case: Suitable for well-defined problems (like mathematical ones).
  • Example: Calculating a tax refund using an official formula.
  • UPSC Application: Use of standard operating procedures (SOPs) for disaster response or legal procedures for land acquisition.

3. Heuristics

  • Definition: Mental shortcuts or “rules of thumb” to simplify decision-making.
  • Use Case: Useful in complex or time-sensitive situations.
  • Types:
    • Means-End Analysis: Break the problem into smaller goals.
    • Availability Heuristic: Judge based on easily recalled instances.
    • Representativeness Heuristic: Judge based on similarity to a known category.
  • Example: A collector prioritizing schemes that showed the highest return elsewhere (availability).
  • Governance Example: Selecting successful model villages from other districts to replicate.

4. Insight

  • Definition: Sudden realization of a solution without a step-by-step approach (“Aha! moment”).
  • Use Case: Often occurs after a period of incubation.
  • Example: A bureaucrat solving a corruption bottleneck by eliminating paper-based work.
  • Famous Experiment: Kรถhlerโ€™s chimpanzees using sticks to get bananas.

5. Analogical Thinking

  • Definition: Solving a problem by finding a similar structure in a different domain.
  • Use Case: Promotes innovation.
  • Example: Using the military chain of command to design an efficient disaster response network.
  • Indian Example: Aadhaar-based DBT modeled after banking transaction structures.

6. Means-End Analysis

  • Definition: Reducing the difference between current and desired state step by step.
  • Use Case: Effective in complex planning tasks.
  • Example: Planning UPSC prepโ€”Identify final goal, break into GS, Optional, Essay, then further modules.

7. Brainstorming

  • Definition: Generating multiple ideas without judgment.
  • Use Case: Creative group problem solving.
  • Example: Policy brainstorming sessions for rural health in NITI Aayog.
  • Psychological Basis: Encourages divergent thinking.

8. Incubation

  • Definition: Temporarily setting the problem aside, allowing the subconscious to work.
  • Use Case: Useful when stuck or under pressure.
  • Example: A writer stuck on a story idea finds the plot after a walk.
  • Governance Analogy: Reframing old policy challenges with a fresh mindset after a break or consultation.

๐Ÿšซ Comparing Methods: When They Go Wrong

Method Strength Risk if misapplied
Trial & Error Quick in low-risk tasks Wastes time/resources in high-stakes cases
Algorithm Accurate, replicable Time-consuming, rigid
Heuristic Fast decision-making Bias-prone (e.g., stereotyping)
Insight Innovative Not always reliable or replicable

๐Ÿ“‹ Application in Governance

Scenario Method Applied
Rural electrification Algorithm (step-by-step implementation)
Tackling fake news Heuristics + Brainstorming
Mission Karmayogi implementation Means-End Analysis
COVID-19 vaccine logistics Algorithm + Analogical Mapping (postal delivery models)

โœ๏ธ UPSC Answer Strategy (10 or 15 markers)

  • Define problem-solving and the idea of multiple methods.
  • Use headings for each method with brief explanation + example.
  • Add public administration/UPSC examples wherever possible.
  • Highlight flexibility in choosing method based on situation.
  • Conclude with the importance of training administrators in cognitive flexibility.

๐Ÿง  Summary Snapshot

PROBLEM-SOLVING METHODS
โ”œโ”€โ”€ Trial & Error
โ”œโ”€โ”€ Algorithm
โ”œโ”€โ”€ Heuristic
โ”œโ”€โ”€ Insight
โ”œโ”€โ”€ Analogical Thinking
โ”œโ”€โ”€ Means-End Analysis
โ”œโ”€โ”€ Brainstorming
โ””โ”€โ”€ Incubation

 

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