Data has become a ubiquitous feature of modern life. Until recently, consumers willingly exchanged their data for the free use of services, or for the benefit of receiving a more personalized digital experience.

But with the latest data breaches and misuse concerns, along with the new GDPR policy, the pendulum is swinging in favor of consumer privacy over convenience.

So now the question is: How do you ensure your methods for collecting, storing, and using data are clean and compliant?

A recent report from Accenture breaks down data ethics best practices into a supply chain framework. The report offers some valuable tips and advice on how to make sure the data you source is on the up and up.

See below:

  1. Obtain Meaningful Consent and Account for the Downstream Use of DatasetsAs data moves further down the supply chain, the scope of use can often go beyond the users’ original consent. Imagine, for example, a fitness company partnering with an insurance business, and bringing their customers’ data with them. Maximizing transparency at the point of data collection is essential, and can minimize the more significant risks down the line. Additionally, clear consent or opt-in is a key requirement for GDPR compliance in Europe.
  2. Prioritize Data Quality Over Quantity — Be wary of collecting data just for the sake of having more data — especially third-party data. The benefits of first-party data are numerous; not only does it provide the best path to truly understanding your customers, but it’s the only way to ensure compliance at the source. All data comes with liability, so consider the possibility that less data (ideally, first-party) may result in both better analysis and less risk in the long run.
  3. Account for Unfair BiasesConsider this: Even algorithms can absorb unconscious biases in a population and amplify them. Take the example of the smartphone app that monitors for potholes in the road by passively collecting accelerometer data. The first cities that deployed this technology to prioritize road maintenance saw wealthy communities receive the most attention — because those were the people with the most smartphones. Data professionals should strive to mitigate unfair biases and consider which ones might be unintentionally introduced through the procurement process.
  4. Repurposed Data Requires Special AttentionWhen sharing data with partners or third-parties, the first questions to ask are: 1) does the act of sharing or selling data enhance the experience for the data discloser? And 2) is there another way to share or sell this data that would increase transparency? In any case, data must be anonymized and aggregated prior to being shared. But most importantly, consent must have been obtained when the data was initially collected.

On top of these best practices, some companies have adopted the idea of creating a Data Code of Ethics, or even a ‘Hippocratic Oath’ for data scientists to take. More communication and transparency around ethical data use can never hurt, and you can expect to see more in the future.

Data discovery is more powerful than ever and, when used the right way, can improve individual lives and society as a whole. But to use and manage data ethically, you must go to the source — where consent happens. You can find more detailed guidelines and best practices on Data Ethics in the Digital Age in Accenture’s full report here.