A New Digital Data Governance Framework To Ward Off Challenges Around Data

The global economy was undergoing a digital transformation; as the COVID pandemic arrived, the transformation accelerated at a breakneck speed. Moreover, the global digital economy is expected to reach $23 trillion by 2025, as per the joint report from Oxford Economics and Huawei. What do I mean by digital economy???

Simply put, the digital economy is driven by the billions of daily online interactions between individuals, businesses, devices, and processes. And, it is the 'data' or the new oil that lies at the heart of this transformation or say data is now a matter of life and death for modern businesses.?

So, what businesses are up to?

To gain the lion's share of the digital economy value, businesses, from small-size to tech behemoths including Google and Facebook, routinely collect, store, and analyze vast volumes of data about their customer base every day and offers to partners and advertisers to understand consumer behavior and perform predictive analytics. But where does the data come from? It can either be,

• Internal data: The data a company collects from its audiences via their website visits, email subscriptions, ad clicks, surveys, consumers using products, social media followers etc.
• External data: The data collected from a different entity unrelated to a company's relationship with its audience. Take, for example, companies like Acxiom and Dun & Bradstreet, which aggregate, organize and sell data from multiple sources.?

It may be debatable whether they sell or give away user data. Still, they do keep track of individual users' personal information, including their basic demographics, parental status, household income, friends, location, likes, dislikes, and the kinds of pages, groups, and articles they connect with.?

This business of digital data needs a check?

Even though some businesses are transparent about their data practices, most prefer to hide this information from customers, opt to control sharing, and solicit forgiveness rather than permission. Additionally, it's fairly uncommon for businesses to secretly gather personal information for which they have no immediate purpose in the hopes that it will prove useful in the future.?

Additionally, any company that shares consumer data must take reasonable measures to ensure the recipient utilizes the information for what it is intended. In essence, this entails coming to a consensus over the uses of the data that the recipient is permitted to make. The time is high for businesses to understand that besides improving their customer engagement, they are responsible for keeping consumers' data safe.???

The Solution

Today, the world generates 2.5 quintillion bytes of data per day. An active and warranted concern around misuse of consumers' personal data gave rise to newer privacy regulations like the European Union's General Data Protection Regulation (GDPR) and California's Consumer Privacy Act (CCPA) limit data use and seek to give power back to the consumer.?

Digital data is high in volume, unregulated, and unstructured, making it difficult to manage and govern. Hence, I have come up with a new Digital Data Governance Framework - SPrEAD for businesses to ward off data concerns in the very first place. Without wasting time, let's dive deep into the framework,

Framework Copyright: @Gunjan Aggarwal (2) Gunjan Aggarwal | LinkedIn

Sourcing: The very first aspect for a company to consider before buying any digital or third-party consumer data is knowing how the data is sourced and if the consumers hold control of their data. Say, for example,

• Is it clear to consumers how their data is collected?
• Are consumers able to opt-out of data collection?
• Can consumers ask questions about the data policies?
• Can consumers request copies or deletion of their data?
• Are the purposes of data collection defined and clear to consumers?

Procurement: As procurement processes involve interactions with partners and data suppliers, one should insist on the same high standards, just like the one, to ensure that employees follow the company's compliance requirements. Examine whether the ethical concerns around data collection and usage are taken care of, filter out the unethical components, and look if the data seller adheres to the company's policies and is compliant with the standards. This sometimes may call for regular audits.?

Enablement: Third, there should be a clear order of operations to enable digital datasets. At this stage, it is vital to look for,?

• Is my data accurate, complete and up to date?
• Assessing the quality of data?
• How should governance processes differ for digital data??

The roles and responsibilities to enable insights out of data should be properly laid out in advance, with clear roles and responsibilities for data teams.?

Access: Once the data is ready and collected from different sources, it is generally stored in data warehouses. Now, a pertinent question arises - Who should all be given access to data and to what extent. The case of accessibility needs a three-step solution. First, companies should lay out a consolidated and transparent process for users to access data; second, proper training and policy acknowledgement should be there; and third, define the boundaries of the use of data.??

Distribution: In the final step, the downstream approach needs to be adopted, that is, data transmission to an end user from the central server. This ensures the transmission of only those datasets required to carry out a particular task, rather than flooding the entire cache of data to every employee, which is risky.?

To sum up, the digitization momentum is not expected to slow down and will spread over. As a result, the amount of consumer data available is going to explode. This calls for laying down an innovative and robust digital data governance framework to strike a balance between business growth and consumers' right to privacy.?