Why Data Governance is Fundamental to Technology Transformation

Dave DuVarney, Principal, Enterprise Transformation and Digital Solutions, Baker Tilly

Dave DuVarney, Principal, Enterprise Transformation and Digital Solutions, Baker Tilly

To effectively compete in the modern business world, companies must engage in technology innovations to advance operational objectives while staying ahead of competitors. According to Gartner’s “View from the Board of Directors 2021, CIO Research, July 2020”, 60 percent of respondents listed either artificial intelligence or analytics as a game-changer technology following the COVID-19 pandemic. This article will explore how transformative innovations, like augmented decisions, are built on the foundations of data governance.

Augmented decisions

There is a major trend currently occurring in data analytics that is impacting people daily and itis likely they donot know it. For anyone that owns asmartwatch, you are constantly being reminded to stand up, moveand breathe.Your watch is leveraging the data from your daily behavior and using it to cue intended actions. You can choose to listen to these cues or not, but they are present.

Augmented decisionsare an extension of existing machine learning technologies that process historical information to create new predictions. They rely on these predictions to present options and choices to the user. The user can then use both the data presented and their own intuition to make a more informed decision.

Thisprinciple can be applied to our workin data governance. As a consultant, I need to complete daily timesheets. If we were to write a program that checks my calendar at the end of each day for downtime, collects my appointments and then alerts me when it knows I am not in a meeting to “finish your timesheet”, I wouldlikely act on it. To understand which signals will be the correct ones to drive our actions, we fist need to consider some of the beginning elements of data literacy.

Data literacy

Supporting analytics and AI is what makes innovation like augmented decisions possible. However, it relies on a company first embracing data literacy.

Data literacy deals with a company’s ability to consume, understand and leverage their data. There are three main focuses for data literacy:

- Outcomes

- Personas

- Shared language

Outcomes address why we should look at any given analytic. Specifically, what it is we’re trying to achieve by measuring a given event. In the smartwatch example, the intended outcome of the “stand up” notification is to improve our overall health and well-being.

Personas are important to understand whom a signal or analysis is directed towards and what that persona will do with the information once they have it.The persona gives us a view into how a person works, tools they use regularly and how they respond or use information. A user that has easy access to a computer will need a different type of analytic than someone that is on the road and generally consumes information via a smartphone or tablet.

Finally, data literacy relies on a shared language. As a company discusses key KPIs or other data elements, they must have a common way to efficiently communicate them. This starts with ensuring the right business processes and key stakeholders are engaged to develop that shared language and is generally driven byadata governance function.

Embracing data literacy creates a culture where decisions are supported by various forms of data. If key business decisions are supported by data, a greater emphasis is placed on capturing and reporting on that information, allowingcompanies to leverage data for additional purposes. This includes inputs to machine learning algorithms for enhanced predictions and augmented decision making.

Data governance

This brings us to the value of data governance within your company. Data governance is often thought of as a necessary compliance detail, but this is only true if governance isn’t treated as an enabling function within the company.When implemented correctly, it serves as the single source of truth for all data related matters, allowing a company to accelerate decision making through accurate data gained insights.

Ensuring that data governance is an enabler requires three key business drivers:

- Awell-defined charter to ensure people understand the role of the group/team

- A well-represented and committed set of stakeholders who hold accountability for their data stewardship role

- Clearly defined processes and policies that address how changes in data are to be handled

After the three business drivers are established, acompany can start creating a shared language and common understanding to support their data literacy efforts. This can include the use ofdata catalogs to facilitate a collaborative data environment and jump-start efforts to create a shared data language in your company.

Driving future innovations

Driving innovation in your company can come in many forms. As more companies look to the collection, integration and enhancement of data to achieve a competitive edge, they must first build a foundation on strong data governance principles. This foundation supports overall data literacy and drives a greater focus on data driven decision making, which in turn leads to higher quality data to leverage advanced technologies like machine learning to augment and drive decisions in the future.