kamran sharief As companies continue to adopt data and analytics, there’s a need to address the operational facets of data management. More companies are finding ways to integrate business analytics into existing teams and brainstorming on ways to set up and maintain a data lake.
Surprisingly, only a few companies are addressing the ethical elements of data management. Ignoring this could lead to huge financial costs and reputational damage, which take time to rebuild.
What are ethics in business analytics, and why is it important to implement ethical data management? Find out more as we explore the ethical considerations businesses must consider when dealing with big data.
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What are ethics in business analytics?
Ethics in business analytics consist of data-related practices that aim to preserve the trust of employees, clients, partners, and users. Data ethics can also be defined as the complex ethical and moral issues related to data algorithms, data sharing, data recording, and data management.
Companies dealing with business analytics need to adhere to the principles that govern data protection laws.
Why are ethics in business analytics important?
Occasionally, organizations have to deal with ethical dilemmas when dealing with business analytics and data. Issues like data breaches can be costly and affect the company in multiple ways.
Here are some reasons why ethics in business analytics are important.
Gain the trust of stakeholders
Although having business analysts and other techies in your company can help ensure that data is ethically handled, every department must also understand the need to implement ethical practices when handling data.
When everyone in the organization adheres to high ethical standards, this assures the stakeholders and the top management that they can rely on the employees’ objectivity and integrity. Furthermore, stakeholders are likely to embrace other technological solutions that can help keep data safe.
It leads to better decision-making
Ethical businesses are more likely to avoid unintended bias that can negatively affect the company’s reputation and decision-making. Professionals who demonstrate fairness without bias can make better decisions that promote the company’s growth.
Compliance with data privacy regulations
Taking time to understand that data ethics revolves around consent, ownership of data, transparency, and data security as a business is crucial. It also allows you to comply with data privacy regulations like CCPA and GDPR.
Companies with a data ethics framework don’t have to worry about hefty fines as they have a system that governs how they collect, analyze, and use data.
Ethical considerations in business analytics
Ethical considerations in business analytics can help resolve most companies’ ethical predicaments. However, most companies need more analytics-qualified staff who combine their expertise with the ability to understand ethical considerations when engaging with business analytics. To reduce this gap, St. Bonaventure University offers an online business analytics masters course that equips students with practical skills in analytical models and an understanding of how organizations deal with ethical dilemmas when handling big data.
Some ethical considerations in business analytics include:
Confidentiality
Companies must have laws and regulations that protect their customer’s confidentiality. Customers engaging with your company have a right to expect that no personal data will be divulged or shared with third parties without their consent.
Protecting sensitive information can be achieved by obtaining informed consent from your clients. Companies must inform participants of the research’s purposes, the methodology they plan to use, and any risks they might encounter before collecting and analyzing their data.
Typical ways to get consent include signed written agreements and privacy policies requiring users to accept the stated terms and conditions. Checkboxes that track customer behavior through cookies are another way to obtain consent.
Getting consent from the participants ensures autonomy and helps them make informed decisions. A good example is when healthcare companies conduct research and collect data from multiple participants.
Companies must also anonymize data and adhere to data protection regulations like GDPR.
Preserving your customers’ information in a secure database and using tools like dual-authentication password protection can help safeguard privacy and confidentiality.
Transparency
Companies acquire data in different ways. Transparency is one ethical consideration companies must consider when gathering data. You need to inform your data subject about the methods you plan to use to collect data, store it, and use it to gather insights.
The first step is to create a policy that states how you track users’ activity and how that information is stored. You must also be transparent about how and why you use the data. For example, a financial institution collecting customers’ data regarding their credit habits can use the information to help them manage their credit. Having this in place allows the user to decide whether or not to accept the terms.
Data privacy
Data relating to customers and their identities need to remain private. While most people associate privacy with confidentiality, these two principles are different.
Depending on the legal requirements, companies may need to avail themselves of information for auditing purposes when dealing with business analytics. Nonetheless, firms need to protect the privacy of their customers by not sharing their information with third-party companies or individuals that could track their identity.
Industries like healthcare and finance store a lot of client data. They need to ensure that this private information remains private. Additionally, they must limit how acquired data can be shared for privacy concerns.
Data security
Data breaches were a huge concern in 2018. The Marriot Hotels hack affected half a billion people who had stayed at the hotel, Polar App exposed military and security personal information, and Facebook experienced a major data breach that affected at least 30 million users.
Data safety and security is an ethical consideration companies should not ignore. While big and small companies can leverage business analytics to collect and analyze personal data to draw useful insights, it’s also essential they ensure that the collected data is safe from unauthorized access, intrusion, and corruption.
