Data leaders are challenged to find the right balance between long-term thinking and short-term outcomes when defining their governance strategies. John Yelle, DTCC Executive Director, Enterprise Data Management (EDM), recently joined other data leaders at the CDO
& Data Leaders’ Global Summit 2022, for a panel discussion on ways to successfully manage this balance and establish foundational data governance frameworks that create sustainable “defensive” and “offensive” outcomes for their firms.
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Yelle met with DTCC Connection to share his insights on DTCC’s data governance journey and discuss how firms can not only establish the framework, but also the mechanics of improving data culture for your organization.
DC: What have been the key trends that have forced you to rethink data governance?
JY: In the years following the financial crisis, the industry and regulators made data governance a priority, and the industry has invested a lot of time and money on increasing data transparency. But we learned very quickly that there are several
things we, as an industry, need to improve upon in how we manage data before we can get to the point where decision makers have full confidence the data, they have access to is fit for all purposes.
As the financial services industry continues to transform and modernize solutions and processes, that opens the door to a fantastic opportunity to apply data management and governance practices in a proactive and foundational manner.
DC: Walk us through the "before" state of data management at DTCC when it embarked on the data governance journey? More specifically, what were some of the aspects of our people, process and technology that you felt were most critical to change?
JY: We had some level of data governance, but data was very much managed in silos and driven by technical solutions and process. Data silos can be problematic and lead to redundant data being maintained in different silos or duplicative processes.
Before we could address processes, we had to make sure that we had the right people lined up to take on responsibilities (new operating model, etc.). We installed a Data Stewardship Model where data stewards are the first line of accountability and responsibility for data quality.
With the right people in place, we then retooled the operating model to make sure it can evolve as data evolves. Having the best people in place does not matter if you don’t have the right system. You must have the right resources in place and appropriate tools and technology budgets to make sure it is successful.
DC: What goals were set for DTCC after assessing the current state?
JY: Before you can establish goals, you must set expectations about an enterprise data management program and how you are going to manage those expectations. We established our first data governance roadmap from 2017-2019 for our SIFMUs. Then we expanded our data governance roadmap (2020-2022) to include the entire suite of DTCC businesses and subsidiaries. We listened to the internal business teams and applied defined practices, which support their priorities.
Each roadmap was equipped with a set of goals, which included establishing objective measures of the maturity of our data capabilities and plans to increase maturities where required to enable strategic business initiatives.
DC: What has been your strategy for accomplishing those goals?
JY: Our EDM strategy is a living document, constantly being updated and revised. Back in early 2020, we began work with our SIFMU and Solutions businesses on a unified data strategy. We looked at business priorities and objectives from a data capability point of view with the understanding that things evolve and shift and the enterprise data management program also has to shift to stay in step.
A key component of our work was around organizing data. It is a matter of consistency. Each business does their best to be consistent and adhere to the best data management practices, but there will be times when they manage data differently. When that happens, business decisions made to propagate silos must be transparent because you could create data debt – which is redundant content managed via duplicative processes and systems. An important aspect of the unified data strategy was to consider metadata as a category of data on par with transactional data, master data and analytical data. Proactive management of metadata is how transparency is achieved.
DC: What tactics have you found most useful for demonstrating value to your leadership and colleagues along the journey?
JY: There are a couple of ways to create value among your key internal stakeholders. The best way, without question, is to tie it to revenue. If we do this with the data, we’ll help to generate revenue. For external stakeholders, such as clients, demonstrating value through risk mitigation and efficiency will go a long way. Speaking of clients, the client experience is worth calling out, too. If you look at how we support and communicate with clients, there is an immense opportunity to make it frictionless. One way you improve that is to make sure you have data about who the client is and what services they use. When a client runs into issues, we need to get to the root cause quickly. If we have comprehensive, reliable data about the client in an easy-to-use, accessible format, it will be easier to resolve or potentially avoid a client’s pain points.
DC: What do you believe will be most important to ensuring that your data culture continues to evolve in a positive way?
JY: It starts with a culture change. For some reason data teams are not good at celebrating success – and I know because I’m a data person! The challenge is acknowledging “data wins” because data governance and managing data is a job where, if you do your job well, you’re not necessarily noticed.
It’s okay to celebrate success to drive that culture change. We must let folks know what we have done, and we want to collaborate with you to help support your needs.
DC: Lastly, what advice do you have for our audience as they prepare for their own journey?
JY: Don’t boil the ocean. You must have a way to set priorities around increasing the maturity of data capabilities that enable business success through measurable revenue increase, cost reduction or risk reduction and then clearly define the project scope and proactively manage delivery. Which aspects of data management you prioritize depends on several factors, such as the project goal and project timeline, among others. Be thoughtful about it and gain the support of the business and corporate strategy teams. We’ve learned through experience that when you rush ahead without broad alignment, you may end up smacking into a wall.