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

• Will service providers realize the same level of success when extending their data capabilities to clients?
• Where will the lines be drawn between the provider and the manager, what infrastructure needs to stay behind?

Only time will tell the answer to these questions, but while this evolving service model seems poised for success in solving the “data left at the doorstep” dilemma, the devil lies in the details of execution.

The Data Problem

The primary culprit responsible for the failure of several leading industry 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 strategies. 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 did they validate the complete data journey and confirm how this data would be “consumed by” the intended recipients to achieve the expected benefits of transformation.

Consequently, this often caused what we refer to as “data left at the doorstep” – imagine a clean pipe of data that flows into the abyss. This elusive data conundrum is born from a data strategy that lacks discipline within the asset manager’s walls, resulting in inconsistent or erroneous sourcing of data across the organization. When these scenarios are not addressed as part of an 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.

Data Management Offerings Emerge

Fast forward to the present, the service providers have made significant investments in adopting modern, cloud-based data infrastructures, in an attempt to optimize their operating models. However, asset managers continue to struggle with taming the data beast and remain challenged by the cost and complexity to rationalize their overwhelming web of interfaces and data solutions. The confluence of these factors has resulted in the emergence of what we see as the 4^th 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 walls – this emerging approach will enable service providers to partner with their clients and maximize the full data journey of the investment lifecycle from sourcing through end consumption.

The intended result of this model is to ensure that the significant investments in improved data quality and timing are not lost due to an asset manager’s inefficient or fractured data environment. Optionality within these offerings are varied with stand-alone component solutions; the ability to serve as your data steward; augment your existing data model, or enable you to fully leverage your provider’s state-of-the-art data infrastructure.

Key Considerations

Since these offerings are quite new, your ability to leverage data may vary depending on your specific needs and which provider you select, some key considerations are:

Data Quality – Examine how data integrity and timeliness is controlled. 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 these solutions, it will be 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.

Breadth and Flexibility – Not all providers can accommodate unstructured or client-supplied data. Additionally, some offer data marts, services, and BI tools to enable the usage of the data. Ultimately it is important to understand what features are available today vs. a placeholder on a roadmap.

As this new wave of outsourcing is still nascent, 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 this new service offering.

Contact us:

Michael DiScipio

discipio@olmst.com

Olmstead is a consultancy focused on guiding Asset Managers through operational and data transformation