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Enterprise Resources Planning (ERP) systems are the backbone of modern enterprises, driving automation, intelligence, and efficiency. While organizations embrace ERP transformation on their way to intelligent enterprise, one critical aspect receives less attention but is equally crucial to the process, which is to ensure data security, confidentiality, and privacy.
To realize the full benefits of digital transformation, enterprises must embed security as a core consideration from the outset. This article dives into common data security challenges along digital transformation and provides solutions and use cases to demonstrate how embedding Zero Trust and data-centric security enables organizations to overcome these challenges.
Common Challenges in ERP Transformation
Organizations face multiple security challenges during ERP consolidation:
- Data Privacy & Compliance with global regulations like GDPR, CCPA, HIPAA, and ITAR.
- Insider Threats & Data Leakage, where authorized users may misuse sensitive data.
- Single Global Instance Risks, requiring strict need-to-know access controls.
- Complex Data Governance & Management across vast and diverse datasets.
- Collaboration & Data Sharing Needs with external partners while protecting confidentiality.
Viewing from a more systematic perspective, these challenges increase the risks in multiple cross-functional business areas impacted in an ERP transformation:
- Procure to Pay – securing vendor information, transfer pricing, and segregation during divestitures.
- Plan to Produce – protecting bill of materials (BOM), designs, and sensitive production data.
- Record to Report – ensuring financial data integrity, sensitive pricing protection, and compliance with reporting standards.
Strategy to Enable Data Security, Confidentiality & Privacy
Data consolidation is a common practice in ERP transformation that increases efficiency, cuts cost and empowers decision making. Yet, bringing sensitive data into a single instance highlights the need for fine-grained access controls, logical data segregation, and real-time enforcement to prevent unauthorized access to sensitive data. A solution to the challenges to safeguard data security, confidentiality, and privacy is to implement a policy platform that combines zero trust principles with contextual attributes and dynamic authorizations, along with logical data segregation and obfuscation. Specific techniques in organizations depend on the nature of data and organizational demand, but here are some commonly used techniques:
- Data Segmentation – logically partitioning data by attributes such as geography and sensitivity.
- Data Filtering – controlling visibility at row, column, or attribute levels.
- Data Masking – obfuscating sensitive fields while preserving usability.
- Attribute-Based Access Control (ABAC) – enforcing dynamic, least-privilege access.
- Digital Rights Management (DRM) – applying persistent protection to data throughout its lifecycle.
Real-World Use Cases Covered
- Export Control Compliance (Plan to Produce): Dynamic data masking and filtering protect BOMs from unauthorized disclosure, ensuring compliance with ITAR and similar export regulations.
- SOX & Segregation of Duties (Record to Report): Real-time ABAC policies prevent unauthorized financial transactions, reducing fraud risk and meeting regulatory requirements.
Summary
By pairing Zero Trust authorization platforms with logical data segregation and dynamic enforcement, organizations are able to achieve efficient data management and safeguard their consolidated ERP data. Continuous protection over data security, confidentiality, and privacy not only maintains trust with stakeholders, but also enables secure collaboration and business agility in the long run.
If you are interested in learning more details about the solution and its real-world use cases, read the White Paper in full length: Ensuring Data Security, Confidentiality, and Privacy for ERP Transformations
