The integral role of data in organizational success
August 21, 2021

The integral role of data in organizational success

Determining how to leverage and analyze data to make better decisions.

The integral role of data in organizational success

I’d like to introduce Resigility readers to Jonathan Adams, a new and valued member of our team. Jonathan brings extensive experience helping clients transform their data management practices, create a data culture, and use data and analytics to enhance decision-making and results. His skills and background complement Resigility’s overall focus on driving market, business and digital transformation. By adding data and information services to our offerings, we can deliver more comprehensive support to clients, enabling them to turn strategy into action and improve resilience and agility. I hope you enjoy getting to know Jonathan and learning about the data and analytics capabilities available from Resigility.   – Karen Marlo, President, Resigility

The integral role of data in organizational success

With data playing an integral role in organizational success, Resigility brought me aboard in March to provide data management expertise and experience to clients, primarily chief data and information officers (CDOs and CIOs) as well as data and analytics teams.

So, who is Jonathan Adams? In one form or another, I have been an analyst my whole career. As such, I approach technology by scrutinizing how it can serve as a catalyst for developing positive outcomes. With more than 25 years of consulting experience, I collaborate with clients to help them gain maximum value from their data, leading to high-impact results. It’s gratifying to equip organizations with data, information management and analytics best practices that ensure compliance and risk management while enabling insights to create new or improved services, products and operations. My side gig is serving as an adjunct professor of data management at the University of Maryland, where I teach graduate courses in the College of Information Studies on data governance and data quality, and data integration for analytics.

Common goals

I’ve been fortunate to support data management and analytics initiatives at federal government agencies, including the Centers for Disease Control and Prevention, U.S. Treasury, Census Bureau, and Securities and Exchange Commission. More recently, I’ve applied the same methodology at large companies, such as General Mills, Johnson & Johnson and PepsiCo. While each entity had varying issues, they all shared the common goals of managing their data more effectively, using analytics to increase insights, and making informed, data-driven decisions prompting service or product innovations and efficiencies.

Our data management and analytics approach

The most typical challenge and opportunity for government agencies and corporations is determining how to leverage and analyze their data to make better decisions. The key that unlocks this significant opportunity is to build an all-embracing enterprise data management model that engages and aligns everyone in owning, integrating and generating value from data existing throughout the organization. Our approach to producing this model is based on a three-step framework comprised of:

  • Planning: The initial phase includes understanding existing capabilities, defining data analytics, governance and quality strategies, and brainstorming a roadmap to desired outcomes.
  • Architecting: We then assess operating, analytical and organizational alignment, coalescing everything into a data management and governance framework, information architecture and data operating model.
  • Orchestrating: This is the time to move from strategy to action, orchestrating two distinct but parallel paths to implement the model:
  • The adoption path involves defining roles, and using tools, rules and training to keep everyone on track.
  • The sustainment path ensures specific goals and objectives are realized through continuous improvement, staff development, ongoing monitoring of key performance indicators and compliance management.

Both paths depend on change management, employee engagement, communications and other business transformation practices to advance the enterprise data operating model. I’m grateful that my colleagues at Resigility have proficiencies in all of these disciplines to deliver the complementary skills necessary for optimum implementation and maintenance.

Holistic perspective

By looking at each organization’s data and people from a holistic perspective, the enterprise data operating model provides capabilities to achieve business objectives and greater success. Our Resigility team is committed to generating similar results that address your unique requirements. Please feel free to connect through Resigility and/or LinkedIn to start the data, information management and analytics conversation.

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