In the wake of the COVID-19 pandemic, the asset management industry experienced a seismic shift. Firms were forced to discard traditional sales methods like door-to-door visits and golf outings, compelling sales teams to reinvent themselves through data mining and advanced analytics. The pandemic pushed organizations to expedite their enterprise digital evolution, previously only explored in limited capacities.
These transformations unveiled a harsh reality: outdated data management practices, particularly for Client, Account, and Product data. This data often proved incomplete and unreliable, forcing end-users into inefficient data steward roles, tasked with manually cleaning and creating reports simply to keep up with competitors. Organizations grappling with these challenges will have no choice but to embark on a data management transformation.
Client, Account, and Product Data is Enterprise Data
Consider this: Your Client, Account, and Product data is a unique data asset, sculpted entirely by your organization. Yet, it’s subject to interpretation and opinion, resulting in erratic reporting and utilization. Firms grapple with multiple definitions to the same data created and manipulated by various internal departments. These uncoordinated efforts lead to inconsistent answers to customer queries, external database submissions, and stress internal operational processes. Ultimately, unifying your approach to profiling client, account, and product data is challenging, and if done poorly, results in lost opportunities and diminished business growth. Firms must recognize that client data is not just reference data, but rather enterprise data with use across the organization.
To tackle this, you must craft a data strategy that not only fosters a data-driven culture but also outlines the people, processes, and technology required for enhanced data governance, data quality, trust, and end-user empowerment. Data governance is ultimately the key to improving the data quality of client, account, and product data. Ensuring the organization identifies and empowers people to play key roles in the definition, management, and issue resolution of the data will inevitably improve the quality of the data. People and process should drive the data strategy in support of these customer-focused data domains.
Master Data Management
Enter Master Data Management for Client, Account, and Product data – the secret to being effective. Master data management generates a golden source of data that’s consistent, accessible to all, and governed by standard language and definitions, eliminating uncertainty for end-users. This data is critical for many functions including enterprise reporting, sales analytics, and RFP/RFI/DDQ content. Ensuring your MDM data model accounts for a symbiotic view across the data domains will maximize end-users’ capabilities. Your organization must decide how Client, Account, and Product data is connected to allow for advanced data analysis responding to increasingly complex business questions.
Master data management is more than plugging in a technology tool to create a “golden copy” data set. Master data management is data governance in action. So much about client, account, and product data is defined by operational workflows. Leveraging a Data Governance Framework will guide the organization in identifying the internal and external data sources (inclusive of people) that input into the golden record. Workflow enables the identification and promotion of only the most relevant and valuable data resulting in the golden copy.
The Data Governance program also empowers data owners and data stewards to be accountable for data quality. Data owners and data stewards will understand the data best. They will be able to construct business and data quality rules to identify data issues during the golden copy manufacturing process. Data stewards can adjudicate the issues well ahead of end-users’ consumption.
Master data management tooling is an important component to ensuring data quality. The MDM solution should enable the business processes to flow seamlessly, allowing data stewards to manage the data manufacturing process. Done right, this will improve enterprise operational efficiency, client satisfaction, and growth.
Conclusion
In the post-pandemic era, the question isn’t whether to transform your data practices; it’s how fast you can adapt to thrive in the new data-driven landscape. It is survival of the fittest in the data-driven world.
Olmstead has extensive experience in assisting firms framing data strategies as well as implementing Master Data Management solutions supporting Client, Account and Product data. Reach out today to discuss how we can assist with the evolution of your firm’s master data management practices.