Utter those two words to someone who has not heard them before, and you’re likely to get back a quizzical look. A look that encompasses intrigue, doubt, skepticism, and maybe even a little cynicism.
Is this some buzzword made up by consultants? Is this something my kind of business really needs? If it is important, then who is responsible—finance, marketing, IT?
This post will help anyone who’s curious understand what data governance really is, why you should care about it, and some tangible business benefits that it can lead to.
What Is Data Governance?
According to Wikipedia:
Data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete life cycle of the data. The key focus areas of data governance include availability, usability, consistency, data integrity, and data security and include establishing processes to ensure effective data management throughout the enterprise such as accountability for the adverse effects of poor data quality and ensuring that the data which an enterprise has can be used by the entire organization.
A simple way of thinking about data governance is that data is a strategic asset. Like any other asset, it’s ideal to maximize its value and minimize the risks associated with it. Data governance is an interplay of policies, roles, processes, and IT systems designed to manifest this.
Data Governance Policies
The primary function of data governance is to institute policies. These policies cover important factors that contribute to data quality and security.
For example, with respect to data quality, policies can mandate the degree to which data is accessible and accurate. Also, policies provide guidance on how quickly to update data to remain consistent with real world events.
With respect to security, data governance specifies who gets access to which data elements. This is critically important in order to safeguard proprietary and client confidential information.
Data Governance Roles
The next piece of the data governance puzzle is roles. These assign accountability for the standards set forth in data governance policies.
A data steward is an important role in data governance. Typically, there will be multiple data stewards, each accountable for maintaining the quality of some subset of enterprise data. A data steward can be an individual or group tasked with this duty.
A data governance council is the ultimate authority with respect to data policies and decision making. The council comprises of senior representatives from all aspects of the business. They put policies in place, as well as review and evolve the policies to keep them fit for purpose.
Data Governance Processes
Data governance processes include the core processes to maintain and monitor compliance with policies. Moreover, this includes all aspects of day-to-day business and IT standard operating procedures that support the objectives of data governance.
An effective implementation of data governance includes an audit of existing processes that involve data collection, cleansing, storage, and distribution. The aim is to discover gaps that need to be closed to bring the processes into compliance with data governance policy.
For example, if one department maintains historical data for two years, but the policies mandate that five years’ worth of historical data is accessible, then existing storage and archiving processes need to be adapted accordingly.
Tools to Support Data Governance
Standard tools have emerged to support the goals of data governance.
A business glossary is a central repository of all important business terms and the single source of truth to discover the shared definition of each term.
A data catalog is similar to a business glossary in that it specifies key terms, but goes further to specify acceptable values, data sources, which system stores the master record, and the accountable data stewards.
Software solutions exist to support the creation and maintenance of business glossaries and data dictionaries in a collaborative way. These solutions enable stakeholders from all business functions to work together in establishing common understanding. Further, software can perform automated data quality checks and enforce security policies.
Why Should You Care About Data Governance?
Now that we know what data governance is, let’s explore some of the benefits. As data driven approaches to management are becoming a basic requirement for all business, and as the importance of safeguarding sensitive data becomes more paramount, every business has reason to care. Below I outline five key categories.
1. Increased Revenue
Improving the quality of data will have a cascading effect on business operations that ultimately leads to increases in revenue.
Data governance results in better sales lead generation, especially in industries where repeat business is key. Consider a car dealership. Accurate data on past vehicle sales and vehicle service history can help them better identify potential customers in a good position to upgrade to a new vehicle.
Additionally, better product information management will lead to faster time to market. This is particularly important for consumer goods companies where important facts such as ingredients and traceability of raw materials need to be completely accurate.
Moreover, better marketing data can lead to better return on investment for targeted campaigns.
2. Reduced Costs
Cost reduction is a key area where the business case for good data governance is easier to measure.
From a purely IT management perspective, less duplication of data translates into lower storage costs. Clear archival policies ensure that data is not unnecessarily stored in fast retrieval systems when it doesn’t need to be.
From a business perspective, data governance results in the elimination of time needed to reconcile inconsistent data that’s spread across different systems. Furthermore, data governance helps you avoid costly rework by eliminating scenarios where work products were created based on inaccurate data.
Ultimately, confidence in data increases and employees make better decisions in less time.
3. Optimized Working Capital
Working capital costs are an often hidden yet significant category of business expense.
Inventory of raw materials and finished products are the most visible source of working capital costs. A sales and operations planning process is intended to optimize inventory levels; however, where there is lack of confidence in sales and production forecasts, inventory levels creep up.
Data governance can help to increase interdepartmental confidence in forecasts, leading to better planning.
4. Lower Risks
Data breaches can come with very hefty fines, not to mention the negative impact on brand reputation. Data governance sets out access rights to sensitive data and helps inform investments in IT for data protection and monitoring.
In some industries, the accessibility and quality of data can have life and death consequences.
For example, hospital emergency services need reliable access to patient medical information to make sound decisions in an emergency. This remains a challenge for healthcare systems. In a recent study in the UK on the National Health Service (NHS), out of 121 million patient interactions, there were 11 million in which information from a previous visit was inaccessible.
5. Stronger Regulatory Compliance
In highly regulated industries such as finance and healthcare, good data governance will make external audits easier to complete and lower the risk of negative findings during them.
The baseline for good data governance is steadily rising. For example, GDPR in Europe requires companies to comply with requests from consumers to have the data that a company holds on them deleted. And obviously, to comply with this, organizations need to have good understanding of what data, both structured and unstructured, they currently hold on customers. The penalty for noncompliance is very high—up to two percent of a company’s global turnover from the preceding year.
As can be seen, there are many reasons to care about data governance. These reasons will continue to become more amplified as the quantity of data captured in IT systems increases.
Furthermore, data is the fuel for machine learning systems. Data governance can help position your organization well for the future and deliver a competitive edge as machine learning increases its influence on business operations.
In conclusion, data governance is not a short-term project with a clear start and end point. Rather, it is a long-term program that transforms an organization to be more data driven. Your data governance program will need to continuously improve and adapt to the changing landscape, as well as challenges and opportunities presented.
Daliso Zuze is the author of this post. Daliso is an expert in agile software delivery using Scrum. Besides that, he’s an experienced digital transformation consultant and entrepreneur. His technical skills center around mobile app development and machine learning.