Forecasting and Capacity Planning: Demand Forecasting Basics, Capacity Types and Break-Even in Capacity Decisions Questions

Question 1

What is capacity?

Accepted Answer

**Capacity** is the maximum output a system can produce in a given time period under given conditions.

Question 2

Define forecasting.

Accepted Answer

**Forecasting** is the process of estimating future demand using past data, present information and assumptions about the future.

Question 3

What is design capacity?

Accepted Answer

**Design capacity** is the theoretical maximum output as per design specification of a facility or machine.

Question 4

What is moving average forecasting?

Accepted Answer

**Moving average forecasting** estimates future demand as the average of demand in the last (n) periods.

Question 5

State one objective of demand forecasting.

Accepted Answer

One objective of forecasting is to plan **production and inventory** so that stock-outs and overstocking are reduced.

Question 6

What is break-even point (in output terms)?

Accepted Answer

**Break-even point** is the output level where total cost of two alternatives is equal (or where total revenue equals total cost in profit analysis).

Question 7

Explain qualitative forecasting methods (any three) with brief meaning.

Accepted Answer

Qualitative (judgmental) forecasting methods (any three):

- **Delphi method**: experts give forecasts in rounds; feedback is shared until consensus is reached.
- **Sales force composite**: salespeople estimate future demand based on customer interactions.
- **Market research**: surveys, interviews and test marketing to estimate demand.
- **Managerial judgment**: experienced managers estimate demand using knowledge of market conditions.

Thus, qualitative methods are useful when historical data is limited or demand conditions are changing.

Question 8

Explain forecasting horizons: short, medium and long term (any three points).

Accepted Answer

Forecasting horizons:

- **Short-term** (weeks/months): used for scheduling, day-to-day production and inventory decisions.
- **Medium-term** (months to 1–2 years): used for aggregate planning, workforce and capacity adjustments.
- **Long-term** (2+ years): used for plant location, new facilities, major capacity and technology investments.

Hence, longer horizons support strategic decisions, while short horizons support operational decisions.

Question 9

Explain exponential smoothing (basic) and the role of alpha (α) (any three points).

Accepted Answer

### **Exponential Smoothing (Basic)**

Exponential smoothing updates the forecast by using the previous forecast and the latest error.

Key points (any three):
- New forecast = Old forecast + **α** × (Actual − Old forecast).
- **α (alpha)** lies between 0 and 1 and decides how much weight is given to recent demand.
- Higher **α** → forecast reacts faster to recent changes; lower **α** → smoother forecast.

Thus, exponential smoothing is simple and useful for short-term forecasting when demand is relatively stable.

Question 10

Differentiate between design capacity, effective capacity and actual output (any three points) with a table.

Accepted Answer

Design capacity vs Effective capacity vs Actual output:

- **Design capacity** is the theoretical maximum as per design.
- **Effective capacity** is practical maximum after considering maintenance, breaks and setups.
- **Actual output** is the real output achieved in practice.

Table:

| Term | Meaning | Usual relation |
|---|---|---|
| **Design** | theoretical max | highest |
| **Effective** | practical max | lower than design |
| **Actual** | achieved output | ≤ effective |

Hence, performance gaps can be identified by comparing design, effective and actual values.

Question 11

Explain steps in forecasting process (any five steps) with brief explanation.

Accepted Answer

Steps in forecasting process (any five):

- **Define purpose**: clarify why the forecast is needed (production, capacity, inventory).
- **Select item and horizon**: decide what to forecast and for what time period.
- **Collect data**: past demand, market information, seasonality, trends.
- **Choose method**: qualitative (Delphi, surveys) or quantitative (moving average, smoothing).
- **Prepare forecast**: compute/estimate the forecast.
- **Monitor accuracy**: compare actual vs forecast and compute errors.
- **Revise**: update method/parameters as new data arrives.

Thus, forecasting is a continuous process with regular review and improvement.

Question 12

Explain forecast error and any two measures of forecast accuracy (brief).

