At the core of every successful merchandise plan is accurate data. Before we can deliver a reliable plan, we must ensure that the data from your Point of Sale (POS) system aligns with the information uploaded to Retail ORBIT®.

Accurate data validation builds trust, improves planning accuracy, and supports long-term business success.

What Is Data Validation?

Data validation is the process of thoroughly reviewing the accuracy and completeness of your historical data against POS reports. This is a collaborative effort that requires careful review and open communication.

When validating data, the goal is to confirm:

• Classes – Ensure all merchandise planning classes are present and accurate

• Data Completeness – Confirm all expected classes contain data

• Key Data Points – Validate core metrics such as:

  • Sales

  • Markdowns

  • Receivings

  • Inventory

  • On-Order

This validation should be performed at three levels:

• Business Level – Confirm total company data is accurate

• Location Level – Ensure data reflects all physical store locations

• Class Level – Verify the accuracy of sales and inventory trends by merchandise class

Where and How to Perform Data Validation

Once your data has been uploaded or pulled, Support will notify you when it is available for review in the Report Library under the Monthly Reports tab in Data Validation.

At this stage, your role is to:

1. Open the report

2. Thoroughly review all data components for accuracy

3. Identify any discrepancies

4. Work with Support to resolve issues before the merchandise plan is created

Please note that filters are available at the top of the report. These allow you to:

• Select a specific Location

• Select a specific Class

• Select a specific Category

• Include or exclude specific data points

• Include or exclude specific data years

This report can also be exported to PDF or Excel for easier review.

Best Practices for Data Validation

Go Line by Line

Review each data point carefully and look for logical inconsistencies.

Examples include:

• Are markdowns higher than sales? This may indicate a copy/paste error.

• Are certain months missing sales or markdowns? Confirm whether this is expected or a sign of missing data.

Address Issues Early

Resolve data concerns before the first merchandise plan is presented. This creates a smoother planning process and helps prevent last-minute data integrity issues.

Common Data Issues and How to Avoid Them

Manual Data Upload Errors

Common issues with manual data uploads include:

• Typos – Double-check figures before uploading

• Copy/Paste Mistakes – Make sure all columns are aligned correctly

• Cost vs. Retail Mix-Ups – Confirm figures are entered into the correct fields

• Missing Data – Ensure all required data is included, especially markdowns and receivings

Shuttle Data Collection Errors

Even with automated Shuttle data pulls, inaccuracies can still occur. Common issues include:

• Location/Class Code Mismatches – Ensure POS location and class codes are mapped correctly

• Unlinked Receivings – Confirm receivings are properly tied to purchase orders

• Markdown Misclassification – Differentiate between permanent markdowns and POS discounts

• Class Mapping Errors – Verify where mapping occurs, whether in the POS or in Retail ORBIT®, and ensure it is completed correctly

The Bottom Line: Accuracy Drives Success

Thorough data validation is not just a task — it is a commitment to success.

By investing time in careful data validation, we create the foundation for more accurate, timely, and insightful merchandise planning. This ensures every decision is based on reliable information.