Are you ready to support IBOR?

Rob Erman, Managing Director, Head of Global Professional Services, Eagle Investment Systems

There has been a lot of press surrounding IBOR and as my colleague Marc Firenze mentioned in his article in Wall Street and Technology, achieving an accurate and consistent IBOR can prove elusive for some investment management firms. Assuming that they get past the daunting task of defining what IBOR means to them, they need an actionable plan to implement that solution. In our experience, the implementation can be achieved by holding key constituents accountable and monitoring their readiness. Since quality data is the foundation for these types of initiatives, we have developed a data-driven readiness assessment based on six key pillars.

pillarsTo be successful, defining the acceptance criteria for each pillar requires collaboration between all of the interested parties including the software vendor, the client and their third-party industry consultants.

Each pillar is intended to illuminate a key aspect needed to achieve a successful outcome and to isolate areas that have historically had negative consequences on the success of the implementation.

  1. Data readiness. The first pillar, as my colleague Joel Kornblum addressed in his recent blog on our work with AIMCo, is having good quality data in place that supports your needs. Having a measureable way to understand your data and establish that it is ready is a key requirement. Often clients use an historical time period to reconcile the accuracy and completeness of data. While this approach appears to provide the validation that the data is ‘fit for purpose’, it exposes a risk that not every data scenario is represented in the sample data set. A preferred approach is to first construct an inclusive data set that attempts to cover all the specifications. This ensures a foundation for a detailed data dictionary and the basis for understanding when new data scenarios are introduced that do not align with the sample dataset.
  2. Application configuration readiness. The configuration of the application needs to be aligned with the business needs and desired outcomes. The application must be tested to ensure it is ‘fit for purpose’. While every implementation has unique requirements, it is important to make sure that wherever possible, the application configuration is adhering to the vendor best practices. We have found that installing and conducting a gap analysis to a “pre-configured baseline” implementation is an excellent way to validate that the system works for a specific use case and can be modified as needed.
  3. Customization readiness. Making sure that any customization, client-specific rules or code you need to transform or enhance is in place. Once you have done a thorough assesment and have validated the “return on effort” for a given customization, it is important to assess how ready the team is to support and make changes on a go-forward basis.
  4. Information consumption readiness. Once the system is configured, you need to make sure that your downstream uses of the data are supported and that the data is available for consumption. Data flows should be measured using a traceability matrix so data can be tracked right back through the data warehouse to the originator of the data. Within Eagle, we use a tool called Metadata Center to support the management of this data flow.
  5. Client readiness. Another key area is to make sure the organization is ready to use the technology. It’s the one pillar that exists outside of the technology itself and is one that’s often overlooked. It is crucial that the team has a defined playbook that ensures operational readiness of all participants. The playbook should provide insight on the following questions. Do you have the right data governance in place? Do you have the right organizational structures in place? Do you feel your team is ready to be self-sufficient and support the solution that’s been devised? While our goal is to automate as much as possible, it is likely that certain tasks and activities will need a level of human intervention and Service Level Agreement (“SLA”) associated with it.
  6. Technical readiness. You’re dealing with large, highly secure data; from a technical perspective, have you done a thorough security audit and performance evaluation to make sure it meets business needs? Technical readiness is not an afterthought. It requires representatives from other areas of the organization that have not been intimately involved with your project to date. To be most successful, engage them early in the process, make sure you pick the most appropriate time to engage them in the project and allocate meaningful time by your technical expert to make sure this critical step is given the appropriate “air-time.”

Developing a data-centric architecture is an organization-consuming initiative and getting individual supporting pillars in place can represent a significant investment of time and effort. Your software vendor and consultants can play a crucial role in helping you get the pillars in place and in developing measurable ways of assessing their readiness to ensure the solution is best placed for success when it’s implemented.

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