Methods of Problem-Solving

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πŸ“˜ 8.5 Methods of Problem-Solving


πŸ” 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.


🧠 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: KΓΆhler’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 prepβ€”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.

🚫 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

πŸ“‹ 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)

✍️ 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.

🧠 Summary Snapshot

PROBLEM-SOLVING METHODS
β”œβ”€β”€ Trial & Error
β”œβ”€β”€ Algorithm
β”œβ”€β”€ Heuristic
β”œβ”€β”€ Insight
β”œβ”€β”€ Analogical Thinking
β”œβ”€β”€ Means-End Analysis
β”œβ”€β”€ Brainstorming
└── Incubation

 

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