Top 4 Data Governance Practices You Need to Know for 2022

Written by Imran Abdul Rauf

Technical Content Writer

While the data governance industry was valued at $1.81 billion in 2020, top data practices and frameworks could see you become a part of the $5.28 billion industry by 2026. Thanks to the COVID-19, the pandemic has acted as a catalyst for data usage, hence, organizations are following suite.

Modern businesses are well-aware of the fact that data driven decisions are important to improve their bottom line products and services. While implementing a data governance framework and strategy will tell you where to find a specific data in your organization, and who’s the go-to person to access the data.

In this guide, we’re going to talk about data governance best practices that companies should start considering for their IT goals and objectives in 2021 and beyond.

What is Data Governance?

Data governance is a practice that enlists the individuals in the company who has authority to access certain data subjects and how those assets will be used. While a data governance framework are a set of rules and processes created and followed to gather, store, and use data across the organization. When using the word governance, we’re talking about people, processes, technologies, and frameworks working hand-in-hand to manage important data assets.

According to the Data Governance Institute, it is a system of decision rights and accountabilities for processes and workarounds based on data, and implemented under predefined set of rules about what actions will be taken with the acquired information, what approaches will be used, and when and under what situations. Similarly, every organization has its own definition, but the bottom line description remains the same.

Data Governance Best Practices to Watch out in 2022

Data management constitutes all the workarounds regarding handling of data as a valuable asset, and the team at Royal Cyber creates the best practices for its clients across all industry spectrums. A good practice is never developed without experience. That is why it is important to look around and carefully observe what other companies in the industry are doing for handling data governance frameworks and programs and facilitating data management activities.

For starters, you can create a data governance program and then figure out what’s working and what isn’t. This should assist you in tweaking your strategies as per your business requirements and data objectives. Here we’re talking about some crucial data governance frameworks and practices that your company needs to address from an organizational standpoint. While others will be more technical in nature, like participating in enterprise data architecture reviews or focusing on automation for data requests, workflows, permissions, and approval workarounds.

Emphasize on the Operating Model

Your operating model will create an outline and discuss how your organization defines roles, responsibilities, business units, and data domains. In short, what value does data management has for your company and how your business model revolves around it.

Operating model example

Consider a company with a cross functional work structure, i.e., there is frequent collaboration between finance, marketing, IT, and sales department. Each department have their own data governance experts, data owners and stewards, and owners of the entire infrastructure supporting data. In this case, the data governance practice will create a hierarchy where the enterprise data governance structure and corporate data governance council will report to the Chief Data Officer.

Putting it simply, it is important to define the ownership roles across your company as it will help you socialize your data governance program and create a singular structure to handle data subjects. Members from your company and IT department will report to a data governance council, also termed as data stewardship committee.

The council will be responsible for handling routine data concerns, make decisions, decide how to circulate the data across the organization, and ensure the right tools are acquired and used to help relevant stakeholders in performing their jobs as intended.

Recognize Data Domains

After you’re done establishing the data governance structure, now you need to identify the data domains for each of your business aspects like customer, vendor, and product. Each data domain will contain the following elements: data dictionaries, data owners, business processes, business glossaries, report catalogs, systems and applications, data quality scorecards, and policies and standards. Normally, organizations tend to identify data domains when they encounter problems.

Data domain example

Let suppose a business is facing problems in comprehending its data and wants to acquire deeper, clearer insights about their customers. Moreover, the business wants to improve customer experience, acquire more control over answering customer needs, better manage customer data, etc. And the data is unevenly spread over multiple systems with no predefined ownership.

Here you’ll identify the vital stakeholders, business processes, and data sets regarding the customer domain and product lifecycle. The purpose is to help the business better understand where the data is coming from, who is the owner, when it is altered, and the parties who should be involved.

Encourage Consistent Communication

Yes, we’re talking about the typical communication channel whenever a new process or tool is added in any department’s workflow. Obviously, any activity where plenty of data rests, a sense of shared language is created which makes it obligatory for business processes to have efficient communication. Consistent, timely communication shows the impact of your data governance practice for both short- and long-term results. When it comes to data governance communication, there are three important elements to consider.

  • Buy in: C-suite executives and leaders in every department should know the fact that data governance affects every unit of the organization. The purpose is to make them understand why their participation is required and how it will help them reach their strategic goals. Requesting buy ins from senior management will also create an opportunity for companywide adoption of data governance as departments often lead by example.
  • Onboarding: No onboarding process happens in an instant expecting everyone on the floor to understand the person/process and accept their applicability. The case with data governance is no different. You’ll be required to train every data citizen on the all the theoretical aspects and dynamics of organizational data governance. Try to personalize your communication as much as possible so that inspiring every data citizen to act in accord won’t be a difficult job.
  • Adoption: Eventually, the last part requires you to convince every included stakeholder to adopt the data governance practices by holding onboarding refreshers, educating on policy changes and updates, keeping them abreast with data governance metrics and progress, and asking them to embed alerts and notifications in their tools.

Define Metrics to Gauge Performance

Measuring the success of your data governance program is as important as you would measure the success of your monthly sales campaigns. Remember, data governance is a practice and not a one-time activity, you need to keep exercising for making data-sensitive decisions and crafting new opportunities for the organization.

By defining the metrics and KPIs for measuring the success, you’re actually setting underlined business standards set to be met. Even though the best practices also tend to be the most challenging on most parts, they are equally important for driving an organization’s continuous improvement plans.

Initially, start by answering what is “success” for your business. Your definition of success might not necessarily be the same as that of another company as it depends on the nature of industry, business objectives, strategic priorities, and other various particulars.

  • What do you mean by handling data management and accomplishing data intelligence?

  • How will you be certain you have followed your data governance strategy and achieved your goals?

  • How do you visualize a well-thought data governance program?

In answering the above questions, you’re devising your performance evaluation criteria.

Keeping close tabs on your data governance strategy is important in order to have ample flexibility and be able to make relevant adjustments in the future. The following areas to track with associated KPIs should stick with your organization’s overall objectives and roadmap.

  • Adoption - How many employees are using your data governance strategy and technology? For how long? And how frequently?
  • Access - How much time it takes for users to acquire the information they need?
  • Issue management - How many data based issues are logged in your systems? How many issues are resolved? How well are they resolved? And how long it takes to resolve them?
  • Policy compliance - Does your organization abide by the compliance laws mandated by internal executives and external regulators? If yes, till what extent?
  • Data quality - Is the data clean and usable for a specific purpose? (data quality refers to both qualitative and quantitative pieces of information and whether they’re deemed fit for planning, operational, and decision making purposes)
  • ROI - What financial ROI is the data governance program expected to bring for the organization?
  • Data dictionary & business glossary - How many assets have you uploaded to your system?

Thoughts

The above four data governance best practices we discussed only constitute some of the best practices that top data-centric organizations follow. Regardless of the nature of your business and industry requirements, you need a certified data governance and privacy expert to help you get started with your governance program. So are you ready to get accustomed and put these practices to work?

Contact Us

Royal Cyber is a data governance service provider working with the best data-driven teams and technical personnel in the business. Our data governance and analytics service helps organizations acquire valuable insights in real time and enable them to make smart decisions based on that information.

Contact our industry experts at Royal Cyber or [email protected], and learn how your business can acquire data supremacy in your digital space.

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