Compare two sales forecasting methods:
• Static Forecast: Orders placed based on a single, initial forecast for the entire season.
• Dynamic Forecast: Orders placed for a short initial period, then updated based on actual sales and used for the remaining season.
Data Setup:
- Products: Select 5-10 products (P1, P2, P3, P4, P5).
- Initial Forecast: Enter an initial sales forecast unit for each product. For example, 200 units for P1. 100 units for P2, 250 units for P3……
- Sales Period: Set the sales period to 90 days
- Daily Sales: Calculate daily sales for each product by dividing the forecast by the sales period. Example, P1= 200/90= 2.22 units per day.
- Initial Order: Specify the initial order quantity for the first 20 days. E.g. 44 units for P1
- Sales Monitoring Period: Define the sales monitoring period as 14 days
- Costs & Prices: Set a cost price for each product assuming a 63% gross margin
Dynamic Forecast Simulation:
- Actual Sales: Enter actual daily sales for each product during the monitoring period (14 days).
- Updated Forecast: Based on actual sales data, revise the initial forecast for the remaining period (Days 21-90). This can be done using various methods like historical averages, trend analysis, or simply adjusting based on observed trends. Update the forecast.
- Remaining Order: Calculate the remaining order quantity for each product by subtracting the initial order from the updated forecast for the remaining period.
Static Forecast Simulation:
- Lost Sales/Excess Inventory: In a separate section, track lost sales (opportunities missed due to insufficient stock) or excess inventory (unsold units) for the static forecast scenario based on the initial forecast and actual sales data.
Analysis:
- Sales Revenue: Calculate sales revenue for both scenarios by multiplying the actual daily sales (Dynamic) or forecasted daily sales (Static) by the selling price.
- Profit: For the dynamic scenario, calculate profit by subtracting the cost price from the sales revenue
- Leftover Stock: Calculate leftover inventory for the dynamic scenario by subtracting actual sales from the total received quantity (initial order + remaining order).
- Markdown Revenue: If there's leftover stock, calculate markdown revenue by multiplying the leftover quantity by a markdown percentage (e.g., 50%).
- Total Revenue: Calculate the total revenue for the dynamic scenario by summing sales revenue and markdown revenue (if applicable).
Full Answer Section
- P1: 44 units
- P2: 33 units
- P3: 49 units
- P4: 40 units
- P5: 22 units
Sales Monitoring Period: 14 days
Cost Price (assuming 63% gross margin):
- All products: $10 (Selling price: $27)
Dynamic Forecast Simulation:
(Note: This requires entering actual sales data for the 14-day monitoring period, which is not provided in this example.)
- Actual Sales: Enter actual daily sales for each product during the monitoring period.
- Updated Forecast: Based on actual sales trends, revise the initial forecast for the remaining period (Days 21-90).
- Remaining Order: Calculate the remaining order quantity by subtracting the initial order from the updated forecast for the remaining period.
Static Forecast Simulation:
- Lost Sales/Excess Inventory: Track lost sales (missed opportunities) or excess inventory (unsold units) based on the initial forecast and actual sales data.
Analysis:
Sales Revenue:
- Dynamic: Multiply actual daily sales by selling price for each day.
- Static: Multiply forecasted daily sales by selling price for each day.
Profit (Dynamic Scenario Only):
- Subtract cost price from sales revenue for each day.
Leftover Stock (Dynamic Scenario Only):
- Subtract actual sales from the total received quantity (initial order + remaining order) for each product.
Markdown Revenue (Dynamic Scenario Only - If Applicable):
- If there's leftover stock, multiply the leftover quantity by the markdown percentage (e.g., 50%) to get markdown revenue.
Total Revenue (Dynamic Scenario Only):
- Sum sales revenue and markdown revenue (if applicable).
Comparison:
This analysis will reveal the strengths and weaknesses of each method:
- Static Forecast:
- Simpler to implement.
- May lead to lost sales if demand is underestimated.
- May result in excess inventory and potential markdowns if demand is overestimated.
- Dynamic Forecast:
- More accurate as it adapts to actual sales trends.
- Requires more effort for monitoring and updating forecasts.
- Can reduce lost sales and excess inventory.
Conclusion:
The Dynamic Forecast generally offers a more accurate and potentially more profitable approach compared to the Static Forecast. However, it requires additional effort for sales monitoring and forecast updates. The optimal approach may depend on factors like product demand volatility, inventory holding costs, and the cost of lost sales.
Sample Answer
This analysis compares two sales forecasting methods: Static Forecast and Dynamic Forecast, to assess their impact on sales, inventory, and profitability.
Data Setup:
Products: P1, P2, P3, P4, P5
Initial Forecast:
- P1: 200 units
- P2: 150 units
- P3: 220 units
- P4: 180 units
- P5: 100 units
Sales Period: 90 days
Daily Sales (Initial Forecast): (Rounded to two decimal places)
- P1: 2.22 units/day
- P2: 1.67 units/day
- P3: 2.44 units/day
- P4: 2.00 units/day
- P5: 1.11 units/day
Initial Order (First 20