Planning & Decision-Making: Models, Techniques & Real-World Applications

TAKEAWAYS:

• Planning is a cyclical process (not linear) that aligns goals with resources, from corporate strategy (e.g., NTC’s fiber expansion) to daily operations (e.g., Pathao’s driver dispatch).
• Decision-making ranges from rational models (theoretical) to bounded rationality (real-world), where managers like Daraz’s supply chain team use heuristics due to time/uncertainty constraints.
• SWOT/PESTEL are diagnostic tools: Nabil Bank uses SWOT to assess its loan portfolio risks, while Daraz applies PESTEL to navigate Nepal’s trade policy shifts.
• Decision trees quantify risks (e.g., Kathmandu’s traffic light timing optimization) but require probabilistic data—often estimated from historical patterns.
• Contingency planning (e.g., NEPSE’s circuit-breaker rules) turns uncertainty into a structured advantage by pre-defining responses to crises.

1. What is Planning? The Foundation of Organizational Success

Planning is the proactive process of defining goals, forecasting challenges, and allocating resources to achieve them. It bridges the gap between where we are and where we want to be—critical for businesses like Nabil Bank (planning loan disbursement targets) or Daraz (inventory forecasting for monsoon seasons).

Types of Planning

Planning is categorized by scope, timeframe, and level in the organization:

Why it matters:

• Nabil Bank uses strategic planning to decide which sectors (e.g., agriculture, SMEs) to prioritize for loans, reducing default risks.
• Daraz employs operational planning to adjust delivery routes during monsoon rains, minimizing delays.

2. The Planning Process: A Step-by-Step Cycle

Planning is not a one-time task but a continuous loop of evaluation and adjustment. Here’s how it works in practice (e.g., Himalayan Java’s expansion into Pokhara):

flowchart TD
  A["1. Define Objectives"] --> B["2. Analyze Environment<br/>(SWOT/PESTEL)"]
  B --> C["3. Develop Alternatives<br/>(Brainstorming, Scenario Analysis)"]
  C --> D["4. Evaluate Alternatives<br/>(Cost-Benefit, Decision Trees)"]
  D --> E["5. Select Best Plan<br/>(Committee/Manager Approval)"]
  E --> F["6. Implement Plan<br/>(Assign Roles, Timelines)"]
  F --> G["7. Monitor & Control<br/>(KPIs, Feedback Loops)"]
  G -->|"If deviating"| B
  G -->|"If successful"| A

Worked Example: Kathmandu Traffic Management

• Objective: Reduce congestion on Ring Road.
• Analysis: SWOT reveals weakness = outdated traffic lights, opportunity = AI-based adaptive signals.
• Alternatives:
  • Option 1: Manual adjustments (cheap but reactive).
  • Option 2: Smart sensors + AI (costly but dynamic).
• Decision: City chose Option 2, using data from NTC’s traffic cameras to optimize light timings.

3. Decision-Making: From Theory to Reality

Decision-making is the core of planning—choosing between alternatives. Theories range from perfect rationality (unrealistic) to bounded rationality (what managers actually use).

Decision-Making Models

Key Insight:

• Nabil Bank uses bounded rationality when approving loans: they don’t have perfect data on a farmer’s future income but approve based on satisficing criteria (e.g., collateral + past repayment history).
• Google’s PageRank algorithm (used in search) is a rational model—but even here, engineers use heuristics (simplifying assumptions) to make it computable.

4. Tools for Better Planning and Decisions

A. SWOT Analysis: Internal vs. External Factors

SWOT helps organizations like Himalayan Java assess:

• Strengths: Strong brand loyalty in Kathmandu.
• Weaknesses: Limited distribution in rural areas.
• Opportunities: Rising demand for organic coffee in Pokhara.
• Threats: Competition from instant coffee brands.

Worked Example: Daraz’s SWOT

• Strength: First-mover advantage in Nepal’s e-commerce.
• Weakness: High customer service complaints.
• Action: Invested in AI chatbots (like their "Daraz Help" bot) to reduce response time.

B. PESTEL Analysis: Macro-Environmental Scanning

PESTEL examines external forces affecting businesses. NTC uses this to plan infrastructure:

• Political: Government’s "Digital Nepal" policy → favor fiber expansion.
• Economic: Inflation → adjust pricing for broadband.
• Social: Urbanization → focus on Kathmandu/Pokhara.
• Technological: 5G rollout → prepare for IoT integration.
• Environmental: Monsoon floods → reinforce network cables.
• Legal: New data privacy laws → upgrade cybersecurity.

