File Retention and Disposal Policies

Risk Scenario 5: Poor Data Retention Practices 1. Identification of Risks: • Scenario: An organization retains personal data longer than necessary, leading to increased risks of data breaches and non-compliance with data protection laws. • Regulatory Requirements: GDPR, PDPL, and other data protection laws mandate that personal data should only be retained for as long as necessary for the purposes for which it was collected. • Internal Audits: Audits often uncover excessive data retention, highlighting the need for better data management. • Stakeholder Feedback: Concerns from stakeholders about data privacy and the potential misuse of outdated information emphasize the need for strict data retention policies. 2. Assessment of Risks: • Likelihood: High, as many organizations lack clear data retention policies. • Impact: Severe, since retaining data longer than necessary increases the risk of data breaches and regulatory fines. 3. Mitigation of Risks: • Data Retention Policy: Develop and implement a clear data retention policy that specifies retention periods for different types of data. • Regular Data Purges: Schedule regular data purges to delete data that is no longer necessary. • Automated Tools: Utilize automated tools to manage data retention and deletion processes. • Employee Training: Educate employees on the importance of data retention policies and how to comply with them. 4. Recommendations: • Policy Updates: Update data protection policies to include specific data retention guidelines. • Monitoring and Auditing: Regularly monitor and audit data retention practices to ensure compliance. • Stakeholder Communication: Communicate data retention practices clearly to stakeholders to build trust and transparency. By addressing poor data retention practices through identification, assessment, and mitigation, organizations can reduce the risk of data breaches, ensure compliance with legal requirements, and maintain the trust of their stakeholders.

Information Handling Policies, Procedures, and Standards 1. Information Handling Policies These policies establish the overarching principles and guidelines that govern how an organization should handle its data. Objectives Data Classification: Information handling policies classify data based on sensitivity, defining how different types of data should be treated. Access Control: Policies outline who has access to specific data and under what conditions, ensuring that data is only available to authorized personnel. Data Encryption: Policies specify when and how data should be encrypted to protect it from unauthorized access. User Responsibilities: They define the responsibilities of employees and other stakeholders in safeguarding data and maintaining cybersecurity best practices. Incident Response: Information handling policies establish procedures for handling data breaches or security incidents, ensuring a swift and coordinated response. 2. Information Handling Procedures While information handling policies set the rules, procedures operationalize them. Procedures are detailed, step-by-step instructions that provide guidance on how to implement the policies in practice. Key components Data Access: Procedures detail how employees can access data based on their roles, authentication mechanisms, and access control measures. Data Transfer: They specify how data should be securely transferred within and outside the organization, including encryption and secure channels. Data Backup and Recovery: Procedures outline how data should be regularly backed up and the steps to recover data in case of loss or corruption. Incident Response: Procedures provide guidance on what actions to take when a security incident occurs, ensuring a coordinated and effective response. Data Destruction: Proper procedures for securely disposing of data, ensuring it cannot be retrieved after disposal. 3. Information Handling Standards Information handling standards, on the other hand, provide a detailed technical blueprint for implementing the policies and procedures. They establish the specific technologies, configurations, and practices that ensure compliance with the policies and successful execution of procedures. Key aspects Encryption Standards: Specifying encryption algorithms, key management, and encryption protocols to protect data in transit and at rest. Access Control Standards: Defining authentication methods, authorization mechanisms, and user privileges that ensure data access is restricted to authorized users. Data Backup Standards: Outlining how data backups should be performed, frequency, retention policies, and data restoration standards. Network Security Standards: Defining best practices for network security, firewall configurations, intrusion detection systems and network segmentation. Data Retention Standards: Determining how long data should be retained and when it should be securely disposed of.

Do you (crypto) shred? I’m not talking about on the slopes But rather about destroying sensitive info once you don’t need it anymore. While the collapsing costs of cloud storage have made it economical for many businesses to indefinitely retain every piece of information they have ever captured, this might not be the best move from a privacy or security perspective. Some steps you can take include: 1/ Specifying data retention policies. Understanding how long you need to keep records for both business and regulatory purposes should drive your decision-making here. Consult with legal counsel and business leaders to determine your requirements. These can help you to draft a policy based on type of record and source of information. 2/ Automating data destruction. Automatically enforcing your retention timelines is a best practice. Instead of relying on manual efforts to destroy information - especially of the personal kind - the easiest and most secure option is to set auto-deletion timers using enterprise software tools. Google Workspace, for example, allows setting customized retention timelines. 3/ Using cryptoshredding when storing with third parties. Whenever you provide data to another organization, you can never be sure as to how it is handled or whether all copies will be deleted per your requirements. An effective way to mitigate this risk is called cryptoshredding. If you are able to manage the encryption keys for the data stored with another provider, simply deleting these keys at the end of the retention period can greatly reduce the likelihood of anyone accessing this data in the future. What are some other methods of data destruction that can help to reduce privacy and compliance risk? #privacy #compliance #riskmanagement #crypto #cryptoshredding

