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Navigating Privacy Compliance Challenges for Startup Success

Startups face unique challenges that can impact their success and sustainability. Obstacles such as financial constraints (inadequate funding or limited cash flow) and resource constraints often result in small teams having to do the jobs of many. Despite these challenges, startups should not ignore legal and compliance requirements. Companies should take the time to understand the risks and potential liabilities associated with the personal information they obtain on their customers, vendors, and employees. Non-compliance with regulations and laws can result in severe consequences for start-ups, including fines, lawsuits, and heightened scrutiny during their future acquirer’s due diligence process.

To mitigate these risks, startups should develop a comprehensive data privacy risk management strategy that prioritizes their highest data privacy compliance risks so that they can allocate their limited resources and funds appropriately across initiatives.   

What privacy compliance activities should startups prioritize?

1. Data Inventory of Personal Information

Creating a data inventory is a fundamental building block that supports an overall privacy program. A data inventory (a.k.a., register of processing activities) is a requirement of the GDPR under Article 30 and is needed to operationalize other regulatory requirements such as responding to data subject requests related to access, opting out, erasure and providing an accurate privacy notice prior to collection of personal information. The data inventory should document the flow of personal data through the processing life cycle, from initial collection and storage to the time when the personal data becomes obsolete or deleted. A privacy data inventory includes pertinent information on both assets and processing activities:

    • Assets – These consist primarily of software systems or databases where personal information is stored. This may also include things like systems, file shares, email systems, or any other “places” where personal information is stored.
    • Processing Activities – These consist of activities employees do or processes they support during which personal information is collected/used/processed/transferred/sold/etc. This may include activities like direct marketing, recruiting, managing benefits, and processing sales transactions. They always leverage at least one of the assets, often more than one.

2. Privacy by Design

  • Embed privacy considerations into the product development lifecycle. Incorporate privacy features and safeguards from the early stages to ensure that privacy is built into the product or service, rather than treated as an afterthought. This will prevent the need to make changes after the fact for a more efficient design process. Provide design and product teams with training and a procedure on how to properly implement privacy by design. At a minimum, guidelines should include the following requirements:
    • Implement and operationalize appropriate technical and organizational measures to protect users’ data.
    • Integrate data privacy safeguards to honor data subjects’ rights.
    • Process only as much data as is necessary for the initial purpose for which it was collected.
    • Store data only for as long as it is needed.
    • Limit access to personal information to only relevant personnel.
    • Consider the impact on the user when designing new products or services and ensure that an analysis is performed to consider the impact on the user versus the benefit of the processing.

3. Data Protection Impact Assessment (DPIA) and Privacy Impact Assessment (PIA)

  • Two essential risk assessment mechanisms that are required for the most active and emerging global privacy regulations are the DPIA and PIA. 
    • Data Protection Impact Assessment (DPIA): Required when carrying out high-risk processing activities (large-scale processing, sensitive data, automated decision-making or profiling, systematic monitoring of public areas on a large scale) to document and weigh the risks with consideration for impact to the data subject. A DPIA is required under the GDPR.
    • Privacy Impact Assessment (PIA): Required for projects that involve high-risk processing (sensitive data, targeted advertising, sale of personal information, certain profiling, high-risk of harm to data subjects) with heightened risk to the privacy of individuals. PIAs are required under a few of the current U.S. state privacy regulations and in some cases are required to be filed with a regulatory agency.

In conclusion, startups are no strangers to challenges, but those that neglect data privacy legal and compliance requirements are taking on risks that can be mitigated. By developing a comprehensive data privacy risk management strategy, startups can strike a balance between innovation and adherence to legal and compliance obligations, ensuring a smoother path to success and long-term sustainability.

© Copyright 2023. The views expressed herein are those of the author(s) and not necessarily the views of Ankura Consulting Group, LLC., its management, its subsidiaries, its affiliates, or its other professionals. Ankura is not a law firm and cannot provide legal advice.


compliance, data & technology, f-performance, data privacy & cyber risk, article

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