C. Decision Trees: Quantifying Risks

Decision trees help Nabil Bank evaluate loan risks. Example:

• Scenario: Approve a ₹500,000 loan to a restaurant.
  • Success (70% chance): ₹600,000 repayment → ₹100,000 profit.
  • Failure (30% chance): ₹0 repayment → ₹500,000 loss.
• Expected Value = (0.7 × ₹100,000) + (0.3 × –₹500,000) = ₹70,000 – ₹150,000 = –₹80,000.
• Decision: Reject unless collateral covers the risk.

5. Common Pitfalls in Planning and Decision-Making

6. Case Study: How Nabil Bank Uses Planning and Decision-Making

Challenge: High loan defaults in the hospitality sector post-2015 earthquake. Solution:

1. Planning:
   • Strategic: Shift focus from retail to SME loans (less volatile).
   • Operational: Introduce dynamic interest rates tied to GDP growth.
2. Decision-Making:
   • Used decision trees to assess sector-specific risks.
   • Implemented collateral rules for high-risk loans.
3. Tools:
   • SWOT: Identified opportunity in agricultural financing.
   • PESTEL: Noted legal changes in land mortgage laws. Result: Default rates dropped by 22% in 3 years.

7. Exam Tip: How to Score Full Marks

1. Define clearly: Always start with definitions (e.g., "Planning is a systematic process...").
2. Use real examples: Link theories to Nepali businesses (Nabil Bank, Daraz, NTC). Examiners reward contextual relevance.
3. Diagrams > Text: Draw flowcharts for processes (e.g., planning cycle) and decision trees for numerical questions.
4. Compare models: For decision-making, contrast rational vs. bounded rationality with pros/cons.
5. Critical analysis: Don’t just describe SWOT—explain how a company would act on weaknesses (e.g., "Himalayan Java should partner with local cooperatives to cut costs").
6. Numerical questions: For decision trees, show calculations step-by-step (expected value, probabilities).

Common Exam Questions:

• "Explain the planning process with an example from a Nepali company." → Use NTC’s fiber expansion.
• "How would you apply SWOT to improve Pathao’s customer satisfaction?" → Highlight weakness = driver reliability, opportunity = AI routing.
• "Calculate the expected value of a decision using a decision tree." → Practice with loan approval scenarios.

In the Real World

1. Nabil Bank’s Loan Approval System

   • Idea Used: Decision trees + bounded rationality.
   • How: The bank’s underwriting team uses a scoring model (credit score, collateral, sector risk) to approve loans. Unlike a purely rational model, they accept satisficing outcomes (e.g., approving 80% of "good" loans quickly rather than analyzing all 100% perfectly).

2. Daraz’s Inventory Planning for Monsoon Season

   • Idea Used: Operational planning + contingency strategies.
   • How: Daraz’s supply chain team uses historical sales data to forecast demand spikes during monsoon (e.g., umbrellas, water purifiers). They also stock backup inventory in multiple warehouses to handle last-mile delivery delays caused by floods.

3. NTC’s Traffic Light Optimization (Kathmandu)

   • Idea Used: Data-driven decision-making + SWOT analysis.
   • How: NTC partnered with Kathmandu Metropolitan City to install adaptive traffic signals using real-time data from cameras. Their SWOT analysis revealed:
     • Strength: Existing traffic management infrastructure.
     • Weakness: Manual overrides causing inefficiencies.
     • Action: Replaced 50% of signals with AI-controlled ones, reducing congestion by 15% in peak hours.

4. Pathao’s Driver Dispatch Algorithm

   • Idea Used: Heuristics in bounded rationality.
   • How: Pathao’s algorithm doesn’t use a perfect rational model (which would require solving a complex NP-hard problem in real time). Instead, it uses simplified rules (e.g., prioritize drivers closer to the pickup location, ignore minor detours) to make fast, good-enough decisions—a classic example of satisficing.

5. NEPSE’s Circuit-Breaker Rules

   • Idea Used: Contingency planning.
   • How: NEPSE’s Level 1, 2, and 3 halts are pre-defined responses to market volatility. For example:
     • If the Nepse Index drops 10% in a day (Level 1), trading halts for 30 minutes.
     • If it drops 20% (Level 2), trading halts for the day.
   • This turns uncertainty into structure, protecting investors from panic selling.