Data Management – The 4th Wave of Outsourcing


The latest evolution of asset management outsourcing is here: A new solution to the age-old problem of data management. These offerings bring a new class of service to front-to-back offerings and are raising the bar; the service provider will assume accountability and must get it right.

You’re not alone if you’re struggling with data. The vast amount of data needed by investment managers is often overwhelming to efficiently collect, manage, and distribute for consumption. From sourcing and aggregating data from multiple suppliers, to aligning resources to fully control and govern the data, to optimizing an infrastructure to fully utilize the data…there are many complexities to navigate. If not well-managed, data problems can compound and lead to inaccuracy, latency, and difficulty getting data to the consumers.

The Data Problem in Operational Outsourcing

The primary culprit responsible for the failure of several high-profile outsourcing deals over the past years has been the four-letter word: Data.

While service providers have been challenged to scale and digitize their infrastructure, asset managers often underestimated the importance of coupling an outsourcing engagement with a detailed review of their internal data strategy. As a result, the due diligence for these programs focused primarily on the functional capabilities and, at best, the quality of data delivered from the service provider. Rarely was the complete data journey validated, to confirm how this data would be consumed by the intended recipients to achieve the expected benefits of transformation.

Consequently, this often caused “data left at the doorstep” — where the required data is received, but not leverageable. This data conundrum is borne from a data strategy that lacks discipline within the asset manager’s walls, resulting in inconsistent or erroneous usage of data across the organization. When these scenarios are not addressed as part of outsourcing due diligence, legacy practices involving user-developed tools with random sourcing methods (what we refer to as the underground data organization) will continue to persist and impede a manager’s ability to realize success.

Outsourced Data Management Offerings Emerge

Fast forward to the present: Service providers have made significant investments in adopting modern, cloud-based data infrastructures in an attempt to optimize their clients’ need for data. However, asset managers continue to struggle with wrangling their data and remain challenged by the cost and complexity to rationalize overwhelming webs of interfaces and data solutions. The confluence of these factors has resulted in the emergence of what we see as the 4th wave of outsourcing – full-service data management.

The objective of these offerings is to address the data challenge head-on, from the moment a client’s target operating model is designed. Rather than two disparate entities optimizing data within their own walls, this emerging approach enables service providers to partner with their clients and maximize the full data journey of the investment lifecycle from sourcing through end consumption.

These platforms employ data fabric frameworks, which enable consistent capabilities for distributed and diverse data sets, and unify data management to provide improved control of data. These frameworks include data access solutions that enable faster and more powerful queries to be applied to the data, enabling asset managers to delve into data science and advanced data analytics to glean valuable insights.

The key to this model’s success, though, is that the investment made in improved data quality, timing, and access mustn’t be lost due to an asset manager’s inefficient or fractured operating environment or an obsolete data strategy.

Key Considerations

For clients of these platforms, it will be of paramount importance to be able to fully realize the benefits of the platform and get the data into the hands of the intended users. Since these data platform offerings are still somewhat nascent, your mileage may vary depending on your specific needs and which provider you select. There are some key considerations for evaluating a data platform service in order to ultimately select your optimal partner.

Data Quality – Examine how data integrity and timeliness is controlled, and how quickly data can be validated for accuracy and made available for consumption. Additionally, the platform should analyze patterns in the data to spot issues like slow, inaccurate, or otherwise problematic data suppliers.

Data Governance – When considering the data platform solutions, it’s important to understand how your data governance objectives will be met across organizational boundaries. You’ll also need to consider if this type of offering will benefit or hinder an optimal data culture within your firm.

Capabilities – Not all providers currently accommodate unstructured or client-supplied data. Furthermore, for supported data domains, a provider may not yet have active clients utilizing all of them. And on the data integration side, there are varying tools offered across providers for data accessibility. Ultimately it is important to understand what features are available today vs. a placeholder on a roadmap.

Drawing the Line – As part of due diligence, it’s important to get clarity around the line of responsibility of data management services between you and the outsourcing partner. What does a shared data stewardship function look like for this partnership? What should the joint data architecture look like?

Separation – It’s prudent to plan ahead for a future separation with the outsourcing partner, and think about what this means for your data residing in their platform. Maybe you’ll choose to insure your firm against this concern by retaining copies of your data in your own lake or data warehouse. But if so, does this reduce the value of subscribing to a data platform solution in the first place?

As this new wave of outsourcing is still growing, success stories and lessons learned are limited, so asset managers will need to move forward with eyes wide open and carefully assess these areas and other aspects of data platform offerings.

Olmstead is uniquely positioned as a pioneer of the data-centric consulting approach to help guide you through your journey of assessing whether a data management outsourcing partner is right for your firm. Reach out today for a discussion.

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