One management layer for ERP, PLM, CRM, and e-commerce data.
Data Control ensures that operational data is up to date, consistent, and accurate across all systems and in decision-making.
Reduce manual work, improve data quality, and ensure that decisions and automations are based on reliable data.
Do you recognize these situations?
Data is corrected and transferred to systems using Excel.
There is no certainty about which data is correct when making decisions.
The same customer or product appears under three different names.
Data in the ERP, PLM, and CRM systems is neither synchronized nor consistent.
Reports show different figures.
Data Control was built to solve these problems.
How does Data Control work?
Data Control makes operational data management part of everyday business operations. It brings data, workflows, and responsibilities together into one controlled framework. When data is easily accessible and reliable, decisions, processes, and automations throughout the organization use the same data. Data Control also helps manage documents, Excel files, portals, and other data sources outside systems as seamlessly as system data.
Identify and validate data
Data is automatically validated against agreed rules, formats, and business requirements before it moves into processes or other systems.
Manage corrections and decisions
Exceptions are directed to the appropriate responsible persons. Corrections, approvals, and decisions are made through controlled workflows, not in emails or Excel files.
Update, synchronize, and trace
Approved data is automatically updated across systems. Every change remains traceable, ensuring that the same data is available for reporting, processes, decision-making, and automations.
Use data from outside your systems
Not all business-critical data is stored in an ERP or CRM system. Data Control also helps utilize documents, Excel files, portals, and other external data sources as part of controlled data management, decision-making, and automation.
Less correcting. More reliable decision-making.
30–50% less manual work
Recurring checks, corrections, and data transfers are moved into a controlled and automated operating model.
Better data quality
Rules, validation, and approvals reduce the risk of incorrect data spreading across systems.
Faster and smoother processes
Data does not need to be searched for, checked, or corrected multiple times. Work progresses without unnecessary delays and bottlenecks.
More reliable decision-making
When data is consistent and up to date, decisions can be made faster and with greater confidence.
A stronger foundation for automation and AI
Automation and AI require reliable data. Data Control helps build a sustainable foundation for using them.
Ready to spend less time managing data and more time on your business?
Let’s start by identifying where data processing takes up the most time in your business.
Together, we will review where the most manual work, copying and pasting, data correction, and duplicate maintenance occur, as well as where better data management and more reliable data can deliver the greatest business benefits.
Data Control makes a difference in our customers' daily operations.
Lanttu.io's solutions have helped customers clarify data management, reduce manual work and build a more reliable foundation for their business.
Musti Group
Musti Group's customer story highlights the centralization of extensive data management and the streamlining of daily operations across multiple business processes.
Tamro
Tamro's customer story highlights the clarification of product information management and the importance of data quality in daily business operations.
Data no longer needs to be corrected one system at a time.
Most data quality issues arise when the same data exists in multiple locations without shared rules, responsibilities, or workflows.
Data Control brings data, workflows, and responsibilities together into one controlled framework. It makes data management part of the business process rather than a separate IT function.
A management layer, not a new system
Data Control operates on top of existing systems without a complex system renewal, data warehouse project, or new master data or PIM system.
One view for managing data, responsibilities, decisions, and traceability.
Business-driven data management
Consistent data accelerates decision-making, improves processes, and reduces uncertainty throughout the organization. Workflows, responsibilities, and rules are designed to support business processes, decision-making, and compliance requirements.
Automation, synchronization, and AI in one solution
Data is validated, enriched, and synchronized automatically. The same reliable data is available across systems, processes, and reports throughout the organization. AI can automatically complete and enrich data as part of the same workflows.
Manage all business data
Not all critical data is stored in an ERP system.
Data Control also helps manage documents, Excel files, portals, and other external data sources as part of the same framework.
Built-in auditability
All changes, approvals, and corrections are traceable.
A complete audit trail reduces risks and makes it easier to meet compliance, audit, and reporting requirements.
What does Data Control add on top of ERP?
ERP records business transactions. Data Control manages data.
It guides and ensures that data remains reliable at all times. Data Control manages data quality, workflows, responsibilities, and decisions across systems.