📂 Data Retention Policy: From PDF to Automated Enforcement ⚙️ Here’s a hard truth: most organizations still treat their data retention policy as a static PDF—something to hand auditors, not something that actually drives behavior. But in 2025, that approach is a liability: 🔎 67% of companies admit they don’t consistently apply their data retention rules across systems (source: Ponemon Institute). 💸 The average cost of failing to delete data when required? $4.45M in regulatory fines and legal exposure (IBM 2023 Cost of a Data Breach Report). 🗑️ 40% of stored data is “dark”—nobody knows why it’s being kept, which inflates storage costs and risk (IDC). Here’s the shift forward: ✅ Moving from “policy on paper” → to policy as code. ✅ Embedding retention rules directly into data platforms, file storage, and SaaS apps. ✅ Automating deletion, archiving, and reporting—so compliance isn’t a manual checkbox, it’s a living system. The benefits are real: • Lower storage costs • Reduced breach impact (less data = less risk) • Faster, cleaner audits • Stronger trust with regulators and customers ✨ Think of it this way: a PDF tells people what they should do. Automated enforcement ensures it actually gets done. 👥 Curious to hear from you: Has your organization moved beyond the PDF? What’s worked—or what’s been the biggest blocker? Let’s swap lessons. This is one area where automation pays for itself. #DataGovernance #Compliance #Cybersecurity #RiskManagement #Automation

🔵 DATA POLICIES IN S/4 HANA: THE FOUNDATION FOR TRUSTED, SECURE, AND COMPLIANT DATA In today’s data-driven world, enterprises running SAP S/4 HANA face mounting pressures to manage massive data volumes, enforce compliance mandates, and ensure data quality across every business process. A robust set of data policies is the linchpin that transforms raw information into a strategic asset—fueling insights, mitigating risk, and unlocking operational excellence. 🔶 WHAT ARE DATA POLICIES? 🔹 Formal guidelines, rules, and standards governing the creation, storage, usage, retention, and disposal of enterprise data in S/4 HANA. 🔹 Cover domains such as data quality, security, privacy, classification, and lifecycle management. 🔹 Ensure consistency, traceability, and accountability across organizational roles and systems. 🔶 CORE POLICY DOMAINS 🔹 Data Quality & Integrity – rules for validation, enrichment, and cleansing 🔹 Data Privacy & Protection – GDPR, CCPA, and regional compliance controls 🔹 Data Classification & Labeling – sensitivity tags, usage restrictions 🔹 Data Retention & Archival – retention periods, archival procedures, and secure disposal 🔹 Master Data Governance – standards for product, customer, vendor, and financial master records 🔹 Audit & Compliance – logging, monitoring, and reporting requirements 🔶 BEST PRACTICES FOR S/4 HANA DATA POLICIES 🔸 Align Policies with Business Objectives Ensure every policy maps back to revenue drivers, cost savings, or risk mitigation goals. 🔸 Embed Policy Enforcement in S/4 HANA Leverage SAP Information Steward, Data Quality Management, and Fiori apps for real-time checks. 🔸 Automate & Integrate Use ABAP or SAP Workflow to automate validations, notifications, and exception handling. 🔸 Stakeholder Collaboration Engage business SMEs, IT architects, data stewards, and compliance teams early and often. 🔸 Continuous Improvement Institute regular policy reviews tied to audit findings, process changes, and technology upgrades. 🔶 ROLES & RESPONSIBILITIES 🔹 Data Owners – Define policy scope, approve standards, measure compliance 🔹 Data Stewards – Implement rules, manage exceptions, drive remediation 🔹 Solution Architects – Configure S/4 HANA modules, integrate enforcement tools 🔹 Compliance Officers – Audit adherence, steer regulatory updates 🔹 End Users – Follow guidelines, report anomalies 🔶 IMPLEMENTATION ROADMAP 1️⃣ Assessment & Blueprint – Catalog data domains, map to regulatory and business needs 2️⃣ Policy Design & Approval – Draft standards, secure executive sign-off 3️⃣ Technical Enablement – Configure SAP tools, build workflows, set up dashboards 4️⃣ Pilot & Rollout – Start with critical processes, iterate based on feedback 5️⃣ Monitoring & Governance – Track KPIs, refine policies, train users Share your challenges, wins, or questions below. 👇 #S4HANA #DataGovernance #DataPolicy #SAP #MasterDataManagement #Compliance #DigitalTransformation