Data quality and data governance initiatives often get overshadowed by trendier projects involving AI or IoT. This article describes the importance of data quality and data governance to the success of all other digital transformation projects and outlines how data managers can build a business case for them.
Let’s face it, data quality and data governance are not the most exciting topics in the world. While senior executives want to support transformative programs to revolutionise their business, data quality and data governance projects often get overlooked in favour of trendier projects like artificial intelligence (AI), robotics, internet of things (IOT), and even business intelligence (BI).
Regulated industries are probably the only exception. Senior executives and board members are held accountable for data breaches, misuse of data, or misinformation caused by poor data quality. As such, they’re very open to new business cases put forth for data quality and data governance projects.
“Without solid data quality and governance, AI, IOT, and BI projects are doomed from the outset”.
The Importance of Data Quality and Data Governance in Digital Transformation
In Gartner’s 2019 CEO Survey, 15 percent of CEOs named data centricity and data management as organisational competencies that need to be developed further. We expect this number to grow in 2020 as our experience in the Irish, UK, and European markets confirms that organisations are realising the value of investment in data quality and data governance.
Data quality and data governance are essential for the successful delivery of all other digital transformation programs — without solid data quality and governance, AI, IOT, and BI projects are doomed from the outset.
When you position data quality and data governance projects from this perspective, it becomes a lot easier to make the business case for them.
We believe there are clear business case drivers which show return on investment in data management, quality and governance can be made successfully. In this section, we’ll describe three key business drivers that will help you build a case for investment in data quality and data governance projects.
3 Key Business Case Drivers for your Data Quality and Data Governance initiative
All organisations make decisions about data, regardless of whether they have formal data quality and data governance functions. However, those that invest in formal data quality and data governance technologies and programs exercise authority over their data with greater intentionality. This level of data control means they are better equipped to address three core business drivers critical to any business case:
- Reduce risk
- Improve operational efficiency
- Grow the bottom line
1. Build a Business Case based on Reducing Risk
The risk management component of a data governance framework considers:
- Data integrity
- Regulation and Compliance
Improving data quality and data governance surfaces the enterprise risk posed by data and helps establish policies and processes to minimise those risks.
Outlining potential risks to the enterprise creates a sense of urgency about data security. Data quality and data governance initiatives improve data security as they define data ownership and related responsibilities.
Improved data security benefits the business directly, by physically protecting the data asset to prevent loss, and indirectly, by enhancing the reputation of the business as a company that customers, suppliers, and stakeholders can trust. Safety and security of customer and employee data are complete no brainers and must be core to your business case.
“The business case for data quality and data governance is easier when both are properly understood”.
Data quality and data governance play an important role in regulatory compliance. Businesses are held accountable to different regulations depending on the locations and industries they operate in. Data quality and data governance reduce risk of non-compliance by providing efficient policies and processes to control confidential and personally identifiable information (PII), thus avoiding the risk of penalties and sanctions.
Highlighting the risks and potential costs associated with non-compliance is a huge motivator for investing in data quality and data governance.
2. Build a Business Case based on Improving Operational Efficiency
Data quality and data governance benefits the business by making data more accessible to those who need to make decisions and take actions.
Clean, up-to-date, good quality, well-governed data adds a layer of confidence to decision making. This leads to faster turnaround of answers and accurate reporting. Data governance also establishes uniformity with data definitions and business terms so everyone can speak the same language and compare like with like. This demonstrates the inclusive nature of data which adds value to all stakeholders.
Improved data quality also improves user satisfaction and encourages the use of data in decision-making processes. In your business cases, highlight how decisions based on reliable, factual data can lead to better business outcomes and continuous improvements in business performance.
“In your business case, emphasis the growth of data and stress the importance of addressing it sooner rather than later”.
For example, businesses today have an ever increasing number of data sources, both inside and outside the organisation. Simplified business data integration streamlines common processes for continuous business monitoring to enable more data-based analytics. The quicker businesses can integrate trustworthy data into their decision making, the faster they’ll be able to make more incisive decisions. In your business case, emphasis the growth of data and stress the importance of addressing it sooner rather than later.