The 2019 Data Governance Winter Conference took place December 2-6th, 2019 at the oceanfront Marriott Delray Beach in Florida, just steps from the Atlantic Ocean. Hosted by DebTech International, this premier event offered opportunities for hundreds of data governance and data stewardship professionals from across the world to come together and share best practices, learn from and help each other, and network.
Whether you were a beginning or seasoned practitioner, this conference offered something for all levels: tutorials, keynotes, speaker sessions, real world case studies, panels, special interest groups, sponsored sessions, exhibitor’s showcase, workshops, panels, and two-day seminars.
Additionally, breakfast and lunch sessions each day fostered an atmosphere of interaction among peers, colleagues and speakers who shared questions, insights, and ideas with each other.
Having attended last year, I was excited to return. Getting to Florida from California is an all-day affair, so I decided to fly in early for a few days of vacation to enjoy the white sandy beaches and turquoise waters (just a few steps away from the hotel!) and explore the charming shops and restaurants along Atlantic Avenue (the main street of this cozy oceanside community). What better way to tackle the challenges of data governance than being well-rested and refreshed? In hindsight, that was a very effective strategy – and this year’s conference was even better than before!
Pre-Conference Tutorials
The first pre-conference day offered optional half-day morning and afternoon interactive tutorials facilitated by industry leaders, focusing on a specific subject. Topics ranged from getting started, gaining leadership buy-in, agile data governance, balancing competing priorities, and linking data governance to data strategy to using data governance tools, data protection & CCPA, data policies, and operationalizing data governance.
I chose Gaining & Sustaining Senior Leadership Buy-In with Bob Seiner to start the day. Bob emphasized making data governance practical and non-invasive, by engaging those who are already doing this work informally and teaching them to do it differently and better with officially recognized roles and responsibilities and repeatable processes. He shared great ideas on messaging for leadership, including the tagline “Think before you ____ data!” with options like “Print, Share, Export, E-mail” filling the blank.
I moved on to Donna Burbank’s Designing Data Governance & Metadata into Data Strategy for my second tutorial. Using examples from various industries and clients, Donna explained how to link business goals to technology solutions and position your enterprise data architecture to support top business goals. One effective strategy for communicating with leadership is using storytelling to illustrate how data governance can help meet strategic goals. Attendees practiced writing and sharing elevator pitches (with audience feedback) for top projects at their organizations. One of my favorite taglines from her presentation was “Your data is only as good as your metadata!” Without good metadata, democratizing data will be a much bigger (if not impossible!) challenge.
Conference Sessions
Following the tutorials, the first set of speaker sessions for the conference kicked off. I sat in on The Building of the Data Governance Program at BlueCross BlueShield of Alabama to learn how Kristin Cacace led their data governance program to address key gaps identified by their internal information management team. Within a year, they established data ownership and stewardship across four domains, ramped up 40 data stewards, and added several hundred critical data elements (with definitions) to their business glossary, closing out 7 of 12 major gaps requiring data governance assistance. Impressive!
Next came the first keynote session of the conference from the winner of the 2019 DGPO Data Governance Best Practice Award. Cynthia Parsons from Nationwide Insurance shared insights gained along their nearly twenty-year journey, starting with the emergence of data governance in 2001 and its various stages of formalization and expansion to the eventual positioning of data governance and quality assurance as an enterprise function with multiple lines of defense under a Chief Data Officer. I encourage everyone to read about their journey and learn from their strategies and successes. Huge congratulations to Cynthia and Nationwide!
The Data Governance Professionals Organization (DGPO) kicked off the first official conference day with Lessons Learned in Data Stewardship from Successful Practitioners. Michele Koch and Marichelle Tanag presented key roles and responsibilities associated with Stewardship (one of the six core areas of practice in their best practices framework). If you’d like to learn about Chief Data Steward, Enterprise Data Steward and Subject Matter Expert (SME), check out the DGPO website for more information – this organization is a great resource for any data management professional!
