Complex investment strategies, recessionary economic dynamics, increasingly demanding clients and ever-changing regulations put increased stress on the capabilities of existing Enterprise Data Management (EDM) platforms and the Data Operations teams that run them. What was simply the daily burden of sourcing, cleaning, and reconciling data centrally has now become a severe business inhibitor and carries a cost that most organizations do not wish to pay.
Buy Side firms need an agile model that adapts to their growth journeys and evolved investment strategies enabling key resources to instead focus on truly value-added tasks like engaging on new and complex topics such as ESG, climate, cryptocurrencies, private debt and the myriad other investment opportunities that are becoming increasingly mainstream requirements.
Switching between these markets and increasing investments in ESG and/or alternatives should not require lengthy reviews nor be so challenging from a resource point of view. Retooling and retesting prevents the business from hitting the ground running. Canny business strategies will only get you so far without a deep re-evaluation of your data operating model and how it can be made to adapt at speed.
So how does a company approach these challenges?
Many companies have been burnt by prior experiences with EDM providers and are looking for new and innovative ways to tackle these tasks. Some companies have reached the stage where they simply want to outsource their data operations to a service provider, while others remain far more hands on and have decided to retain control. They might be seriously considering upgrades and/or replacements of existing platforms.
But how do you decide which path to take? Will your newly-deployed EDM solution really meet your requirements or are you starting down a multi-year project only to decide that you should have migrated to a fully managed service model? Maybe the step to fully managed services feels too big a leap for the organization’s current structure?
The ideal operating model would appear to be one that provides a cloud-based SaaS core that can be rapidly configured to support all your current and likely business requirements. The organization providing this platform should be able to provide operational services that can manage as much or as little of the operational burden as your organization requires, and change as your company develops.
As your organization grows you should be able to opt to receive deep support from senior advisors to enable rapid configuration of new data types when needed, while ensuring that day-to-day data quality thresholds are always met. This, coupled with robust and timely change management, will for the first time provide business users of such capability with the agility to realize commercial objectives.
In our next article in this series, we’ll look at what you need to consider when re-evaluating your data operating model, and examine some best methodologies, solutions, platforms, and services that companies might investigate when looking to refresh their data management capabilities.