Ensure data quality and completeness (AI)
Drive your data quality—don’t just deal with it. Transform scattered information into reliable, actionable data. MaPS System unifies MDM, PIM, and DAM to guarantee completeness, consistency, and traceability across all your master data, from the supplier to the end customer.
Challenges related to data quality and completeness
Finally accelerate your processes
When data is complete and reliable, launches, updates, and publications are no longer held up. You gain speed across every cycle — offers, master data, content, and markets.
Reduce hidden costs
Fewer re-entries, “parallel” files, last-minute corrections, and endless back-and-forth between teams. Data becomes a controlled flow, rather than a permanent building site.
Ensure reliable field execution
Inconsistent information (units, statuses, relationships, versions) quickly turns into operational errors. Governed data means fewer incidents and smoother day-to-day operations.
Improve the customer experience
Improve the customer experience Clear and accurate information = fewer abandoned carts, fewer returns, and fewer support requests. Data becomes a driver of trust.
Secure omnichannel and partner relationships
Marketplaces, e-commerce, B2B clients, and catalogues impose strict requirements. Complete and compliant data means fewer rejections, less reprocessing, and faster distribution across all channels.
Protect compliance and brand integrity
Missing or incorrect data, obsolete documents, unclear usage rights—the risk is immediate. Quality also means maintaining control over evidence, versions, and associated content.
Making AI truly effective
AI is only as powerful as the data behind it. With complete, consistent, and traceable master data, you can industrialise enrichment, classification, and quality checks—delivering reliable results at scale.
How to industrialise data quality and completeness with MaPS System?
Industrialisation means moving from ad-hoc corrections to a continuous, measured, and governed approach. MaPS System secures data at scale by combining a single source of truth with control rules, workflows, and monitoring across all domains (products, third parties, suppliers, sites, content, documents, etc.).
MaPS System consolidates information from ERP, CRM, PLM, supplier files, or business teams, then harmonises it into a common data model: master data, nomenclatures, units, formats, languages, and structures (variants, hierarchies, relationships).
Completeness requirements vary depending on the channel, country, or business scenario. MaPS System allows you to define requirements by scope:
- Mandatory and conditional attributes (based on category, typology, or status)
- Completeness by language, market, and channel (e-commerce, B2B, marketplaces, catalogues, partners)
Requirements linked to industry standards (FAB-DIS, ETIM, GDSN, DPP, customer-specific formats)
To prevent errors and maintain data stability over time, MaPS System industrialises quality through automated checks:
- Validation of formats, value ranges, units, and cross-attribute consistency
- Mapping and relationship checks (categories, ranges, hierarchies)
- Detection of inconsistencies and duplicates across managed master data
- Blocking or alerting for “critical” errors prior to distribution
Effective quality management relies on robust processes. MaPS System defines clear steps and accountabilities:
- Role-based enrichment cycles (contribution, review, and approval)
- Clear status tracking and milestones (draft, awaiting approval, approved, live)
- Comprehensive audit trails (tracking every change, user, and data source)
MaPS System transforms quality and completeness into actionable indicators:
- Completeness scoring (global, by channel, by country, or by typology)
- Monitoring of passed/failed rules and critical bottlenecks
- Dashboards to prioritise efforts and secure publication
Data is not limited to attributes: visuals, documents, and usage rights are essential for distribution. MaPS System links and monitors all content (formats, versions, rights, usage) to ensure that every publication relies on the correct assets at the right level of compliance.
When data is structured and governed, AI becomes a powerful accelerator: assisting with content creation, suggesting enrichments, automating classification, detecting anomalies, and performing advanced checks. The goal is to save time without compromising reliability, thanks to integrated validation and traceability.
Concrete examples of quality and completeness managed with MaPS System
Quality and completeness are managed on a daily basis, using rules, workflows, and requirements tailored to each specific use case. Here are some concrete examples applicable across various master data domains (products, third parties, suppliers, sites, content, and documents).
Supplier onboarding and multi-source collection
Centralise heterogeneous files (Excel, portals, partner exports), check formats, units, mandatory fields, and consistency, then qualify data before distribution.
Result: faster integrations, fewer manual corrections, and secure data exchanges.
Smoother omnichannel publication
Define completeness requirements per channel (e-commerce, marketplace, B2B, catalogue), featuring mandatory/conditional attributes, multi-language support, and validation gates before distribution.
Result: fewer rejections, smoother product launches, and guaranteed consistency across all touchpoints.
Master Data Governance (customers, suppliers, organisations, sites)
Harmonise master data (nomenclatures, statuses, addresses, hierarchies), limit duplicates, track modifications, and secure common business rules.
Result: reliable master data that can be used by all teams, without conflicting versions.
Standardisation and B2B exchanges (FAB-DIS, ETIM, GDSN, customer formats)
Structure attributes and taxonomies, manage standard versions, automate checks, and generate “ready-to-exchange” exports based on required specifications.
Result: industrialised data exchange, reduced manual reprocessing, and improved reliability of shared data.
Performance management through scoring and prioritisation
Implement completeness scores and quality checks (by scope, market, or channel) to quickly identify bottlenecks and focus efforts where they have the most impact.
Result: continuous, measured improvement directly oriented towards performance.
AI acceleration without losing control
Streamline data enrichment (including suggestions, classification, content generation, and anomaly detection) while upholding strict validation rules, workflows, and comprehensive traceability.
The Outcome: significant productivity gains at scale, backed by reliable and governed data.
A strategic priority: ensuring data quality and completeness
By mastering the quality and completeness of your information, you transform data into a genuine performance driver: faster to distribute, more reliable to use, and simpler to govern.
With MaPS System, you industrialise this daily control — through rules, workflows, and traceability — allowing you to publish with confidence, reduce manual rework, and sustainably secure your exchanges and channels.
Let’s build your growth together
Transform your data into a performance driver.
With our expertise, our scalable platform, and our commitment to providing tailored solutions, we support you at every stage to ensure your data management sustainably drives your success.
Your data. Your way. Your growth.
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