Research shows that capital markets firms are planning to move away from building and towards buying data management platforms at a rate four times higher than the average for other technologies[1]. This momentum is being driven by firms outsourcing commoditised data initiatives so that they can instead focus on projects that build competitive advantage. This was one of the main discussion points during a recent webinar we hosted with CEB TowerGroup on the topic. As the trend grows, we asked the question: what does best look like for your firm?

Initially it comes down to determining exactly what you are trying to achieve; what is your overall objective? Is it operational agility, reduction of operational risk or alleviating budget pressures? Setting these objectives upfront ensures any outsourcing project is aligned to strategic business initiatives and the overall data management programme.

Next, consider the different managed services models available. From straight-forward hosting through to a fully managed service or even business process outsourcing, you need to know which model best suits your objectives. Also be clear on who owns what. In a fully managed service, it’s necessary to define the unbiased fiduciary on mission critical enterprise data – is it the provider or you?

Then determine what data domains you need to solve for. Remember, not all data is created equal. Appetite for outsourcing different data domains will vary. Data such as reference data is fairly commoditised and is often selected for outsourcing. Other domains, such as investment data which includes positions, transactions and fund performance, may be viewed as more proprietary and sensitive but should still be considered as part of your managed service strategy. It’s worth remembering that the more data domains you combine, the more value you derive from understanding the relationship between interrelated data.

Finally, we come to what best looks like for your firm. Managed service models are made up of a number of different components: infrastructure, applications, change and data management. With each component, there is an implied value continuum from infrastructure (low value) through to data (high value). If you want to quickly set up a new test environment, then it’s just a matter of outsourcing the infrastructure. If you’re looking to identify data optimisation opportunities, then your managed services provider will have responsibility for the actual data.

Whether you start with managing infrastructure or jump straight to managing data, one of the most important considerations is flexibility. As regulations, your business environment and executive direction evolve, you’ll need to ensure that whichever model you adopt, it can easily respond to change.

[1] CEB TowerGroup, Not all data is created equal, April 2016