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Chapter 7 | Data Supply Chain Guidebook

Share, Sell or Network

The million-dollar question: Can we ethically share or sell data?

How do you provide access to datasets—or insights from those datasets, which are not the same thing—to other people, organizations, or systems?


Example

The manufacturer sells data or insights to vehicle-makers, map services, and regulators

In our automotive data supply chain example, the vehicle maker might make subsets of their data, or data-derived insights like "these are the parts of the city that have a lot of traffic," to other manufacturers, map services, or even regulators. This creates a feedback loop to influence the world around us.

However, sharing and selling data is the stuff of headlines for a reason: if our driving data tells someone exactly where and when we drive, do we want that shared with anyone else?

Sharing data with the discloser

Many business leaders are trained to look at using data for their company's benefit. This does not necessarily lead to the best uses of data, however. If we think about our customers as family and friends, we don't want big companies to use their data for their selfish purposes. Why would we bother sharing sensitive information about ourselves, or allow ourselves to be tracked, just to sell us more stuff?

Ask not what data can do for you, but what data can do for your users.

Instead of starting with data use cases for your business needs, ask what data could do to help your customers achieve their own goals.

For example, Apple uses sensors in their Apple Watch device to help users understand more about their bodies. If you have to choose between sharing data to help a business and sharing data to help yourself, which would you choose?

Consider your users' desires: How can data help your users do something that already matters to them?

For example, we all need to organize our time. Apple and Google help users understand how much time it takes to get from one location to another by predicting the travel time between events in their calendars. This incentivizes users to list the location of their events in their calendar. Users wouldn't bother to add location information if they didn't trust that they would get more value from putting in the effort and that their privacy would be respected.

Sharing data externally

Data can be shared with third parties for several reasons, among them:

  • Sharing to improve quality, as a customer service call center might share recordings to receive coaching for its staff
  • Sharing to deliver a service, as a personal budgeting app might share account numbers with a bank in order to import transactions
  • Sharing to provide insight, as a research app might share citations with a search engine to find related content

Selling data

Data can be sold in a number of forms, whether as raw data, processed data, or as insights from data. You can find more information about positive models for monetizing data in our guide Creating Value with Data.


Ethical considerations when selling data

Consider whether you're selling data to a party your company knows and/or has control over vs. selling data in an open marketplace. Both options require careful review and structuring of agreements, especially if you don't have unlimited rights to the data you are selling, such as personally identifying information. It's very easy to harm people through data sharing and sales: one seemingly anonymous record could complete a piece of a data puzzle for bad actors, revealing an individual's identity.

There are also risks of security breaches resulting in identity theft, fraud, and other negative consequences for the original data disclosers—not to mention outcomes from poorly-analyzed data (such as bad credit-scoring algorithms).

Additionally, data about specific users falls under an increasing number of regulations regarding individuals' rights, national security interests, and 'data sovereignty.' Mere checkbox-style consent from an individual does not meet modern standards of informed consent or data use scope control expected by current laws. You can learn more in our guide to Data Ethics and Data Politics.

Read about some of the many methods of data monetization here

Read More

Discussion Prompts

Will you share or sell any data to other parties?

Will you share your analyses back to the source of the data?

Can we ethically share or sell data?

How do you provide access to datasets—or the insights from those data sets, which are not the same thing—to other people, organizations or systems?

Exercise

A lot of the most valuable data we can collect is from and about people. But that data isn't just valuable for companies and organizations—it can also be useful for the people who generated it.

Think of a few types of data your organization has access to about its customers. For each data type, answer these questions:

  • Can this data teach customers something about themselves that's useful to them? If so, what?
  • Would you need to analyze or aggregate the data to make it useful for customers?
  • Are there any ethical considerations that would need to be addressed before sharing this data with customers?

Recap

  • There are many ways to share or sell data outside an organization
  • It's important to consider how you can share data back to its source—the users or organizations who furnished it to you—to create value and relationship
  • There are many ethical considerations when sharing or selling data, as well as laws and regulations to be respected

Discussion Prompts

  • Will you share or sell any data to other parties?
  • Will you share your analyses back to the source of the data?
  • Can we ethically share or sell data?
  • How do you provide access to datasets—or the insights from those data sets, which are not the same thing—to other people, organizations or systems?