Data collection, storage and analysis have a wide range of business applications, from sales and marketing to business operations and strategic partnerships. As data collection and warehousing technologies improve, businesses amass ever-increasing amounts of personal information about customers. This information collection, however, brings increased concerns about privacy, the transformation of raw data into useful information and the misuse of data.
As data leaders navigate today’s contentious legal and financial environment, they face ethical challenges. Data mining has become synonymous with exploiting customers for profit. Consumer awareness has resulted in new laws emerging worldwide, such as sector-specific laws in the U.S. and the General Data Protection Regulation (GDPR) in Europe, the most stringent privacy law in the world.
Businesses may, however, follow existing laws while crossing ethical boundaries. To establish a consensus set of ethical practices, laws alone are insufficient. Business schools and industry leaders are responsible for adhering to ethical behaviors. Analytics professionals learn about ethical best practices in programs like the online Master of Business Administration (MBA) in Business Analytics from the University of Illinois Springfield (UIS).
Ethical Concerns for Analytics Professionals
To aid a company in collecting and using data judiciously, there are several principles professionals need to learn. The UIS program curriculum, in courses like Management of Database Systems and Data Mining for Business Analytics, emphasizes these principles and more:
- Ownership, transparency and consent: Businesses must abide by laws that say individuals own their personal data. They must also meet customers’ reasonable expectations for visibility into and control over how their data is collected and used. Companies should be transparent about their practices and must ask permission through disclosures before using data. They should ask customers to explicitly consent to certain practices rather than simply opt in or out.
- Personal data: The U.S. has no current legal standard, as of 2022, for what is considered personal data — though courts have found that items linked to individuals’ identities, such as social security and credit card numbers, must be protected. Sector-specific regulations and company-held beliefs are the de-facto standards, which makes transparency even more important. Customers should understand how the companies that collect and use data define personal data.
- Privacy: With the power to collect data comes the responsibility to ensure it is not made available to outside parties without consent and does not fall into criminal hands. Companies must use up-to-date data security methods, including de-identified datasets, dual-authentication password protection and file encryption.
- Governance and compliance: In the EU, the GDPR offers a comprehensive legal framework for data practices. In the U.S. currently, where there is no national legal framework, so data governance within companies to ensure compliance with industry regulations and internal policies is imperative. There must be accountable leadership responsible for policies and enforcement.
- Intention and outcomes: It is ethical to collect data when customers or applicants would approve its use, which relates to data transparency. Data should not be used to profit from the weaknesses of individuals or any other ill-intentioned objective. However, even good intentions can lead to disparate impacts, deemed unlawful in the Civil Rights Act. Certain misuses of data and algorithms can result in disproportionately negative effects on specific groups of people and the companies that engage in such practices can be liable.
- Bias in algorithms: Because fallible humans write algorithms, unintentional biases can make data harmful. This can happen due to code written deliberately to produce biased results, the influence of biased feedback from certain populations or poorly developed code.
Five Best Practices to Ensure Integrity
Data collection and analysis leaders must develop formal policies within their organizations and best practices for implementing those policies to avoid data negligence or outright data crimes. Many business leaders work with leading academic institutions to promote best practices in training and education. These are a few examples of best practices common to corporate exemplars of data ethics:
- Develop a company culture of data integrity led by a data ethics board. This cross-functional group should have representation from each business function and level of leadership and should develop and evolve a comprehensive set of policies and best practices.
- Develop a consumer culture of informed consent. Aim to be one of the most transparent organizations in your sector by clearly explaining your data collection practices, purposes and risks before you collect the data. Allow consumers to give informed consent before proceeding.
- Study the ethical decisions made by competitors. Industry best practices are advanced when leaders from different companies within a sector communicate with one another through professional organizations and advance data practices by sharing what they have learned.
- Never misrepresent, misinterpret, change, embellish or lie about data. Ensure that data practices result in letting the data tell the story, even when that story is not what the collectors or analysts expect.
- Conduct extensive vetting for additional data usage beyond the purposes of the original data collection. For example, universities can collect data from applicants that allow them to identify candidates with a predisposition to making later donations, but that should not be a prerequisite for university admission.
UIS has worked extensively with leading employers to help train professionals who can meet the highest standards of ethical practices. Graduates of the online MBA in Business Analytics program confirm the institution’s reputation for integrity, which shows in the high demand for graduates among employers in Illinois and throughout the region.
Learn more about the University of Illinois Springfield’s online MBA in Business Analytics program.