Stores data
Manages transactions
Displays data
Produces reports
Records changes
Manages a single system
Ensures data quality
Manages the data lifecycle
Validates, enriches, and synchronizes data
Ensures the reliability of reports
Provides an audit trail
Manages data across systems
A modern alternative to traditional MDM and PIM thinking
A new system
Centralized master data or product information
An IT-driven project
A long implementation
Focuses on structured data
A centralized data repository
Data maintenance
Centralized data management
For managing data
A management layer on top of existing systems
Operational data management across the entire business
A business-driven operating model
A lightweight and phased implementation
Also covers documents, Excel files, and external data sources
Data is managed where it is created and changed
Data maintenance, workflows, responsibilities, and decisions
Operational management
For decision-making, automation, and AI
Data Control does not replace ERP, CRM, or e-commerce systems. It adds a management layer between them, ensuring that data, responsibilities, and decisions work together as one integrated whole.
Ready to see Data Control in practice?
We show how better data management reduces manual work, accelerates decision-making, and supports automation without a complex MDM or PIM project.
Together, we will review where the most data corrections, copying and pasting, and duplicate maintenance occur, and how these can be reduced in your current operating environment.
Frequently Asked Questions
What is Data Control?
Data Control is an operational data management solution that brings data, workflows, responsibilities, and validation together into one controlled framework. It ensures that the same data is up to date, consistent, and available across all systems and for decision-making.
Does Data Control replace an ERP system?
No.
ERP manages business transactions such as orders, products, inventory, and invoicing.
Data Control complements ERP by managing data quality, workflows, approvals, responsibilities, synchronization, and traceability across systems.
Does Data Control replace an MDM or PIM solution?
In many cases, yes.
Most companies do not need a separate MDM or PIM system, but rather a better way to manage data within their current system environment.
Data Control provides a lighter and more business-driven alternative for situations where the goal is to improve data quality, reduce manual work, and manage workflows.
What types of data can Data Control manage?
Data Control is not limited to master data.
The solution can be used to manage, for example:
- Product data
- Customer data
- Supplier data
- Material data
- Price lists
- Documents
- Excel files
- Data obtained from portals
- Other external data sources
How does Data Control improve data quality?
Data Control automatically validates data against agreed rules, formats, and business requirements.
Incorrect or incomplete data can be automatically routed to the appropriate responsible persons for correction before it spreads across systems.
How does Data Control reduce manual work?
Recurring checks, approvals, data corrections, and synchronizations can be automated.
This frees experts from correcting data and allows them to focus on developing the business.
How is Data Control related to automation?
Automations require reliable data to function correctly.
Data Control ensures that the data used in automations is up to date, consistent, and validated.
Can Data Control use AI?
Yes.
Data Control can be integrated with AI solutions for purposes such as:
- Enriching product data
- Completing customer data
- Processing documents
- Classifying data
- Validating data
AI solutions benefit from using high-quality and well-managed data.
Is a new data warehouse required to implement Data Control?
Not necessarily.
Data Control operates on top of existing systems and uses existing data sources.
Can Data Control operate in a multi-system environment?
Yes.
Data Control is designed for situations where data is distributed across multiple systems, such as:
- ERP
- CRM
- PLM
- E-commerce
- Document management
- Files and Excel spreadsheets
How can changes be traced?
An audit trail can be recorded for all changes.
This makes it possible to see:
- Who made the change
- What was changed
- When the change was made
- Why the change was approved
Does Data Control support compliance requirements?
Yes.
Controlled workflows, approvals, responsibilities, and an audit trail help meet, for example:
- Quality management system requirements
- Audit requirements
- Internal control requirements
- Industry-specific compliance requirements
How quickly can Data Control be implemented?
Data Control can be implemented in phases.
Implementation can begin with a single process, data category, or business problem without extensive system renewals.
Who is Data Control suitable for?
Data Control is particularly suitable for companies where:
- The same data exists in multiple systems
- Data is maintained in Excel
- Data quality causes problems
- Manual work takes up a significant amount of time
- Decision-making is based on multiple data sources
- The use of automation or AI solutions needs to be expanded