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BLOG
TOP 4 CORPORATE DATA MANAGEMENT CHALLENGES
Karin Magness
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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.
Download “The Data Avalanche” whitepaper to get access to seven readiness steps
that you can take today to overcome your most complex eDiscovery data
challenges.
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