Demand planning forecast import fails due to date format mismatch in CSV template

ERP Infor CloudSuite
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1

Our monthly forecast import process is failing with date format validation errors. We’re using the standard CSV import template for demand planning, but CloudSuite keeps rejecting the file with ‘Invalid date format in ForecastDate column’ errors.

Our CSV file uses MM/DD/YYYY format (e.g., 06/01/2025), which matches what we’ve always used. The date format validation seems to have changed or become stricter in ICS 2023-1. The forecast data upload worked fine last month, but now nothing imports successfully.

Example error from the import log:


Row 45: Invalid date format '06/15/2025' in column ForecastDate
Expected format: YYYY-MM-DD
Import aborted at row 45 of 1200

I’ve checked the CSV import template documentation, but it still shows MM/DD/YYYY as acceptable. Has the date format requirement changed? How do we fix this without manually reformatting thousands of forecast records?

system 2

I’ll address all three focus areas comprehensively:

CSV Import Template: The ICS 2023-1 forecast import template has strict formatting requirements that differ from previous versions. Download the updated template from Demand Planning > Import/Export > Download Template. Key changes:

  • ForecastDate column: MUST be YYYY-MM-DD format (ISO 8601)
  • No alternate date formats accepted in CSV imports
  • Date validation occurs at row level - one invalid date fails entire import

Your template structure should look like:


ItemNumber,LocationCode,ForecastDate,Quantity,UOM
ITEM-001,WH-EAST,2025-06-01,150,EA
ITEM-001,WH-EAST,2025-06-15,175,EA

Critical: Column headers must match exactly (case-sensitive). No extra columns allowed unless defined in custom import profile.

Date Format Validation: The validation logic in 2023-1 is non-negotiable for forecast imports. The system performs these checks:

  1. Pattern validation: Must match YYYY-MM-DD regex pattern
  2. Date validity: Month 01-12, day valid for month, year 2000-2099
  3. Business logic: Forecast date cannot be more than 24 months in past or 60 months in future

Your error shows the validator is working correctly - it expects ISO format and rejects MM/DD/YYYY. The ‘Expected format: YYYY-MM-DD’ message is explicit about requirements.

To fix your existing process:

  • If generating from database: Modify query to format dates: `TO_CHAR(forecast_date, ‘YYYY-MM-DD’)
  • If from Excel: Use formula =TEXT(date_cell,"YYYY-MM-DD") in helper column, copy/paste values
  • If from ETL tool: Add date transformation step with output format YYYY-MM-DD

Forecast Data Upload: For your 1200-row file that’s failing at row 45, here’s the resolution process:

  1. Immediate Fix: Open your CSV in Excel/text editor

    • Find/Replace all dates: Convert MM/DD/YYYY to YYYY-MM-DD
    • Excel formula approach: Insert helper column with =TEXT(A2,“YYYY-MM-DD”), copy down, paste values over original
    • Text editor approach: Use regex find/replace if comfortable with patterns

  2. Validation Before Import: Use the import preview feature

    • Demand Planning > Import > Validate File
    • Reviews format without committing data
    • Shows all validation errors upfront

  3. Automated Solution: Modify your source data pipeline

    • If exporting from planning system: Change export format settings to ISO 8601
    • If from spreadsheet: Create macro to auto-format date column on save
    • If from database: Update query date formatting as shown above

  4. Alternative Approach: Use API instead of CSV

    
POST /demandplanning/api/v1/forecasts
Content-Type: application/json
X-Date-Format: MM/DD/YYYY

[API accepts format specification in header]

    The REST API is more flexible with date formats when specified in request headers.

For your current stuck import, reformat the dates in your CSV file to YYYY-MM-DD and re-upload. The import should complete successfully once date format matches system requirements. Going forward, adjust your forecast data generation process to output ISO format dates from the source to avoid manual reformatting.

This draft is based on general Infor CloudSuite knowledge. It has not been verified against your specific version and environment. Practitioners: verify the steps and share your experience below.

3

ICS 2023-1 did introduce stricter date validation for forecast imports. The system now enforces ISO 8601 format (YYYY-MM-DD) regardless of your regional settings. You’ll need to update your CSV generation process to output dates in that format. Most spreadsheet tools have date formatting functions that can handle this conversion automatically.

4

Before reformatting everything, check your Demand Planning > System Configuration > Import Settings. There’s a ‘Date Format Override’ option that was added in 2023-1. You might be able to configure the system to accept your existing MM/DD/YYYY format instead of changing all your source files.

Also verify your user profile’s regional settings haven’t changed. Sometimes system updates reset these to default values, which could explain why last month worked but this month doesn’t.

5

I checked the Import Settings and there is a Date Format Override field, but it’s grayed out and set to ‘ISO 8601 (System Default)’. I can’t modify it. My user profile regional settings show US format (MM/DD/YYYY), so that hasn’t changed. It seems like the system is enforcing ISO format regardless of configuration.

nikhildata 6

Confirmed this resolves the import failure — after updating our CSV ForecastDate column to YYYY-MM-DD ISO 8601 format in ICS Demand Planning, all 500+ forecast rows imported successfully.

7

The Date Format Override being grayed out is expected behavior in 2023-1. It’s only editable if you have ‘System Configuration Administrator’ role. However, even with that role, forecast imports specifically require ISO 8601 format for data consistency across multi-region deployments.

You have two options: 1) Reformat your CSV files before import, or 2) Use the Data Import API which accepts date formats specified in the request header. The API gives you more flexibility than CSV imports.

8

If you’re generating CSVs from Excel, you can use a formula to convert dates: =TEXT(A1,“YYYY-MM-DD”) where A1 contains your original date. Copy this formula down your date column, then paste values to replace the originals. Save as CSV and your format will be correct for import.

For automated processes, most ETL tools have date transformation functions that can handle this conversion in your data pipeline before generating the import file.

danieldata 9

Sometimes system updates reset these to default values, which could explain why last month worked but this month doesn’t.