David Smith, Senior Director Data Governance and Matthew Bonavita, Senior Director, Global Risk Management, New Balance
David Smith, Senior Director Data Governance and Matthew Bonavita, Senior Director, Global Risk Management, New Balance
Businesses create and have more access to data than ever before. Those companies that can harness the value in their data into meaningful information that leads to better informed decision-making, gets them closer to their customer needs and provide its employees more confidence to complete their tasks will have an enormous competitive advantage in the marketplace.
Championing data quality and responsible data use begins with a bold commitment to aligning organizational expectations from the C-Suite to entry level associates. Data quality is the foundation of confident decision-making. It ensures data is accurate, complete, consistent and reliable, empowering teams to act with clarity and precision. Responsible data use helps minimize errors and reduce risks. When data owners follow established standards, apply proper validation and uphold governance practices, they help maintain the accuracy and reliability of the data across the organization.
Marketing, supply chain and innovation functions depend on high-quality data to operate and drive team success. In a mature data-driven organization, understanding how those teams rely on high-quality data to operate effectively is pivotal to supporting responsible data usage. Marketing thrives on data to craft personalized campaigns and leverage customer insights; Supply chain relies on it to optimize forecasting and logistics; Innovation teams harness it to fuel experimentation and accelerate product development. Their success centers on data that is accurate and timely. Poor data quality is a risk to these teams when the critical data elements they rely on are not managed responsibly by data owners in the functional areas. Companies must always be on high alert and vigilant as data is constantly changing and evolving throughout the end-to-end process utilized by all functions. For example, inaccurate demand forecasts will lead to running out of stock or an unhealthy amount of excess inventory, while incorrect customer data can derail targeted marketing activities.
A data steward plays a critical role within functional teams by ensuring that data is accurate and aligned with business needs, acting as a bridge between technical standards and operational execution 
Responsible data use is equally critical. It means managing data ethically, transparently and in compliance with internal policies and external regulations. This includes protecting the privacy of consumers, mitigating bias in data collection and decision making and ensuring data is used appropriately. Responsible practices reduce legal, financial and operational risks and build trust across teams and with customers.
So what steps can be taken to drive data success? Creating documented controls in a balanced, federated data governance model is key to ensuring data usage is globally governed while simultaneously allowing local management of the data. To support this, organizations must invest in strong data governance that provides the global guardrails, empowers data owners to act locally, and fosters a culture of accountability throughout the use of the data in downstream processes. When teams understand the impact of their data decisions through transparency of the end-to-end process, they will be better prepared to protect the company from risk.
Building data expertise and literacy across the organization is pivotal and starts with sharing knowledge. Hosting workshops, creating playbooks, and utilizing data glossaries and data dictionaries are good ways to educate and communicate with key stakeholders. One strategy that supports raising data literacy is embedding data stewards within teams to foster collaboration and ensure best practices are consistently applied. A data steward plays a critical role within functional teams by ensuring that data is accurate and aligned with business needs, acting as a bridge between technical standards and operational execution. They become the central person to share and embed data knowledge from across the enterprise and into functional teams.
Investing in data storytelling is a good way to connect data quality directly to company goals. By translating complex data concepts into relatable narratives, teams can better grasp how data impacts business outcomes such as customer satisfaction, operational efficiency and revenue growth. Visualizing data quality trends and linking them to company specific decisions helps build a shared understanding and reinforces the importance of data excellence. When knowledge is openly shared and stories bring data to life, teams become more confident in their data decisions.
Functional teams will need to also establish clear metrics and key results for data quality to improve. Aligning key data usage metrics across the company can support the tracking of progress and identify areas for continuous improvement. Transparency in the metrics promotes responsible data usage and accountability in the roles, responsibilities and expectations in the process. By leaning in on the metrics related to the data, team members can more easily identify gaps in the process, data and technology and expedite improvements to the process.
Technology and associated tools play a critical role in supporting data quality and responsible data usage. Key enablers of technology are the ability to profile, catalog and understand data lineage across systems, while supporting transparency and consistency. If done correctly and in partnership with the stakeholders, teams can easily understand the source of the data, structure and usage of data in the end-to-end process. Embedding logic into these tools, such as automated validation rules and access controls, reduces the risk of bad data traveling from source to consuming systems. For example, AI-driven automation can flag inconsistencies in real time, enforce compliance policies and modernize data correction processes, helping organizations proactively manage data quality and mitigate operational and regulatory risks by solving issues at the source.
The goal of modern companies must be to unlock and promote the value of data. Companies must draw a line in the sand and commit to elevating data quality and responsible data use as a strategic, core business investment. The time to champion data is NOW. By empowering teams, investing in the right tools to support team members and fostering a culture of accountability, the business can leverage data as a strategic advantage that drives innovation and company growth.