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Remain Focused on Data Management Fundamentals

Application of data management fundamentals in a changing environment will contribute to a winning record

Introduction

In the movie Bull Durham the manager of the Durham Bulls, the film’s minor league baseball team said, “This is a simple game: You throw the ball, you hit the ball, you catch the ball.”

Anyone who has tried to do that knows it’s not that simple when a baseball is flying rapidly toward you. But baseball remains true to its roots and the simplicity of the game remains at its core. Keep your eye on the ball. Work closely as a team. Know everyone’s strengths and weaknesses. Fundamentals matter. New technologies, new equipment and new rules keep baseball fresh, interesting and challenging. However, the game is built on fundamentals.

Data Management Parallel Concepts

Parallels can be drawn to data management.  Consider the following.

It’s an exciting time to be part of the data community. There is much to keep professionals engaged and challenged. AI, data architecture and data modeling, data privacy issues, cybersecurity, the General Data Protection Regulation (GDPR), IoT, digital transformation, and more.  It is important to maintain a focus on what is new and what is on the horizon.

It is equally important to not lose sight of fundamentals. They will support and contribute to success in meeting challenges.

There are 5 core data management principles that have evolved over time yet remain true, relevant and important today, and will continue to remain so in the future.  In a profession where change is especially fast-paced, all data professionals can expect success when they retain focus on these concepts.  While key fundamentals are not limited to these principles, they remain at the forefront of success stories.   

Quality, fit and relevant for the intended purpose. There is no debate that data quality is a key to any organization’s success.  With the sheer volume of data available, it is important to know the uses of each data element and what quality aspects are necessary.  Data may still be stored in siloed environments, but its usage may be across the enterprise.  Additionally, data elements critical for one application may not be as critical for another.  The data manager needs to know the differences. Quality efforts can be more focused, data can be made available in a more timely fashion, and costs can be lowered.

Know the user communities.  Not long ago the data community was primarily statisticians, actuaries and IT professionals. The data community is expanding. Disciplines that are more diverse have, want, and need access to data.  Almost everyone is a data citizen in some respect.  Not everyone may understand the full extent, value, meaning or importance of the data they are handling or the rules that apply to its use. Data management is as much about knowing and managing the users of the data as it is about the data itself.

Executive support, executive presence.  Challenges have existed in communicating the need for investment in data management practices, procedures and applications where returns were not always apparent or immediate.  However, in the absence of such policies the reality of customer loss, credibility reduction, and confidence decline, business costs, fines, penalties, and legal costs are widely known.  The rise of the Chief Data Officer has elevated the importance of all aspects of data management.  Executive support has evolved into executive presence.  Executive presence is critical and goes beyond traditional passive acknowledgement, transforming to active championship and sustained funding for data management programs.

Metadata. More users mean there is a greater need to understand the collection of data elements and what they represent.  Metadata, data about data, must reach a broader audience.  It needs to be understandable by those who may not be data professionals. Metadata brings increased meaning and context to data, which is especially important when the user population is expanded.  A shared, common business vocabulary contributes to consistent use of data throughout an organization no matter who the specific user may be.  The fundamental skill of creating and managing a metadata repository includes being able to communicate to a diverse user base.

Data governance. As in any form of governing, rules, principles, responsibilities and accountability must be established. Data assets must be governed through a formal data governance program.  This will maximize the value of the data, align strategies throughout an organization and reduce risk. Many industries are regulated and must rely on data to fulfill their core business obligations to clients and stakeholders.  Regulated industries such as insurance and financial services are accountable to regulators at the state level, the federal level, and through global regulations.  A strong data governance program provides a framework for data operations to function effectively and securely. In addition, it provides a documented way to communicate the practices and procedures that exist.  Data governance is a core function of every data management program.

Conclusion

The concept of managing data may seem simple as the game of baseball appears.  In both instances, the strength of core principles has been demonstrated over time and supported by their ability to adapt to a changing environment.  A solid understanding and application of fundamentals has always, and will always, contribute to a winning record.

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Aimee Siliato, FIDM

Aimee Siliato, FIDM is an experienced data management professional with related experience in actuarial science, product development and government relations. Aimee has led the Insurance Services Office’s, (a subsidiary of Verisk Analytics) data collection, acquisition and strategy department. She is a member of the Board of Directors and vice president of marketing for the Insurance Data Management Association (IDMA) and a past president and chair of the Board of Directors of IDMA. She is a contributing author to the textbook Introduction to Data Management Function and Tools. A graduate of Brooklyn College, Aimee obtained her fellowship in insurance data management in 2007.

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