In this episode, Laurence Young, a value consultant, discusses the importance of improving data from a business perspective. They explore showcasing the value of data investments and emphasize the significance of revenue as a metric for growth. The speaker also shares insights on quantifying the return on investment for data initiatives and addresses challenges in improving customer data. They highlight the importance of aligning organizational goals with data projects and connecting business metrics with data quality metrics.
To demonstrate the value of investing in data, data leaders should align data enhancements with overall business goals, translating process improvements into direct benefits for the business such as cost savings, revenue generation, and productivity enhancements.
To showcase the value of data investments, data leaders need to link improvements in data quality and processes to financial outcomes by analyzing key performance indicators (KPIs) and quantifying the financial impact through increased customer retention, improved cross-selling, or other relevant metrics.
Deep dives
The Importance of Connecting Data Investments to Business Value
One of the main topics of discussion for data leaders is how to connect investments in data to business value. This challenge is a recurring issue faced by CIOs, CDOs, and VPs of data and analytics. The key question is how to show the value to the business when investing in data-related initiatives such as software, reports, dashboards, data governance, and data stewardship. Stakeholders want to know the quantifiable business benefit and outcomes that these investments will bring. This has become even more relevant with the increasing need for data-driven decision-making. The conversation with Lawrence Young, a value consultant, explores the significance of this connection, highlighting the importance of translating data improvements into tangible financial impacts, such as cost savings, increased revenue, and risk mitigation.
Understanding the Business Perspective of Data Investments
To successfully connect data investments to business value, it is crucial to consider the business perspective. Technical teams often focus on process improvements, but it is important to translate those improvements into direct benefits for the business, such as cost savings, revenue generation, and productivity enhancements. By aligning data enhancements with overall business goals and initiatives, it becomes easier to demonstrate the value of investing in data. The speaker emphasizes the need to bridge the gap between technical teams and business stakeholders, ensuring that data initiatives have a clear and measurable impact on the bottom line.
The Significance of Financial Metrics in Demonstrating Data Value
When showcasing the value of data investments, financial metrics play a vital role. It is essential to link improvements in data quality and processes to financial outcomes. By analyzing key performance indicators (KPIs) and connecting them to revenue, cost savings, and risk management, data leaders can demonstrate the return on investment. This requires understanding the baseline metrics and identifying areas where data improvements can directly influence business outcomes. Quantifying the financial impact, whether through increased customer retention, improved cross-selling, or other relevant metrics, creates a more compelling case for investing in data initiatives.
Maintaining an Ongoing Focus on Data Value and Alignment
Building a strong partnership and maintaining alignment between business and tech teams is crucial for ensuring continuous focus on data value. Data initiatives and their impact on business outcomes should not be seen as one-time efforts but as ongoing processes. It is important to have a dedicated person or team responsible for monitoring the progress, keeping the project on track, and adjusting strategies as business goals evolve. This ongoing commitment allows organizations to refine their approach, adapt to changing circumstances, and maximize the long-term value of their data investments.
Data leaders have long been challenged by the need to make a tangible connection between investments in data and quantifiable business outcomes. Value Engineering is an evolving competency that CDO’s can integrate into their organizations to solve for this mission-critical need. In this episode, Laurence Young shares his insights as a practiced Value Engineer, sharing his recommendations on the steps CDOs need to take within their organizations to start measuring their business effectiveness.