Wrapping up the day was an open reception hosted by IBM. Folks gathered for a few hours under the open air of the hotel’s outdoor terrace to share food, drinks, and conversation. The energy was palpable as the sounds of laughter, conversation, and old friends reconnecting filled the air. The conference was already off to a great start!
The two inaugural keynote addresses seemed to set the tone for this year’s conference. Starting with the question Is Corporate Data Literacy a New Mission for Data Governance?, Ho-Chun Ho from JLL shared thoughts and concerns about the skills and knowledge that modern information workers and business leadership need to understand the origin and meaning of data, the methods and technologies used to process and present data, and the proper interpretation of data to support better business decisions. Second, Scott Buckles from IBM used the analogy of Fantasy Football to explain how to Accelerate Your Path to AI by Utilizing DataOps. By coupling machine learning (ML) with knowledge cataloging and a strong information architecture and development operations standards, artificial intelligence can make both structured and unstructured data “business-ready” by eliminating extensive manual data preparation and cleansing processes. My favorite tagline? There is no AI without an IA!
The rest of the morning and afternoon were filled with speaker sessions. I listened to Rachini Moosavi and Sonya Jordan from UNC Health Care describe what to do When Top-Down Data Governance is Not an Option. After spending a year assessing current state through interviews, roadshows and research, they formulated a set of strategies and priorities focusing on data literacy, data utilization and data quality to launch and stabilize their data governance community through grassroots efforts. Healthcare is a tough nut to crack, and their hard work with establishing a council, onboarding stewards to their roles & responsibilities, creating analytics certification standards and cataloguing their assets certainly paid off!
Next I listened to David Loshin who filled in for an ailing Danny Sandwell from ERwin talk about Empowering the Citizen Analyst to Realize True Business Value through formal processes for data intelligence to harvest, organize, curate, administrate, and socialize data and help companies improve operating margins, reduce costs, and increase revenue.
The final event of the day was the exhibitors showcase and reception where conference attendees interacted with each other and more than a dozen sponsors to learn about DG tools and services and share what they learned while enjoying a variety of appetizers and drinks.
Danette McGilvray started the second day of conference sessions with an overview of The Leader’s Data Manifesto, a call for action and declaration of intent for organizational leaders to manage their data, information, and knowledge as vital business assets. Next up was the first interactive practitioners panel called Our Pain is Your Gain – Tips from the Trenches in which five panelists from various industries joined moderator Len Silverston to answer questions and share insights about their data governance journey. Audience members were encouraged to ask questions and share some of their experiences, too. Personally, I find these panels to be one of the most beneficial parts of these conferences – no matter where you are on your data governance journey, cultural and organizational differences have a great impact on what works and learning vicariously from others is a tremendous resource.
Next on the agenda was a featured facilitated discussion about How to Demonstrate the Value of your Data Governance Program with yours truly. This was a new offering and I was flattered to facilitate. With a room overflowing with attendees (it was SRO!), we shared a variety of ideas ranging from baselining and tracking general statistics (e.g., counting assets, data domains, number of employees in DG roles, catalog entries, glossary terms, data quality rules, etc.) to the harder questions of defining and attaching ROI (e.g., labor savings from automation, decrease in data duplication & storage costs, etc.) to your program. Measuring value isn’t always easy – so start with the tangible measurements like basic statistics to build a good foundation before tackling the harder and more challenging elements like ROI.
Wrapping up the conference sessions was a Q&A with the Winners and Finalists of the Data Governance Best Practice Award. This interactive panel of several DGPO award winning practitioners and finalists shared many of their learned, insights, and successes from their own journeys as well as their thoughts and advice for tackling the concerns and problems faced by audience members. If you are struggling with your program, I highly recommend talking to any of these award-winning organizations (Nationwide Insurance, Vanguard, Amica Mutual Insurance, SRP, Dun and Bradstreet) about their experience.
