Have a policy
First and foremost, there must be a comprehensive and well-understood policy regarding data ethics for the organisation. This can vary from business to business based on the use and collection of data, but the core concepts remain the same:
- Ownership
- Transparency
- Privacy
- Intention
- Outcomes
Make sure that the business decision makers agree and understand the data ethics policy and appreciate why it must be upheld. It is not just a piece of paper to have in a folder to be pulled out when needed, it is a cornerstone of developing a solid and functional data culture within an organisation. Data culture takes time to build and grow, and an easily accessible data ethics policy, alongside regular use of data ethics and best practice, makes developing data culture smoother. Embedding data ethics into governance processes and organisational culture builds trust and manages risk, which are imperative for growth and success in the long term.
To make a data ethics policy, a data team needs to:
- Develop a risk framework
- Prioritise communication
- Utilise the correct tools
When developing a framework, some organisations create a cross-functional data ethics committee. This committee is then tasked with developing, publishing and upholding the data risk framework. This in turn develops communications across the organisation related to data ethics and improves the standing of the data team within a business, leading into the second point: communication.
Data leaders need to lead the conversations and be an example of good data ethics usage which can be achieved through regular interactions with different business areas and soliciting feedback. Make sure there are regular points of contact for different teams (depending on the size of the organisation) to discuss data and any pain points they may be experiencing regarding data ethics.
Finally, the tools being used must be suitable for the data needs of the organisation. This requires research and investment into finding the best solution for the problems at hand. There are multiple tools and variations of technology that can assist in different data functions, but to ensure the best ethical data function the tools must be accurate for the individual needs of the business. There must be a catalogue of volumes and types of data used, data lineage that shows visibility and transparency into the flow of data, tools identifying sensitive data storage and use, data governance processes, ownership and overviews of the data ethics standards that have been agreed.
Train the policy
Education is the answer to a lot of problems in the data and analytics industry, particularly for those that do not have a data-centric job function or business decision makers that have not experienced data-led business intelligence previously. The downside is that training does require resources such as financial backing and time, but the investment is a fraction of the potential outcomes from a deeply entrenched data culture with rich data ethic practices.
Once training has been completed, participants should be:
- Aware of the potential harms that arise from data collection, use and sharing.
- Able to critically think about data ethics within the context of their business needs.
- Knowledgeable of tools and techniques that benefit ethical data use.
- Able to highlight potential risks through the further development of data use in a business.
- Confident to help others in the practical steps of undertaking data ethics.
Data ethics is constantly evolving alongside burgeoning businesses, which means regular training is required to ensure new hires can match the data culture and ethical understanding of longer service staff, any new developments to the data ethics policy are embraced and new tools designed to improve data operations are used effectively.
Review the policy and train again
This cannot be overstated enough: regularly review the data ethics policy and train team members in new developments. Data tools and techniques are constantly evolving – the tools and practices that were commonplace just ten years ago are eons behind the latest developments and capabilities, and this will likely happen in the future too.
In the same way that there needs to be regular housekeeping when it comes to data literacy capabilities, data ethics knowledge and training must also be maintained, monitored and re-evaluated regularly to ensure the highest levels of quality. This can be achieved through strong communication with different areas of the organisation, requesting feedback on data capabilities and regular questionnaires.
There must be a level of granularity when training new team members in data ethics, and training must be completed before anyone is let loose on raw data to ensure a high degree of compliance, quality and correct use of said data. Once a comprehensive understanding of the data ethics policy and correct use is a natural part of the wider data culture, ensuring the correct use of data ethics will become an easier task. Education is the key, and following education the correct ethical processes need to be cemented into day-to-day operations.
