Each material with a single name. At last.
Descriptive material standardization (PDM) is the process of describing each item in a unique, structured and standardized way, with a clear taxonomy of characteristics. We standardize and enrich your material records on an MDM (Master Data Management) platform, with automation and AI, eliminating duplicates and confusing descriptions that hold back purchasing, inventory and production.
160 clients trust us
Prepare your master data for the Brazilian Tax Reform
Pain
"Screw", "scr." and "SCREW M6" are the same item. And the system doesn't know it.
Free-form, non-standardized descriptions create duplicate items, repeat purchases, idle stock and reports no one trusts. The larger the base, the greater the chaos. And the stockroom clerk ends up deciding by eye: registering the item again, because searching takes more work than creating.
Duplicate items that turn into repeat purchases
Idle stock that no one can find
Wrong product classification that turns into tax risk
How we solve it
Taxonomy, standards and automation, at scale.
In the warehouse, everyone labels. In the master data, almost no one does.
Want to know how many duplicate items exist in your catalog today? The free assessment measures it in just a few days.
Get the free assessmentClassification and additional data
A standardized description is the start. The complete record is the goal.
Along with the description, we deliver the item's classification in the standards your operation uses and the data that procurement, tax, logistics and quality need to find in the record.
International standard
What UNSPSC is, and why we standardize on it
UNSPSC (United Nations Standard Products and Services Code) is an international standard for classifying products and services, maintained by GS1 US under the endorsement of the United Nations. It organizes the item into a hierarchy of segment, family, class and commodity, with a unique code for each level.
With the catalog classified in UNSPSC, spend by category becomes comparable across plants, companies and countries, procurement can consolidate demand and negotiate by family, and the data speaks to sourcing systems and marketplaces that already use this standard. We classify the item in UNSPSC together with the descriptive product standardization, in the same standardization flow.
Additional data
What else goes into the record
Translation into English and Spanish, for multi-country operations and catalog sharing across units.
Unit of measure normalized, with a conversion factor between purchasing, inventory and consumption units.
Packaging attributes: type, quantity per package, purchase multiple, weight and dimensions.
ANVISA regulatory attributes, when applicable: registration or notification, holder, presentation and risk class.
UNSPSC classification and descriptive product standardization, along with building the description, are supported by ADAM, our machine learning, with human validation before publishing to the ERP.
Learn about ADAM
Artificial intelligence
ADAM standardizes materials — and sustains governance afterward
ADAM is 4MDG's artificial intelligence. It reads the free-text description that comes from the requester, understands which material it refers to, proposes the standardized description, fills in the missing characteristics and points to the record that already exists in the base before a new one is created.
Cleansing
Legacy base in order
In the initial load, ADAM classifies and rewrites thousands of items at once, flags duplicates for review and returns the base with a single standard.
New record
Standard from the start
With each new request, the suggestion is already on screen: description, class, characteristics, classification and UNSPSC. The analyst reviews instead of typing from scratch.
Governance
A standard that doesn't degrade
The model keeps running on the production base, flagging standard deviations, new duplicates and incomplete fields for the steward to handle.
The final decision is always human: ADAM suggests and your team approves, with an audit trail of who accepted or rejected each suggestion.
Results
A clean catalog pays for itself.
The cost of bad data does not show up as a budget line. It shows up spread across repeat purchases, idle stock, disallowed credits and wrong decisions. The market has already measured this bill.
US$ 12,9 mi
is the average annual cost of poor data quality for an organization.
Source: Gartner, data quality survey
15 to 25%
of annual revenue is what companies lose because of bad data.
Source: MIT Sloan Management Review with Cork University Business School
59%
of organizations do not measure the quality of their own data, so they operate without knowing the size of the loss.
Source: Gartner, surveys with organizations
60 mi
records already managed
by 4MDG
321+
MDM projects
delivered since 2019
We know the size of this bill because we have faced it at industrial scale, with real clients and real databases.
Explore our Data Cleansing service →Step by step
How to standardize a catalog in five steps.
01
Diagnosis
We measure duplicates, empty fields and conflicting standards in your current base.
02
Taxonomy
We define families and attributes with procurement, inventory, tax and production.
03
Standardization
We rewrite short and long descriptions to the standard, with automation and AI.
04
Deduplication
We group and merge identical items, with specialist approval.
05
Governance
Workflow and rules keep the standard alive, so the base stays clean.
We integrate with what you use
Contact
Request the free assessment of your catalog.
We show you how many duplicate items, non-standard descriptions and inconsistent tax classifications exist in your database today. No commitment.
Av. Queiroz Filho, 1700, Torre E, Conjuntos 715 a 718
Vila Leopoldina, São Paulo, SP, 05319-000