Data governance has become a necessity in today’s continuously-evolving enterprise environment. In fact, a survey found that most organizations have already employed a range of tools and applications to facilitate various data management functions. This is especially true given how businesses today need to access various data points and gather huge quantities of information regularly.
With data governance, companies can manage their risks, reduce costs, and maximize value when dealing with large amounts of data. However, not all data management policies are created equal.
To ensure quality enterprise data while avoiding its misuse, companies need to follow the core principles that make proper data governance effective. The following are the best practices to follow, so you can master data governance in your organization.
1. Establish a Measurable and Company-wide Goal
In order to work well, a data governance program needs to have a measurable goal that everyone in the organization understands. Each company will have a unique goal since this will depend on factors such as their industry, target market, and capabilities.
Such an objective could be anything that affects growth, efficiency, revenue, or risks. To get started, one must first determine the primary reason for the program and identify ways to assess its effectiveness.
An ideal approach is defining the end results, which means determining the information issues that need to be addressed before the company can obtain value from it. This could also be about the goals that have to be achieved and using data to facilitate their accomplishment.
The following are some examples of data governance goals:
- Improving operational efficiency
- Increasing sales in a particular market
- Simplifying business integrations
- Enhancing overall data quality
2. Measure the Data Governance Program’s Success
Once a measurable objective has been set, it’s only right to assess the whole data management program to see if it has been effective. After all, data governance is all about making decisions.
It’s important to keep in mind that the standard measurements of success for most organizations do not directly apply here. Some of the metrics that can allow companies to identify whether their governance policy works are the following:
- The total number of individuals taking part in the program — such as those trained in specific processes or assigned certain tasks
- Notable improvements in terms of quality and usage of enterprise data
- The total number of data sources that were impacted by the data governance policy
3. Be Knowledgeable of the Regulations for Compliance
Not all industries are scrutinized the same way, as some are more lenient than others. For instance, those in the retail business have more leeway compared to financial institutions. The location where one operates also affects the regulations one need to follow.
That’s why it’s vital to identify the rules and regulations when setting up a data governance program. An ideal approach is ensuring that it helps meet organizational goals while allowing the entity to remain compliant.
No one should dive right into their governance policy without first understanding what their company’s compliance requirements are.
4. Involve Executive-level Managers Right From the Start
Involving C-suite executives from the very beginning of a data governance program can help facilitate and speed up the entire process. Companies can establish their data domains faster while minimizing the time needed to refresh all of their data assets.
Doing so should allow organizations to obtain value from their data as soon as possible. It should also help them make smart business decisions based on their analytics-driven insights.
To capture the interest of the top management, one should consider asking the following questions:
- What kind of data do you need for your domain to achieve its KPIs or goals?
- What are the challenges that affect your ability to access data seamlessly?
- How do these obstacles impact our offerings?
Being able to refer to the business value of data right from the start can catch the attention of C-suite executives. This also helps companies jumpstart their data management initiatives.
5. Secure Company Data
Digital security has become a priority nowadays, especially given how threats continue to evolve and grow in sophistication. Keeping enterprise data systems safe while staying on top of rules and permissions is not an easy job for anyone.
That’s why security and data governance teams need to work hand-in-hand for both to be effective. For starters, the governance group needs to apply data access policies and set them as close to the data sources as possible.
For instance, customer information can be established within the database of a transactional system but assessed within a data warehouse. The data here will be extracted regularly from the system and then uploaded to the repository.
By applying privacy and security rules close to the source, companies can get rid of unnecessary data while simplifying how they manage it.
6. Ensure Awareness and Transparency
Organizations should be committed to making everyone aware of their data management program while ensuring transparency throughout. The main reason for this is that such a policy simply won’t be effective if there are data users who don’t know that it exists.
Here are several tips to consider to ensure awareness and transparency:
- Be transparent about the program by letting everyone know what its goals are and how to measure it for success. Publishing the data management strategy will go a long way in keeping everyone on the same page.
- Onboarding policies need to make new employees aware of the data governance program. Companies can work with their human resource teams to insert data governance training into their approach.
- All technical training that touches on data needs to include relevant aspects of the data governance strategy. Employees need to know how the program affects the tools and platforms they use.
- Let everyone know that certain data sets have been governed accordingly by applying a stamp of approval. These labels can be added to data reports, dashboards, and other areas for awareness.
7. Constantly Review the Data Governance Policy
It’s important to assess the data management program even after it has already been established. Effective policies need continuous effort — especially since new roles and regulations will come up in the future.
Data leaders should identify what needs to be improved by adopting necessary technologies or getting rid of obsolete ones. Repeated evaluation of governance policies can keep organizations in line with the changing business environment.
At a minimum, companies should assess their data governance policy at least once a year while other reviews can be performed when needed.
Data Governance and ESG Reporting
There is a growing demand for companies to be more transparent in terms of their social responsibility and sustainable practices. Organizations are now being held accountable by various stakeholders and NGOs with the goal of learning how they impact the world today.
That’s why environmental, social, and governance (ESG) analysis and reporting have now become a necessity as they provide valuable insights while developing long-term value for key parties.
In ESG reporting, a company discloses data on its operations concerning its environmental, social, and corporate governance. In other words, it allows investors to have an overview of how the business affects these areas.
Being able to analyze the performance of these ESG elements will provide decision-makers with the knowledge they need to screen investments. Investors can avoid choosing companies that could pose a high financial risk due to their poor environmental performance.
There is a growing demand for corporate ESG data reporting, showing that future-focused organizations know that communicating their ESG criteria within their strategy is essential.
The importance of ESG for companies and investors worldwide is growing. In fact, a 2020 report found that 90% of the largest 500 companies are already practising ESG reporting.
Experts are predicting that ESG transparency will be the focus for many organizations in the years to come. This is especially true as investors are increasingly looking at ESG-related issues to help manage their investment risks.
At the end of the day, companies that fail to provide ESG or sustainability reports about how they operate may be overlooked by potential investors.
Conclusion
Establishing a data governance program is a monumental feat that requires the involvement of everyone in the organization to be effective. That’s why having a solid strategy, measurable goals, and an emphasis on collaboration are all necessary for success.
With the right framework, companies can master data governance and become more efficient in how they handle their data.
Meanwhile, ESG reporting has started to become a need for companies today. Not only does this help them reach capital markets — it also allows them to be seen as potential investments for interested stakeholders.
Showcasing solid ESG performance results in favor from investors while those who fail to uphold theirs are seen as a greater financial risk.
With robust data governance and an effective ESG reporting approach, businesses can increase their resilience in the years to come.