Accepted Answer

### **Forecast Error and Accuracy Measures**

- **Forecast error (e)** is the difference between actual demand and forecast:
  - e = Actual − Forecast

Accuracy measures (any two):
- **MAE (Mean Absolute Error)**: average of absolute errors; easy to interpret in units.
- **MSE (Mean Squared Error)**: average of squared errors; penalizes large errors heavily.
- **MAPE (Mean Absolute Percentage Error)**: average of percentage errors; useful for comparing different items.

Thus, error measures help select better forecasting methods and improve reliability of capacity planning.

Question 13

Explain capacity strategies (lead, lag and match) with merits and limitations (exam-style with table).

Accepted Answer

### **Capacity Strategies (Lead, Lag, Match) — Exam-Style**

Capacity strategy decides when and how much capacity to add relative to demand.

#### **1) Lead strategy**
- Add capacity **before** demand increases.
- **Merits**: better customer service, capture market share, avoid lost sales.
- **Limitations**: risk of **idle capacity** and higher fixed cost initially.

#### **2) Lag strategy**
- Add capacity **after** demand has increased.
- **Merits**: better utilization, less risk of overcapacity.
- **Limitations**: risk of lost sales, late deliveries during demand surge.

#### **3) Match strategy**
- Add capacity in small steps to match demand.
- **Merits**: balanced risk and cost.
- **Limitations**: requires frequent adjustments; may still face short-term mismatch.

Table:

| Strategy | When capacity is added | Main advantage | Main risk |
|---|---|---|---|
| **Lead** | before demand | service level ↑ | idle capacity ↑ |
| **Lag** | after demand | utilization ↑ | lost sales ↑ |
| **Match** | step-by-step | balanced | adjustment complexity |

**Conclusion:** Choice depends on demand uncertainty, competition, cost structure and service requirements.

Question 14

Explain break-even analysis for capacity/process choice with a numerical illustration (exam-style).

Accepted Answer

### **Break-Even Analysis for Capacity/Process Choice (Exam-Style)**

Break-even analysis compares two alternatives based on fixed and variable costs.

Assume two process alternatives:
- **Option A (manual)**: Fixed cost (FC_A = 50,000), Variable cost (VC_A = 80) per unit
- **Option B (automatic)**: Fixed cost (FC_B = 2,00,000), Variable cost (VC_B = 40) per unit

#### **Step 1: Write total cost equations**
- (TC_A = 50,000 + 80Q)
- (TC_B = 2,00,000 + 40Q)

#### **Step 2: Find break-even output (Q*)**
At break-even: (TC_A = TC_B)

(50,000 + 80Q = 2,00,000 + 40Q)

40Q = 1,50,000

Q* = 3,750 units

#### **Decision**
- If output **< 3,750**, Option A is cheaper (lower fixed cost).
- If output **> 3,750**, Option B is cheaper (lower variable cost).

Mini table:

| Output level | Preferred option | Reason |
|---|---|---|
| Low volume | A | fixed cost low |
| High volume | B | variable cost low |

**Conclusion:** Break-even analysis helps choose the best capacity/process option based on expected demand volume.

Question 15

Explain steps in forecasting process and how accuracy is controlled (exam-style with flowchart).

Accepted Answer

### **Forecasting Process and Accuracy Control (Exam-Style)**

Forecasting is a systematic process, and accuracy must be monitored so that decisions remain reliable.

#### **Steps in forecasting**
- **Define purpose** and time horizon.
- **Collect data** (historical demand, market information).
- **Select method** (qualitative or quantitative).
- **Prepare forecast**.
- **Compare with actual demand** and calculate errors.
- **Revise model** and update assumptions regularly.

#### **Accuracy control**
- Use error measures like **MAE**, **MSE**, **MAPE**.
- If errors are high, change method, adjust parameters (e.g., α), or update data.

Flowchart:

```text
Define purpose → Collect data → Choose method → Make forecast
      ↓
Compare with actual → Compute error (MAE/MSE/MAPE)
      ↓
If error high → revise method/parameters → new forecast
```

**Conclusion:** Regular error monitoring and revision makes forecasting more accurate and improves capacity and inventory decisions.

Forecasting and Capacity Planning: Demand Forecasting Basics, Capacity Types and Break-Even in Capacity Decisions

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