Big Data and Business Ethics

Written by Liezl Groenewald

How did Walmart know to dispatch extra strawberry Pop Tarts to their stores in the path of Hurricane Sandy? How did public health officials gain an understanding of Ebola’s extent throughout the region? The short answer to these questions is: Big Data analytics.

I was recently fortunate enough to attend the European Business Ethics Forum (EBEF) in London.  EBEF brings together those who are responsible for the ethics, compliance or business conduct programmes in their organisations.  Participants share practical information and experiences relating to their programs and, through lively discourse, and explore together problems in the field of business ethics around the globe.

One of the themes that were discussed in both formal and informal settings was the question of Big Data and business ethics. A very relevant topic which I believe is not yet receiving the same attention in South Africa as seems to be the case in Europe.

Big Data

There might not be a universally accepted definition of Big Data, but the Institute of Business Ethics UK (IBE) states that the term generally “refers to the increased complexities in the use of data, and it can be described as the product of three elements[1].  These elements are:

Volume: a vast amount of data is generated every second (Google, for example, receives 4,000,000 search queries every minute of every day).

Variety: many different types of data are now available. New technologies can analyse data from different sources such as messages, video, photos and social media.

Velocity: the speed at which data is generated and circulated is accelerating.  In some cases, data is not even put into databases because technology can analyse data while it is being generated and circulated.”

The Internethas increased the sheer volume of data that is collected, the velocity of the process and the variety of sources. Everyday devices such as smartwatches and mobile phones that are connected use the internet to transmit, collect and analyse data.  Each of these actions leaves digital traces, which are aggregated to form the bulk of Big Data[2].   The data that is collected is often processed using algorithms that can identify useful patterns.

Big Data Application in Business

Big Data is big business, with forecasts that the Big Data technology market will grow at a 27% compound annual growth rate (CAGR) to $32.4 billion through 2017.[3]

As Big Data adoption continues to grow, it will become increasingly important to competitiveness for organisations.  Here are just two powerful Big Data application examples:

  • Fraud detection

For businesses whose operations involve any type of claims or transaction processing, fraud detection is one of the best Big Data application examples. Historically, fraud detection has proven difficult. In most cases, fraud is discovered long after the fact, at which point the damage has been done and all that is left is to minimise the harm and adjust policies to prevent it from happening again. Big Data platforms that can analyse claims and transactions in real time, identifying large-scale patterns across many transactions or detecting anomalous behaviour from an individual user, have changed the fraud detection arena.

  • Social media analysis

Everyone seems to be on social media, whether they are “liking” company pages on Facebook or tweeting on Twitter. Social media can provide real-time insights into how the market is responding to products and campaigns. With those insights, companies can adjust, for example, their pricing and promotions quickly.

Ethical Issues

But access to vast amounts of data presents new challenges that organisations need to consider in living up to their core ethical values and building public trust.  In discussions the IBE held with ethics practitioners the latter highlighted that organisations’ commitment to respect for personal information, to be open and transparent in their dealings, to be trustworthy, to behave with integrity and to treat customers fairly are all values that can find new applications in the era of Big Data. According to the IBE’s research[4], some specific issues that responsible businesses need to address to fulfil their duty of care towards stakeholders are:

Respect for personal information

One of the main ethical dilemmas organisations have to face is between collecting and using data to improve performance and their commitment to respect the privacy of stakeholders.  The Protection of Personal Information Act will go a long way in addressing this particular dilemma in South Africa.  But in a country with limited regulation and potentially weak government datasets could easily be acquired by companies with ethically questionable marketing strategies, or political groups wanting to target specific sets of people.

Informed consent and openness with information

The way in which consent to process personal information is obtained from users is another critical issue.  Traditionally explicit consent from respondents was required, but with the Internet, the border between what can be considered as informed consent has blurred.

Fair treatment of stakeholders and integrity of Big Data

Traditional statistical methodologies rely on representative samples of a whole population being analysed, but “the new datasets produced by Big Data may not be statistically accurate and can, therefore, produce flawed results”[5]. When the validity of a dataset cannot be guaranteed, noteworthy issues may arise.  According to the IBE’s research, this may lead to some individuals or groups accidentally being afforded “more visibility and thus be favoured, or discriminated against, at the expense of those less visible”[6].

Questions for Ethics Practitioners

During a workshop organised by the Royal Statistical Society in November 2015 to discuss the opportunities and ethics risks of Big Data, participants stressed the need for data governance to minimise harm and maximise benefits from the use of Big Data. They also emphasised the inclusion of considerations of risk and risk management.

According to the IBE, these observations highlight potential new opportunities for the Ethics Function in organisations, which could hold an oversight responsibility on the ethical aspects of Big Data collection and use.  Below follows some questions that the IBE proposes that Ethics Practitioners can ask themselves: [7]

  • “Do we know how the organisation uses Big Data and to what extent it is integrated into strategic planning?
  • Do we send a privacy note when we collect personal data?  Is it written in a clear and accessible language which allows users to give a truly informed consent?
  • Does my organisation assess the risks linked to Big Data?
  • Does my organisation have any safeguard mechanisms in place to mitigate these risks?
  • Do we make sure that the tools to manage these risks are effective and measure outcome?
  • Do we conduct appropriate due diligence when sharing or acquiring data from third parties?”


Organisations must realise that they have a responsibility to promote transparency and prevent the misuse of personal data. Questionable ethical conduct when dealing with Big Data can influence an organisation’s reputation, stakeholder relationships and revenues.  Care should also be taken not to create the perception of unethical handling of personal data as this can lead to diminished stakeholder trust and relationships.

It is incumbent on Ethics Practitioners to accept the additional responsibility of ensuring that their organisations have formal policies, systems and tools in place to mitigate ethics risks associated with their access to, and handling of, Big Data. At all times organisations must ensure that the latter is aligned with their core values.

[1]Business Ethics and Big Data, Business Ethics Briefing (52: June 2016), Institute of Business Ethics, pp 1-2

[2] Ibid.

[3] Five Facts About the Big Data Market You Must Take Seriously. [Accessed 13/02/2017]

[4] Business Ethics and Big Data, Business Ethics Briefing (52: June 2016), Institute of Business Ethics, p 3-4

[5] Ibid

[6] Ibid

[7] Ibid

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