This chapter provides an overview from DAMA-DMBOK2 on data governance (excerpted from pages 67-74), and then covers the additional data governance responsibilities needed for blockchain to work well within our organizations.

Overview from DAMA-DMBOK2

Data Governance (DG) is defined as the exercise of authority and control (i.e. planning, monitoring, and enforcement) over the management of data assets.

While the driver of data management overall is to ensure that an organization gets value out of its data, Data Governance focuses on how data-related decisions are made and how people and processes are expected to behave in relation to data.

Each organization should adopt a governance model that supports its business strategy and is likely to succeed within its own cultural context. Organizations should also be prepared to evolve that model to meet new challenges. Models differ in organizational structure, level of formality, and approach to decision-making. Some models are centrally organized, while others are distributed.

Data Governance organizations may also have multiple layers to address concerns at different levels within an enterprise—local, divisional, and enterprise-wide. The work of governance is often divided among multiple committees, each with a purpose and level of oversight different from the others.

The following table describes the typical committees that might be established within a data governance operating framework.

Additional responsibilities due to blockchain

Data governance increases trust in the data within an organization. In many business processes, the central power authority needs to prove its data can be trusted. Therefore, many central power authorities invest heavily in data governance.

I am not only CEO of my small publishing company which acts as central power authority for many publisher processes, I am also the data steward for author and book metadata. This information must be correct, or I quickly lose credibility from bookstores, distributors, and authors themselves. I am also the data steward for royalty information, and I will quickly lose trust from authors if this information is suspect.

Even if a blockchain application to process royalties is introduced within my publishing company, I still need to act as data steward for royalty information—even though my company is no longer the central power authority. I am still responsible for defining and ensuring the data quality of all of the royalty rules. For example, Bob the author receives 12% royalties. Even though blockchain makes the royalty process quicker and more transparent, I am still ultimately responsible for Bob receiving 12% royalties, and not 8% or 15%.

Blockchain will not replace any activities within data governance. In fact, blockchain adds additional responsibilities to those who work with data governance.

Applying DG across organizations

DG exists at local, divisional, and organization-wide levels, but what about across organizations or industries? Blockchain applications will make data governance more complex and interesting by crossing organizational boundaries. Your Data Governance Steering Committee may need to meet periodically with the committees from other organizations that are involved in the same blockchain initiative. For example, a group of insurance companies, working cooperatively to build a blockchain application to reduce fraud, would require consistent data governance practices.

In another example, someone buys a book on Amazon, and via a smart contract ten minutes later the author receives a royalty. Do we view terms like “book” consistently? What about the concept of “return?” If the customer returns a book to Amazon, how do we ensure the author’s royalty is also returned? Furthermore, from a tax perspective, we must ensure that the publisher and author do not need to treat this particular book sale as generating tax.

When blockchain applications cross organizational boundaries, there will likely exist the need for cross-organization or industry-wide DG committees.

Managing perception

Does managing data as an asset include managing the perception of the technology used to store that data? There are a number of applications that have been built using blockchain technology that have a very poor perception among the public.

For example, Silk Road was a website where illegal items could be bought or sold anonymously using bitcoin. The cloak of anonymity granted by blockchain allowed those with poor intentions to conduct business without anyone knowing their identities.

In addition, when we read the news about the latest ransomware attack, payment demands are usually in a digital currency such as bitcoin, which helps to ensure the criminal is not caught.

The Data Governance Steering Committee may need to get involved and possibly work with the marketing department if the perception of blockchain could stand to be improved.

Reviewing rules

Smart contracts are used by blockchain applications to enforce rules set out in agreements, standards, and contracts.

How do we know, though, that those rules are actually being applied correctly?

The code written to automate document clauses must be under the review of data governance, to ensure the code is correctly interpreting the rule.

Checking the rules can apply to both business and government organizations. Let’s return to our royalty process, for example. Even if the blockchain application successfully transfers royalties to a particular author, if the wrong royalty percent is coded into the smart contract, the wrong amount will be paid to the author, leading to accounting and credibility issues.

Reviewing the rules for data governance also includes making sure that smart contracts (and their interaction with other technologies, such as artificial intelligence or IoT) do not cause ethical issues. For example, imagine a smart contract that uses a number of factors to determine car insurance rates, including Fitbit® sensor readings. The sensor readings can report whether a policyholder had a good night’s sleep or not; if a policyholder has a poor night’s sleep for several days in a row, their car insurance rates go up, because of their increased risk of falling asleep at the wheel. This insurance hike could be contested by the consumer, crossing the line into ethics and law. As such, data governance may need to get involved and work closely with the legal department.