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Data Types

Product Master Data: When the Item Record Is Wrong

Every sale, every stock movement and every margin report starts from the product record. It says what the item is, how it is counted, what it costs and where it belongs. When that record is wrong, the error travels into invoices, inventory and pricing at once, and it rarely announces itself.

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By the korppi team, and

What the Product Record Decides

A product record carries more than a name and a code. It holds the unit of sale and the unit of stock, the pack size, the standard or last cost, the tax rate, the category used for reporting and pricing, and often the barcode customers and marketplaces use to identify it. Sales, purchasing, warehousing and finance all read from the same record.

That is what makes product data so powerful and so fragile. One wrong value is not one wrong invoice. It is every invoice, every stock count and every margin calculation that touches that item until someone notices.

Units and Pack Sizes That Do Not Agree

The classic product data error is a unit mismatch. The item is bought by the box, stored by the piece and sold by the case, and somewhere along the way a conversion is wrong. A case of twelve is invoiced as a single piece. A box is received as one unit and the stock count is out by a factor of ten.

These errors are hard to see in totals because volumes and values still look plausible. They show up as customers who are undercharged without complaint, stock that never reconciles and margin reports that nobody quite believes.

Outdated Costs and Hidden Losses

Margin is price minus cost, and the cost comes from the product record. When purchase prices rise and the cost on the item is not updated, every sale of that item reports a margin it does not have. Products that lose money look healthy, discounts are approved on the wrong basis and the gap only appears when gross margin falls short at period end.

In high-inflation periods this effect is strongest, because costs move faster than records. A price list that was right in January can be selling below cost by June, and the sales report will not say so.

Duplicate Items and Wrong Categories

Duplicate items arise when the same product is created twice, by a new supplier, a new pack size or a new channel. Sales history and stock are split, so one code looks like a slow mover while its twin runs out. Category errors do similar damage: an item in the wrong category gets the wrong price rules, the wrong discount and the wrong place in every report.

Product data problems are not limited to one company. When GS1 UK and Cranfield School of Management compared product data held by large UK grocery retailers with the data from their suppliers, they found it inconsistent in well over 80% of cases, and estimated losses of at least 700 million pounds over five years plus a further 300 million in lost sales. Every system that receives your product data, including the marketplaces in e-commerce and marketplace data, inherits its errors.

Where Product Data Meets Stock and Sales

Wrong product data is one of the main reasons inventory and stock data drift from reality. IHL Group estimates in its 2026 study that out-of-stocks and overstocks cost retailers worldwide about 1.7 trillion dollars a year, and many of those situations begin with an item record that says the wrong thing about what is on the shelf.

On the sales side, product data feeds straight into pricing and discount leakage. Writing in MIT Sloan Management Review, Thomas Redman estimated that bad data costs most companies 15% to 25% of revenue, and product records are among the most widely shared data in any business.

What korppi Delivers

korppi brings product record problems to the surface before it reports any money and puts a value on each one from the invoice lines and stock movements it affects. You see which items are costing revenue or margin, how much and who owns the fix, instead of a gross margin that is simply lower than planned.

The korppi Data Health Report gives you that picture once, with the before and after. korppi Revenue Intelligence keeps it current with every new export. Every figure is calculated from your own data, AI explains the results without inventing numbers and a read-only export is enough. korppi never writes to your system.

Start With a Data Health Report

If your margin reports do not quite match what you expect, the product master is a good place to look. Request a Data Health Report for your own data, or request a demo to see korppi first. See also the overview of master data types.

Frequently Asked Questions

What is product master data?

It is the stable record of each item you buy, stock or sell: code, description, units and pack sizes, cost, tax rate, category and identifiers such as barcodes. Sales, purchasing, warehousing and finance all depend on it.

How does wrong product data reduce margin?

An outdated cost makes unprofitable sales look profitable, a wrong unit undercharges customers and a wrong category applies the wrong price and discount. Each error repeats on every transaction for that item until it is fixed.

Is product data quality only a retail concern?

No. Manufacturers, distributors and wholesalers depend on product data just as much, and any company that sells through marketplaces or to large retailers passes its product data on to them.

What does korppi need to show the cost of product data errors?

Standard read-only exports of your product, stock and sales data. korppi never writes to your system and the details are agreed with your team.

Sources

  1. Data Crunch Report: The Impact of Bad Data on Profits and Customer Service in the UK Grocery Industry · GS1 UK and Cranfield School of Management, 2009
  2. The 2026 Inventory Distortion Study · IHL Group, 2026
  3. Seizing Opportunity in Data Quality · MIT Sloan Management Review, 2017