What’s the best approach for ethical data use?
Data analytics is nothing new in the business world. The use of data has always been essential to gaining valuable insights that can drive greater actions across organizations.
With the proliferated growth of advanced capabilities to capture, process, analyze and contextualize data like artificial intelligence and the Internet of Things, companies are finding it easier to understand the markets they are serving and learn about their customers.
Plenty of companies have collected and used customer data to endorse improved marketing strategies, personalized experiences, and better product recommendations. However, as the world has recently learned from Cambridge Analytica and Facebook, companies can easily cross the line when it comes to the collection and use of data.
Here’s the thing, when it comes to customer data, it’s hard to separate what was lawfully collected from what was not. Multiple factors influence the distinction process including the context of collected data, methods used to obtain users’ consent, and the jurisdictional laws.
Google’s Street View data collection program where users’ online activities are captured is an example of how data practices can be unethical, but not illegal. According to the jurisdictions they fall under, they were simply collecting data.
In many of these malpractice scenarios, it is easy to tell whether the company is being ethical or abusing their power. So it all boils down to the question; just because a company can, does it mean it should?
Drawing the line
Plenty of other businesses across the industries maintain a clean record when it comes to data practice – and these are companies that are highly data-driven and rely heavily on analytics, so companies are not bound to cross the line just because they can.
Being compliant is as easy as straightforward as following rules of conduct as laid out by regulatory bodies, but being ethical means companies should take note of how to employ a transparent, accountable, and calculative approach.
First off, companies need to make sure that they remain transparent with customers about the kind of data they are collecting, the way their data are captured, the purpose of the collection and how the data will be used.
This is one definite way to build trust and ensure that the value proposition behind is clearly communicated. Customers should be made to understand that sharing some of their personal data will benefit them and the company in the long run.
Being up open and honest
Next, companies need to assure customers that they will take accountability over the collected data by devising relevant recovery and security policies. This will come into play in the case of data breaches and cyberattacks.
It should also be communicated effectively across the organization that customer data has to be protected effectively, and utilized in a up-front, non-deceptive way.
Lastly, companies also need to be calculative when deciding on the amount and types of customer data they wish to capture, focusing only on collecting the data that they will use and will provide value to both the company and the customer.
Of course, there are laws and regulations being issued all over the world to guide companies, protect customers and penalize abusers, but companies should not wait for official rulings to start being ethical.
After all, these rulings may not come into effect as quickly as customers would hope and in the face of intensifying awareness over data privacy and misconduct, it is the companies’ responsibility to reassure that they will handle customers’ personal data morally.
In turn, they will be rewarded with customers that trust the business, and benefit from the value their personal data provides.