Data Stewardship Is Imperative to Data Management
As data stewards we often feel this way when we talk to our data stakeholders. Our conversations on the topic tend to gravitate toward the impact or value of data stewardship. What rings true is that the value of its outcomes speaks the loudest as to why data stewardship is imperative to any data management strategy. In this article, we will show you how to let its value do the talking for you.
AI Helps, But It’s Not the Solution
In our current economy where artificial intelligence (AI) and automation are fast providing strategic and operational advantages to many organizations, there are facets that are needed to manage data that are beyond their scope, including critical thinking, creativity, teamwork, communication, and problem-solving. These are foundational skills used by data stewards irrespective of the stage or area of data management.
According to the Data Governance Institute, data stewardship is the “set of activities that ensure data-related work is performed according to policies and practices as established through governance.” There is a lot to data stewardship as both a practice and methodology. It typically has its beginning in grassroots efforts, and, if executed well, its positive impact provides the road for adoption throughout the organization. At the fundamental level, there are three main components of data stewardship.
3 Components of Data Stewardship: People, Process, Policy
People: Though technology can provide the needed leverage to scale successful data management strategies, it is through people that we can cultivate, assess risk, collaborate/communicate, investigate, architect, and decide outcomes for dedicated data practices. These roles are slated for the data stewards.
Process: These are the developed, sustained, and agreed-upon steps needed to maintain, correct, or improve the data. Execution of data management strategies depends heavily on these stewardship processes, ensuring that data management aligns with the organization’s business goals.
Policy: These are clear, specific, and easily understood rules to conduct the activity and use of data assets. They not only define the responsibilities for the data stewards and users, but they also create a frame of reference for handling any issues that come up regarding data.
Linking Data to Information
Data stewardship goes beyond simply ensuring that data is accurate and complete. Professionals in charge of data stewardship apply methodologies and critical thinking always with an understanding of how their stakeholders will use the resulting information. For a data-driven enterprise, the use of information cuts across the entire organization. Even though the use cases may vary from area to area, one thing that is consistent is that the employment of accurate and timely information can positively impact business processes and thereby enhance the customer experience. As expected, when customer experience improves, revenues increase, profits increase, and the business grows. Data and information are fast becoming the lifeblood of the business, and their significance contributing to the long-term success of an organization cannot be ignored. In the middle of this all is data stewardship.
So, What Should Data Stewards Be Talking About?
Data stewardship activities tend to be tactical by nature and could easily lead conversations deep into data rabbit holes. But there are many instances where these conversations are needed. In most cases, stakeholders, partners, and users are focused on the results of the process and methodologies. In other words, they are concerned with how data will meet their use case and improve the information they employ to make decisions. Here are three topics data stewards need to understand in order to positively impact business goals:
- Use of information – Understand your stakeholders’ purposes in employing information for decision-making, managing client relationships, and risk management. Focus on how data stewardship can solve and elevate their use cases. Ensure you are able to pass the baton so that your stakeholders can implement your data for its intended functions.. How data stewardship gets there might not be pertinent to the users. For example, for B2B go-to-market stakeholders, the Chief Revenue Officer requires improvements to customer segmentation to drive sales revenue. Instead of talking about firmographic data completeness and accuracy programs (which data stewardship groups should employ), concentrate on the sales operations increase of efficiency as direct stewardship objectives. Provide their accuracy baseline and proceed with incremental and end-projected improvements together with the required timeline. This adds context to your process goals. The stakeholder use case will inform both your processes and communication strategies. Through this, you can bring external referential data and tools fit for their purpose.
- Protection – Data operations are pervasive across the entire enterprise. Data and the information they generate need to both comply with existing policies and combat data decay to guard the organization against data-related vulnerability. Specifically, for non-compliance of GDPR rules, the agency declared fines of up to 10 million euros, or up to 2% of the offender’s entire global revenue In addition, a study done by IBM noted that $3.1 trillion yearly is lost due to bad data. It pays to make the protection of the enterprise a pillar of both your data stewardship communication and programs.
- Emphasis on stakeholder progress – As the saying goes, Rome wasn’t built in a day. The same goes for data stewardship. Partnership with stakeholders becomes an imperative ingredient when data management is aligned to their progress. Have a firm understanding of stakeholders’ short- and long-term goals. Itemize the “gates they need to pass through” and what success looks like. Any efforts, programs, or projects to move the needle of data quality forward should translate to improvements to your stakeholders’ use case. Data stewardship becomes their bridge to success when this alignment is intact.
Last Rule: Data Stewardship Will Go On as Long as It Needs To
And it must. Data is the raw material for decision-making. Bad data hurts the business. There’s no question that data stewardship programs are crucial to the success and future of the data-driven enterprise. The question is: How can these programs add tangible value? The answer is simple: Through their results. The results would require alignment to specific business goals and the use of information. Data stewardship ensures that data management initiatives comply with established business goals. This is done through creative and critical thinking with the emphasis on positively impacting the enterprise use of data, protection, and progress. The focus on these three components will differentiate your data stewardship program, making it an investment instead of a cost. Let its value be your voice.