The tremendous value that data holds for organizations also comes with the responsibility to properly address its storage, governance, and security. How can businesses tackle this significant task? This article will review the top strategies.
Should you be concerned with having too much data? It is best not to focus on a single figure of data, to say that something is bad. The concern should be understanding the make-up of this data; how much data is sensitive, business-critical, and what proportion is redundant, obsolete, or trivial.
Over-retention of redundant data adds to the operational cost of data, and introduces risk—if you do not need it, why keep it? As a Data Processor or Controller, one should always understand where sensitive data is stored so that it can be processed within the confines of regulation and law.
“Knowing your data” is the key part in assessing when, where, and why content is processed. Understanding this will, in turn, help an organization to understand how much is too much — for example, over-retention of personally identifiable information (PII) or a high volume of intellectual property (IP) that is not adequately protected by security controls.
Understanding what data should be deleted is unique to every organization, and is determined by a combination of regulatory, judicial, and organizational requirements. An organization needs to ensure it understands the type of data it processes as part of its day-to-day operations and how to govern it through an effective Retention Schedule and Policy. An agreed Retention Schedule will identify the different types of content (physical, electronic) and classifications (PII, IP, financial, records) that apply to processed content and how it should be handled (for example, deleted after seven years). Organizations must appreciate that a one-size-fits-all method is not always appropriate, and that different types of content require discrete handling (for example, PII under General Data Protection Regulation (GDPR)).
Effective data retention not only improves regulatory compliance posture, but also enhances productivity by reducing data duplication and improving knowledge management. By systematically eliminating redundant, obsolete, trivial, and duplicated data, organizations can streamline their data storage, making it easier to locate and access relevant information.
However, not managing data effectively can lead to several significant risks for organizations:
- Data Leakage: Poor data management increases the risk of unauthorized access to inappropriately retained content. Breaches can result in significant financial losses, damage to reputation, and regulatory consequences.
- Compliance Violations: Failure to comply with data privacy and protection regulations such as GDPR can lead to substantial fines and legal penalties.
- Lost Productivity: Inefficient data management processes can waste valuable time and resources. An organization’s employees may spend excessive time searching for data, correcting errors, and dealing with data-related issues.
- Financial Loss: Data breaches and compliance violations can result in significant financial losses due to remediation costs, legal fees, and regulatory fines.
- Reputation Damage: Poor data management can damage an organization’s reputation, leading to a loss of customer trust and business opportunities.
It is highly recommended that organizations of any size in any sector develop a strategy for data lifecycle management. Partnering with business stakeholders is an intrinsic part of developing a retention schedule that represents the data map for the organization and provides governance over how it should be processed. IT alone cannot create such a policy. Once a robust documented policy is in place covering physical, digital, structured, and unstructured data, the next steps are to adopt a people, process, and technology-centric solution that enforces it.
In conclusion, a data management strategy is not just a regulatory necessity, but it is a strategic advantage. By partnering with key stakeholders to devise and adopt robust retention schedules and classification models, an organization can mitigate risks, enhance productivity, and ensure compliance. Effective data governance helps streamline operations, reduce costs, and protect sensitive information, ultimately fostering a more secure and efficient business environment. Embracing these strategies will enable organizations to harness the full potential of their data while safeguarding their reputation and resources.
About the Author
As the Head of Data Security at Quorum Cyber and an ex-Microsoft Technical Specialist, Leon Butler has spent over a decade as a technical SME, championing digital transformation through cloud services in sectors like manufacturing and finance. Leon specializes in guiding organizations towards robust regulatory compliance and information security. With an in-depth understanding of Microsoft 365’s security features and industry best practices, he oversees customer integrations and deployments. Leon can be reached online at [email protected] and at https://www.quorumcyber.com/