Data interpretation and presentation
Data interpretation and presentation involve how information is analyzed and visualized, and the results communicated. Companies must determine how to avoid misrepresenting their data and acknowledging limitations in their results. Wrong data interpretation can lead to biased or false conclusions, damaging the company’s reputation and resulting in revenue losses.
Businesses must utilize quality business analytics tools, present accurate data visualizations, and report their insights honestly.
Bias and fairness
In business analytics, professionals will have to deal with conflicts of interest. Unfortunately, if not handled well, conflicts of interest can undermine the credibility of business analytics and lead to biases and unfairness.
For example, using algorithms that decide how to approve loans can cause bias against some people based on gender or race. Companies need to ascertain that their business analysis is unbiased.
Furthermore, data professionals must be honest about factors that could impact their analysis and interpretation of results. The systems need to be tested for fairness and bias to ensure there is no discrimination.
Being transparent about these issues helps build trust with stakeholders and ensures personal biases do not compromise findings. Additionally, when business analysts make recommendations based on the company’s best interests, it leads to more efficient technology solutions that correspond with the business goals and objectives.
Data governance
Data governance is the collection of policies, processes, roles, and standards that ensure the effective use of information. Businesses need to have data governance in place as it defines the processes that preserve the security and quality of data used.
With a data governance framework, an organization defines who can collect data, what actions they can take, the methods to use, and in what situations. Businesses get to define roles for people dealing with data clearly and agree on accountability and responsibility when handling data.
Compliance
Your business must comply with the set data laws and regulations governing data protection. That includes ensuring that all business analytics processes comply with GDPR, CCPA, GLBA, FERPA, and COPPA rules.
Data governance within your company ensures compliance with internal policies and industry regulations. Furthermore, companies need accountable leadership that enforces these laws and policies.
Sustainability
Are the insights you are gathering from the collected data sustainable over time? As a business, you should ensure that the insights you gain through data are viable over time. Business analysis that only addresses the present problems will have no purpose in the future.
Companies must invest in quality data that can provide useful insights in the present and into the future.
How can a business improve ethics in business analytics?
Companies in this digital age face complex ethical issues when collecting data, analyzing it, and ensuring full disclosure. Businesses can improve ethics by:
Establishing clear written policies that protect consumer data
As a business, you need to develop clear policies and procedures that state the type of data you collect, the amount of time you plan to keep the information, and the people who have access to this data. Furthermore, the policy needs to outline the steps you plan on taking when a data breach occurs and provide a channel for people to request deletion or access to their data.
Having that information in writing allows you to be transparent to your customers. It also encourages them to provide informed consent once they know why you are collecting their information and what you intend to use it for.
Have an ethical business analytics framework in place
Small and large corporations need to have an ethical business analytics framework that states the ethical principles and guidelines that govern them. The framework needs to outline how data collection, analysis, and interpretation are done within an analytic system to ensure that the system is used responsibly and ethically.
Continuously assessing and improving your ethical framework is essential as it reflects emerging ethical issues and recommends the best practices.
Incorporate data protection systems and mechanisms.
Prioritizing data privacy should be the goal of every company. Failure to protect your customer’s classified information can lead to a loss of trust and severe penalties. Furthermore, non-compliance also exposes businesses to revenue losses and business disruption.
Businesses must conduct data audits and risk assessments to spot potential risks and develop ways to mitigate them. They also need to invest in data protection mechanisms like encryption tools, cryptographic tools, data masking, and more to secure sensitive information. That will help safeguard people’s privacy and ensure businesses remain data-driven.
Include different perspectives
Ensuring equitability and inclusivity can help avoid biases and unfairness when dealing with data and analytics. Business analysts and other leaders must consider diverse perspectives from customers, employees, and other stakeholders when deciding to collect, analyze, and interpret data.
Ensure the ethical and responsible use of derived insights
Business analytics insights should not be used to trick consumers or violate their rights. Analytical insights are to give direction and enable companies to make informed decisions that align with the company’s values. Companies must advocate for the responsible and ethical use of analytics insights to establish trust and foster responsible data practices.
Collect the necessary data only
Collecting a lot of data was common until companies began to realize that the accumulation of data only exposed them to data breaches and compromised privacy.
Today’s organizations must focus on collecting only the necessary data to maintain ethical data practices.
Learn from your competitors
Taking time to study the ethical decisions made by your competitors allows you to understand how to navigate any ethical dilemma when dealing with data. Organizations may also need to hire ethical experts to advise on ethical considerations in business analytics.
Final thoughts
Ethical considerations in business analytics revolve around the responsible use of data. This includes obtaining consent, ensuring confidentiality, handling data safely, and being responsible for any actions taken due to data interpretation. Being accountable for any unfavorable outcomes and taking immediate action builds trust with your customers and stakeholders. Organizations that incorporate these practices can help ensure business analytics is used ethically.