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As a result of the rapid adoption of online technology over the last couple of years, there has been a dramatic increase in the sheer volume of data being produced and stored across all major industries. Data has grown in importance as a valuable corporate asset over the years to inform business decisions and optimize business operations
Managing company data used to just be about ensuring that the data was accurate and accessible when needed. Now, data management includes storing, organizing, managing, and securing a truly massive amount of data. Organizations must be able to quickly make sense of the information they gather in order to apply it meaningfully, but they also need to be able to protect these intellectual assets from costly cyberattacks. This rapid growth has driven the data management market to adapt by using tools such as artificial intelligence (AI) to improve operational efficiency that drives business value without sacrificing security.
1. The Costs of Data Loss and Inaccurate Data
Data breaches can result in sensitive company data being stolen, sold on the black market, held for ransom or even deliberately corrupted to intentionally slow down operations that result in lost revenue. However, companies can expect to pay more than just a ransom. Once valuable data is lost, all future forecasting models based on that data set will be inaccurate and will lead to poor decision-making in the long run.
The average total cost of a data breach reached a record-high $4.35 million in 2022, according to an IBM report. Businesses have reported $3 trillion in losses resulting from bad data every year. This astronomical number also accounts for lost productivity, maintenance costs, and system outages.
2. Regulatory Fines for Non-Compliance
Not only will there be upfront costs of repairing the data breach itself, but companies now face additional regulatory fines for failing to take adequate risk reduction steps to prevent such data losses from occurring in the first place. Any business collecting data from the European Union must comply with the General Data Protection Regulation (GDPR) and states such as California have their own consumer information protections outlined in the California Consumer Privacy Act (CCPA) that must also be followed to avoid incurring fines. European regulators issued €2.92 billion in fines in 2022 alone, indicating a 168% increase year-over-year.
Companies with sensitive personal data such as financial institutions can also be fined by the Securities and Exchange Commission for data security mismanagement. Recently, Chase was charged $125 million due to its insecure practices of allowing their employees to use their personal email and WhatsApp accounts to conduct official business, which is in violation of the SEC record-keeping requirements.
3. Legal Fees and the Court of Public Opinion
Companies need to emphasize proper data management because regulatory fines and fees for non-compliance do not preclude that company from other legal liabilities. Capital One had to pay out a class-action lawsuit of $190 million in response to a hack that leaked the personal data of 100 million of its customers in 2019.
Data breaches can have further ramifications for the company brand if consumers no longer trust that it can keep their personal data safe. It can be challenging to calculate the true price of losing the confidence of not only the consumer but subsequently, potential investors for other business opportunities.
4. Insurance Premium Hikes and Scarcity
Businesses that fail to take reasonable precautions to prevent a breach can even see their insurance premiums increase. Due to the overall rise in cyber threats, cyber insurance premiums have already increased by an average of 28% in the first quarter of 2022 compared to the last quarter of 2021. At this rate of increase, mistakes can be costly to a company’s bottom line and make it harder to qualify for insurance with decent coverage, as insurers have tightened up policy terms.
Data Management Best Practices
1. Artificial Intelligence
Improving data quality alone — or even the quantity of data — will not be enough to significantly boost company savings on data management. In fact, less than 0.5% of data is actually analyzed and used as a result of a lack of processing power, but this leaves room for potential — especially with the help of AI.
According to IBM’s Cost of a Data Breach Report from 2022, applying AI security and fully deployed automation services has led to an average of $3.05 million in cost savings per breach. AI provided the largest margin of cost savings in the entire study and decreased the average breach cost by 65.2%. Additionally, companies with AI reduced the time to identify and contain a breach by an average of 74 days which not only saves on downtime but frees up highly skilled employees for other tasks that drive value.
2. Employee Training and Security Awareness
Despite all of the promises of AI, companies should not ignore the human component of their labor force. Employee training and education play important roles in ensuring a dynamic data management strategy. This is especially true given that 19% of data breaches in IBM’s study were caused by stolen or compromised credentials, which can only be prevented by reviewing password hygiene protocols and other cybersecurity strategies with employees such as data encryption. Reviewing personal email practices with employees could have saved Chase $125 million dollars and could also prevent harmful phishing attacks.
3. Audit Data and Implement Adjustments
It will be important for companies to at least perform regular checks that their data is accurate and uncompromised, especially if they use the cloud. Performing consistent data audits are important for revealing informative patterns, but they are only useful if companies act on their findings and implement those changes in a reasonable amount of time — something AI can also help with. Purging irrelevant data can also help reduce what a company is liable for auditing and protecting overall.
Conclusion
These best practice are best put into practice with the help of a modern, cloud-based eDiscovery solution, such as Casepoint, which can provide corporations with advanced data management tools, harnessing the power of artificial intelligence and machine learning algorithms. This, in turn, offers a potent means of mitigating the risks arising from data mismanagement, given the ever-increasing amount of data being generated and stored by corporations.
With such solutions, corporations can expediently identify, collect, and analyze large volumes of data in response to legal requests, thus minimizing the potential for data breaches or non-compliance. Casepoint’s eDiscovery platform also provides comprehensive data security features to safeguard sensitive information throughout the legal process. Ultimately, eDiscovery solutions like Casepoint equip organizations with a robust toolbox to efficiently manage their data and minimize legal risks.
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