Modernizing Data Architecture: Involving The Right Stakeholders at the Right Time
January 27, 2025
Read Time: 7 minutes
Inst'l Asset Managers
Rochelle GlazmanHead of Product Marketing
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With any digital transformation initiative, involving the right stakeholders at the right time can make or break the successful adoption of a new technology or process. Asset managers might run into this challenge as they seek to modernize their data architecture. Data touches every facet of the firm, internally and externally, making the active involvement of key stakeholders imperative for a successful data architecture modernization initiative. This blog post will delve into the importance of stakeholder involvement, the specific roles of different teams, and the key use cases that benefit stakeholders.
Five key stakeholders should be involved with upgrading data architecture projects, including front-, middle-, and back-office teams, senior leadership, and of course, the IT and data teams that help implement any new tools.
The face of the firm, front-office teams directly interact with clients and driving client value, offering invaluable insights into clients’ specific needs and expectations. For example, a front-office team might identify the need for real-time data analytics to provide clients with up-to-date investment performance reports. Some front-office teams are looking to adopt artificial intelligence (AI) and predictive analytics to optimize major functions. In fact, in a recent BNY study targeting 200 asset managers, nearly three out of four respondents (72%) listed front-office risk management as the top area to expand their data analytics and insights capabilities. By involving front-office teams, organizations are better positioned to design purpose-built data architecture that leads to better client service and satisfaction.
Middle-office teams are responsible for ensuring data accuracy and compliance. Their role is vital for maintaining regulatory standards and building trust with clients. For example, a middle-office team might highlight the need for robust data validation processes to minimize errors and meet compliance with financial regulations. Their input can help create a data architecture that meets stringent requirements, reducing the risk of non-compliance and associated penalties.
Back-office teams focus on streamlining processes and reducing operational risks. Their input ensures new data architecture supports efficient and reliable operations. As an example, a back-office team might propose automated reconciliation processes to reduce manual errors and improve operational efficiency, helping firms identify the specific back-office changes that will drive cost savings and improved reliability.
Leadership and decision-makers champion the investments needed for data architecture modernization, providing strategic direction and the financial backing required for transformation. For example, a CIO might use stakeholder insights to build a business case for the modernization project, highlighting the potential return on investment and long-term benefits.
IT and data teams provide the technical expertise necessary to verify the feasibility and seamless integration of the new data platform. Their input is essential for identifying potential technical challenges and solutions. An IT team might identify the need for a hybrid cloud solution to balance cost and performance, ensuring the new data architecture is both scalable and secure.
The lack of adoption from key stakeholders, which can stem from not involving them early enough in the process, can threaten successful digital transformation. Firms can benefit in three ways from bringing in the right stakeholders at the right time.
Early stakeholder engagement keeps data strategy initiatives in lockstep with the firm's unique business needs. By incorporating diverse perspectives and insights, the data architecture can be tailored to meet specific business objectives. For example, a stakeholder from the front office might recommend a more user-friendly data dashboard to improve client interactions. This alignment helps in creating a more effective and practical solution.
Stakeholder input helps identify specific challenges and opportunities, leading to more innovative and practical solutions. A compliance officer advocating for enhanced data security features to meet new regulatory requirements can help identify ways to overcome potential obstacles and capitalize on new opportunities using purpose-built technology.
Involving stakeholders early in the process fosters buy-in and support, reducing resistance, ensuring a smoother implementation and long-term use of new processes or tools. For example, the middle office might be dealing with complex fund structures and slower deal execution as part of a new private markets investment strategy. Making sure these specialized requirements and different valuation schedules are accommodated can lead to a more successful and sustainable data architecture modernization efforts.
Modernizing data architecture can facilitate the launch of new financial products and services, helping to drive revenue growth and improve business agility. For example, a new data platform might enable the rapid development and deployment of personalized investment solutions, allowing the firm to stay ahead of the competition. Stakeholder involvement can help identify the specific data requirements and functionalities needed for these new products.
A modern data architecture can help meet stringent regulatory requirements, thereby mitigating and minimizing risks. Data architecture that supports real-time reporting and audit trails can help the firm comply with new financial regulations, for example. Stakeholder input can help in designing a data architecture that is both compliant and efficient.
Major industry transitions, such as T+1, ESG reporting, AI adoption, or cloud migration, require a well-designed data architecture for effective planning and execution. For example, a stakeholder from the ESG team might provide insights on the need for a data architecture that can handle complex ESG data and generate comprehensive reports. By involving stakeholders, the firm can verify that the data architecture is robust and adaptable to these transitions.
Stakeholder involvement can help build or support an ecosystem of technology and vendors, ensuring that the data architecture is robust and adaptable. For instance, a stakeholder from the IT team might identify the need for a data architecture that can integrate with multiple third-party systems and services. This collaboration can lead to a more integrated and efficient technology ecosystem.
Stakeholder involvement is crucial in justifying the financial and resource investments required for data architecture modernization. By providing insights that align the data strategy with the firm's business needs, stakeholders can make a stronger case for the required investments. For example, a business analyst might use stakeholder feedback to create a detailed cost-benefit analysis, demonstrating the potential return on investment and long-term benefits.
Stakeholder input helps with managing legacy systems by identifying potential integration challenges and solutions. A stakeholder from the IT team might highlight the need for a phased migration approach to minimize disruption and ensure a smooth transition, ensuring a comprehensive and effective plan for managing legacy systems.
Stakeholder involvement can also enhance operational efficiency by streamlining processes and reducing costs. For example, a stakeholder from the operations team might identify the need for automated workflows to reduce manual tasks and improve accuracy.
The success of data architecture modernization heavily depends on the active involvement of key stakeholders. From aligning with business needs and identifying challenges to justifying investments and managing legacy systems, stakeholder engagement plays a vital role in every step of the process. By listening to key stakeholders and fostering collaboration and buy-in, firms can ensure that their data architecture is robust, efficient, and will help them achieve their strategic goals. Get more in-depth insights and practical tips on data architecture modernization in this webinar.
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