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Demand Forecast

Demand Forecast allows you to view, upload, and manage demand forecasts for products over time.

Demand Forecast Overview

Overview​

  • Table view: Forecasted demand by SKU and date
  • Chart view: Visual representation of demand trends
  • Bulk upload: Import forecasts from files
  • Two upload types: Time Series or Average forecasts

Date Range Controls​

  • Start: Beginning date for forecast view
  • Days: Number of days to display (e.g., 12 days)
  • End Sat: Calculated end date
  • Date picker with calendar interface

View Tabs​

Table Tab​

Shows forecasted demand in tabular format:

Columns:

  • SKU: Product code
  • SKU Name: Product description
  • Date Columns: Forecasted quantity for each date (e.g., 29/06/2026, 30/06/2026, 01/07/2026...)

Each cell shows the forecasted demand quantity for that SKU on that date.

Chart View

Chart Tab​

Visual representation of demand forecasts:

Chart Features:

  • X-axis: Timeline (dates)
  • Y-axis: Value (quantity)
  • Multiple lines: Each SKU shown as a separate colored line
  • Legend: Shows which color represents which SKU
  • Interactive: Hover to see exact values

Reading the chart:

  • Horizontal lines indicate steady demand
  • Upward slopes show increasing demand
  • Downward slopes show decreasing demand
  • Step changes indicate demand shifts

SKU Filter​

Select SKUs dropdown:

  • Filter which products to display
  • Search box to find specific SKUs
  • Select multiple SKUs
  • Useful for focusing on specific products

View Toggle​

Daily / Weekly buttons:

  • Daily: Shows demand by individual days
  • Weekly: Aggregates demand by week
  • Toggle between views for different planning horizons

Bulk Upload​

Bulk Upload button (top right):

  • Opens upload workflow
  • Import demand forecasts from files
  • Two upload types available

Choose Demand Forecast Upload Type​

Two options for uploading forecasts:

Time Series Forecast​

Description: Upload demand forecasts with specific quantities for each time period. Each column represents a date with its corresponding forecast quantity.

File format: SKU, Date1, Date2, Date3...

Example table structure:

  • Column 1: SKU code
  • Column 2: Date 1 (e.g., 21/10/2025) with quantity
  • Column 3: Date 2 (e.g., 27/10/2025) with quantity
  • Additional date columns as needed

Button: Choose Time Series Forecast

Average Forecast​

Description: Upload demand forecasts with a single quantity per SKU. The system will distribute this across multiple time periods based on your configuration.

File format: SKU, Quantity

Example table structure:

  • Column 1: SKU code
  • Column 2: Quantity (e.g., 20,321)
  • System distributes across periods (e.g., Weekly)

Button: Choose Average Forecast

Upload Time Series Demand Forecasts​

4-step wizard:

Step 1: File Upload​

Upload your Time Series Data File

  • Drag and drop area
  • Or click to select a file
  • Next button to proceed

Step 2: Select Data​

Select the data you would like to import

Select Sheet:

  • Dropdown to choose worksheet (e.g., "Timeseries-Forecast")

Preview: Table showing imported data:

  • SKU ID: Product codes
  • Name: Product names
  • Date columns: Forecasted quantities by date (1/6/2026, 8/6/2026, 15/6/2026, etc.)

Preview allows verification before import.

Step 3: Fields & Date Configuration​

Field Mapping Options & Configure Date Format and Frequency

Map Required Fields:

System Fields → Your Data Fields

  • SKU: Dropdown to select field (e.g., "Please select a field...")
  • First Date Column: Dropdown to select field

Date Format:

  • Format selector (e.g., DD/MM/YYYY)
  • "Select the date format used in your spreadsheet columns"

Forecast Frequency:

  • Dropdown (e.g., "Weekly")
  • "How frequently are the forecasts in your data?"

Buttons:

  • Prev: Go back to previous step
  • Next: Continue to next step

Step 4: Edit and Save​

Edit and Save

Preview: Your time series data will be converted to individual forecast entries. Each cell with a quantity will create a separate demand forecast record for that SKU and date.

Preview table:

  • SKU: Product codes
  • Date columns: Forecasted quantities
  • Shows exactly what will be imported

Buttons:

  • Prev: Go back to edit configuration
  • Save: Import the forecasts

Common Workflows​

Viewing Current Forecasts​

  1. Navigate to Demand Forecast
  2. Select Table tab to see detailed numbers
  3. Or select Chart tab for visual trends
  4. Use Select SKUs to filter specific products
  5. Adjust date range to focus on planning period
  1. Select Chart tab
  2. Choose SKUs to compare
  3. Look for:
    • Seasonal patterns
    • Growth trends
    • Demand spikes
    • Declining products
  4. Use insights for capacity and inventory planning

Uploading Time Series Forecasts​

  1. Click Bulk Upload button
  2. Select Time Series Forecast
  3. Step 1: Upload file with SKU, Date1, Date2, Date3... format
  4. Step 2: Select worksheet and preview data
  5. Step 3: Map SKU and First Date Column fields
  6. Step 3: Configure date format (e.g., DD/MM/YYYY) and frequency (e.g., Weekly)
  7. Step 4: Review preview and click Save

Uploading Average Forecasts​

  1. Click Bulk Upload button
  2. Select Average Forecast
  3. Upload file with SKU and Quantity columns
  4. System distributes quantity across periods based on configuration
  5. Useful for simple, steady-state forecasts

Switching Between Daily and Weekly Views​

  1. Use Daily view for detailed short-term planning
  2. Use Weekly view for high-level capacity planning
  3. Weekly aggregates daily forecasts for easier analysis

Understanding Forecasts​

Forecast uses:

  • Production planning: Schedule work orders to meet demand
  • Inventory planning: Maintain appropriate stock levels
  • Capacity planning: Ensure sufficient production capacity
  • Material planning: Order materials to support production
  • Sales planning: Align sales efforts with production capability

Forecast accuracy:

  • Regularly update forecasts based on actual demand
  • Compare forecasts to actuals to improve accuracy
  • Adjust for seasonality, promotions, and market changes

Tips​

  • Update forecasts regularly to reflect changing market conditions
  • Use Chart view to quickly spot trends and anomalies
  • Time Series forecasts provide more granular control for variable demand
  • Average forecasts work well for stable, predictable products
  • Weekly view is useful for strategic planning
  • Daily view helps with tactical scheduling
  • Filter by Select SKUs to focus on key products or problem areas
  • Review forecasts before uploading to catch data errors
  • Use date format configuration to match your spreadsheet format
  • Forecast frequency (Daily/Weekly) should match your planning cycle
  • Schedule: Auto-scheduler uses forecasts to plan production
  • Work Orders: Create work orders to meet forecasted demand
  • Materials: Material requirements driven by forecast-based production plans
  • Inventory: Stock projections based on forecasted consumption
  • Capacity Report: Compare forecasted demand against available capacity