Much has been written on data governance. It’s an unwieldy concept and its overall purpose can often be confusing. That’s largely because data governance is not a binary solution or process; it will look different for every company because they are all unique. A successful governance program must be tailored to each individual organization. However, creating a program doesn’t have to be a massive headache. Here we’ll discuss the five most important questions you’ll need to answer in building your data governance strategy.
1. What is data governance?
At its most fundamental level, data governance produces high-quality data through a set of rules, procedures, and policies that allow for ownership and decision-making. According to the Data Governance Institute, it is “a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.”
Data governance can be achieved from applying a multitude of strategies for an enterprise:
top-down or bottom-up
singular department focus
product or service focused
and so on
A governance approach and its focus will vary depending on scope, maturity and needs; however, it should be able to achieve a clear understanding of roles and involvement, operations, rules and policies and a way to support and measure its effectiveness.
2. Why is this important for my organization?
Transforming data into information is one of the most important aspects of data management and business intelligence. Making business decisions with data that is either incomplete, not readily available, has multiple business meanings, or is inaccurate are easy justifications for embarking on a governance initiative highlighting data quality.
Other reasons include the inability of business groups to agree upon the data’s purpose, definition, and ownership, which can lead to difficulty coming to a resolution or disjointed decisions. Data governance is important because it creates purpose, leading to greater understanding and trust of data that drives organizations to digital transformations.
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3. When should we employ a Data Governance Framework?
Organization and clarity are the key components to maintaining quality data governance initiatives. When there is a common goal, with shared responsibilities in more than one department or business group, it is simply not realistic to informally maintain these.
Implementing a framework helps control and support the complicated process of organizing multiple business groups, unifying them along a shared goal and purpose, and putting controls in place to ensure processes continue to drive the goals of the initiative.
Frameworks align stakeholders from different business groups into clear operation and communication procedures.
4. Who should be involved?
For some, the thinking is because data is the focus, it is the responsibility of IT to create a successful program. This view is short-sighted. Ultimately, success lies in the shared responsibility that must be driven by the business group(s) which owns the data.
Business owners will need to define the data elements, metrics for operations, and decision-making rules. Then, the role of IT is in the planning of technology and solutions to achieve this strategy. The Data Governance Committee is the glue which keeps IT and business groups aligned and accountable for a successful program.
A data governance effort starts with defining what is important for the organization and begins to group those things into an overarching guide and defined mission — enter the Data Governance Charter. This charter will be the guiding document for your organization’s data efforts, clarifying scope and purpose, providing the reasoning behind the importance for the company, and getting business buy-in from the highest levels.
Accompanying the charter is the framework. This will carry out the goals of the charter and establish the scope and the accompanying roadmaps to deliver the invested value back to the organization.
Establishing a framework is the hardest step in the process because it is the foundation upon which additional initiatives and changes evolve.
These first five questions are just the tip of the iceberg. How much time, money and dedication needs to be budgeted? Where do we begin applying data governance principles in our organization? Is the framework flexible for an evolving organization and focus, does it have enough process and definition without becoming overwhelming? These answers and more are going to be important to kicking off your governance journey.
RevGen Partners has helped many organizations set up successful data governance programs. Improving the data quality into a trusted business asset, securing data uniformly, and establishing master data management solutions are just a few examples of outcomes that have enriched the data and analytics capabilities of our clients. Contact us today to find out how RevGen Partners can help your organization achieve more through data governance.
Corey Biehl is a technology leader in RevGen’s analytics and insights practice. He is passionate about designing and developing data & analytic solutions that make a difference.
A quick summary of our series on AI implementation, where we covered topics from data alignment and architecture to AI analytics and governance, addressing the benefits and challenges of AI integration.
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