Poor data quality costs the average organization a staggering $12.8 million every year, according to Gartner research. Data governance requires significant investments in people, processes, and technology, so measuring the return on that investment (ROI) is crucial.
Calculating your data governance ROI isn’t just about justifying the expenditures – it quantifies the tangible business value created and enables data-driven decision-making for continuous improvement. Demonstrating a positive ROI is essential to securing long-term executive support and positioning data governance as a business enabler, not just an IT cost center.
Why is Measuring Data Governance ROI Important?
At first glance, measuring the ROI of data governance initiatives may seem challenging. After all, how do you quantify something as intangible as “better data”?
The reality is that poor data quality and inefficient data management have very tangible financial implications. Organizations can mitigate costs by implementing robust data governance while unlocking new revenue streams.
Measuring data governance ROI provides a way to benchmark progress against targets over time and make a compelling business case for sustained investments.
Cost Savings from Data Governance
One of the most straightforward ways data governance drives ROI is through hard cost savings. This includes reducing costs from data breaches, compliance penalties, litigation, and associated brand damage – just look at the billions in fines issued for privacy violations. It also means avoiding redundant costs by eliminating duplicate data silos and rationalizing overlapping data storage, maintenance, and licensing across the enterprise.
Further cost savings come from minimizing manual effort and labor costs for data integration, cleansing, transformation, and other routine tasks that can be automated. Another major factor is decreasing costs from product defects, service failures, overprovisioning, and other downstream impacts of poor data quality. Finally, data governance enables the decommissioning of legacy systems and lowers IT infrastructure costs through data consolidation and optimization.
Productivity and Process Gains
Beyond direct cost savings, data governance ROI comes from productivity gains and process optimization.
This involves increasing workforce efficiency by enabling self-service data access with proper security controls rather than relying on manual requests. It reduces the significant time spent finding, preparing, integrating, and reconciling data across disparate sources for analysis. Productivity is boosted by providing clean, consistent, trusted data for decision support instead of second-guessing sources.
Data governance facilitates cross-functional collaboration by establishing a “single source of truth” and democratizing data access. It allows for standardizing and streamlining business processes through integrated, high-quality data and automated workflows.
Additionally, it enables the automation of repetitive, manual data-related tasks like data entry, validation, and mapping. Accelerating decision velocity by ensuring stakeholders have the right data at the right time, properly governed, is another key benefit.
New Revenue Opportunities
While cost savings and productivity are the most obvious ROI contributors, data governance also unlocks new revenue opportunities. It enables data-driven decision-making for developing innovative products, services, business models, and go-to-market strategies.
Data governance provides the trusted data foundation for advanced analytics, AI/machine learning, and intelligent process automation initiatives. It improves customer analytics for personalized marketing, cross-selling/upselling, churn prevention, and superior customer experience.
Data governance also facilitates regulatory compliance, enabling confident entry into new markets, industries, and geographic regions. Finally, it drives innovation by democratizing access to high-quality data across the organization and empowering employees.
12 Tips for Calculating Data Governance ROI
While the potential ROI is compelling, calculating an accurate return requires a structured approach.
Here are 12 tips for effectively measuring and maximizing the ROI of your data governance initiatives:
- Define the key ROI metrics to track based on your goals, priorities, and potential impact areas, such as those outlined above.
- Establish a solid baseline for each metric before implementing data governance to measure improvements against.
- Directly measure metrics with clear costs/gains like savings from avoided data breaches, penalties, litigation, etc.
- Conduct employee surveys or activity sampling to quantify time/effort savings from increased productivity.
- Use industry benchmarks and market analysis to estimate potential revenue opportunities enabled.
- Leverage analytics to correlate data governance maturity with positive business outcomes like revenue growth.
- Calculate ROI as (Gains – Investments)/Investments, capturing one-time implementation and ongoing operational costs.
- Use conservative estimates to account for hard costs and soft benefits when possible.
- Forecast expected ROI over multi-year horizons based on your data governance roadmap and adoption curve.
- Complement quantitative ROI metrics with qualitative evidence through use cases and success stories.
- Establish processes to continuously measure, optimize, and course-correct your data governance ROI.
- Adjust ROI targets and focus areas as your data governance strategy evolves and matures over time.
A Real-Life Data Governance Example from Semarchy’s Client
Let’s look at two real-life data governance ROI case studies that showcase how organizations can maximize returns from their initiatives.
Insurance group APRIL International consolidated customer/prospect data across global subsidiaries into a centralized Master Data Management (MDM) solution from Semarchy. They automated data reconciliation, cleansing, and deduplication for better lead management. This enabled effective cross-selling by providing a unified view of customers and their policies. APRIL also adapted data governance rules and processes to uncover revenue growth opportunities.
Their primary ROI drivers were:
- Increased sales
- Cross-selling revenue
- Operational efficiency gains.
Learn more about APRIL’s success story.
Industrial minerals producer Imerys unified multiple internal systems for consistent master data after acquisitions and decentralization. Through governance, they ensured regulatory compliance and high data quality for business intelligence. Imerys implemented Semarchy’s MDM and data integration solutions to streamline the management of product/material data while overcoming complex data integration and distributed data governance challenges.
Their primary ROI came from optimized operations through:
- Unified data
- The development of new BI capabilities
- Improved regulatory compliance.
Making the Case for Data Governance ROI
Implementing a data governance solution is an investment that can pay back significant returns when done right. Data leaders can make a compelling business case by quantifying data governance ROI from cost savings, productivity gains, and new revenue opportunities.
Real-world examples prove the ROI potential is massive – whether optimizing operations, streamlining compliance, enabling advanced analytics, or simply becoming a more data-driven organization.
When selling data governance ROI to executives within your business, make sure to:
- Highlight the intangible strategic benefits like risk mitigation, competitive advantages, and data-driven innovation.
- Back it up with concrete ROI metrics and use cases.
- Position data governance as a business enabler, not just an IT project.
- Emphasize the cultural and mindset shift required to truly become a data-intelligent enterprise.
- Outline a long-term roadmap for continuous measurement and maximization of returns as your data governance program matures.
Ready to maximize your organization’s ROI on data governance? Request a demo of the Semarchy Data Platform today.