At this point, attendees dispersed to head home or attend one of the four half-day workshops with seasoned practitioners. I chose Supporting Business Needs through Data Quality Metrics with Danette McGilvray, in which she shared her experiences and successes with educating folks on what it means to define, implement, and leverage data quality rules and processes to generate better and more trusted data. These workshops are a great opportunity to learn from experts and other attendees who share their stories and challenges, and I always find something new and exciting to use. My favorite tagline? Never measure anything unless you are willing to act on the results. If we don’t address data quality by fixing the underlying problems, there isn’t much point to monitoring those problems.
Seminars
The final two optional conference provided an opportunity to participate for a much deeper dive into specific subject areas with two-day seminars that provide hands-on learning and exercises. These seminars are facilitated by industry experts with this year focusing on data stewardship and data quality. I highly recommend attending them if your budget allows, as you’ll come out of them armed with a lot of ideas, suggestions and materials for tackling these areas at your organization.
My Key Takeaways
Data governance is maturing, but we still have a long way to go. It’s a challenging space that requires patience, persistence and a “can do” attitude – data governance is effectively all about change management at the enterprise level, which requires cultural change. People are often set in their ways, and we cannot influence behavioral change until we change minds – and change is never easy. Being surrounded by others in the same space provides a wealth of validation, learning opportunities and knowledge sharing – making these conferences highly valuable.
My key impressions were:
- Data is increasing faster than ever before in volume, velocity, variety – and veracity is tantamount.
- Without data governance, the data will manage us. With data governance, we can manage the data.
- Your organization needs to succeed and grow, and information workers will do what they need to run or improve the business – even if that means a lot of manual and semi-manual processing or data silos/islands.
- Those legacy behaviors and mindsets are neither sustainable nor scalable, and they create excess variation and cost. Data governance is the core enterprise strategy that helps resolve those challenges.
- Information Architecture is KEY. Without a solid IA strategy and plan, data governance efforts will be much harder and could even be compromised. Work with all your enterprise architects to coordinate and streamline IA efforts across the enterprise.
- The push for digital transformation and automation will exacerbate your data challenges if you don’t establish formal roles, responsibilities and processes for enterprise-wide data management.
- Regulatory oversight for data security and privacy will only grow. New standards like GDPR and CCPA will require more modern, mature and manageable data governance keeps pace with those requirements.
- Data literacy seems to be growing into one of our most pressing organizational challenges. How do we teach employees and leadership to recognize good vs. bad data? How do we help them learn how to use tools and processes to understand how data is sourced, what it means, how good it is, and how it should be used? How do we drive consistency and trust across the enterprise? These skills must become commonplace in the Digital Age.
Ultimately, analytics and reporting (and the multitude of insights, decisions and actions that arise from them) all demand good data as basic building blocks. “Good” starts upstream at the point of entry or recording in our transaction systems and must flow through all downstream paths to the point of consumption. It’s as simple as the tagline, “Garbage in, garbage out.” With good building blocks, data consistency increases and data variation decreases so we can scale faster and better – making automation through AI/ML and other forms of advanced analytics and data science better positioned for success. With bad building blocks, we won’t get the better answers or decisions we expect – we’ll just get bad answers or decisions, faster.
Organizations have tackled these and related challenges with formal approaches for managing other enterprise assets like employees (HR), money (Finance & Accounting), supplies (Supply Chain Management), computer equipment & technology (IT), buildings & vehicles (Facilities Management), and more. When we manage data as a true enterprise asset with formal roles & responsibilities, processes, tools and outputs, data literacy may become as commonplace as those of these other assets. Data governance is gaining traction as a formal enterprise function, with a growing presence at the CxO table in the form of Chief Data Officers and Chief Analytics Officers. As data governance matures, I expect to see more algorithms and standards for calculating the value of data assets (often referred to as “infonomics”) and eventually even the inclusion of data assets on company balance sheets.
I’d like to send a huge thanks to DebTech International, the supportive sponsors, the dedicated hotel employees, and all the speakers and attendees for helping make DGW 2019 a resounding success! I will close with the same final thought I always have – data governance is a journey, and the only way to fail is to quit … so never, EVER give up!
