2024 Planning – Key Distribution Intelligence Considerations


Olmstead recently conducted a study on the state of Distribution Intelligence (DI) across asset managers.  A key takeaway:  while DI has established itself as a mainstream function, ROI is largely anecdotal, and the best-in-class only recently, after significant investments (in data, tools, and talent), have positioned themselves to increase sales adoption and impact.

This study resulted in the creation of Olmstead’s DI Impact Model, which highlights data and cultural enablers.  In an industry that wants to flip the ratio of time spent data wrangling versus analysis, it’s no surprise having trusted and accessible internal and external data is a key to success.  The model also recognizes the importance of the cultural side to adoption.

As you iterate through 2024 planning and make the case for DI investments, consider the following enablers and whether your organization, like best-in-class DI functions, has embraced both the hard and the soft side of DI. How does your organization score on these key enablers? 

Olmstead DI Impact Model

Data-Centric Enablers:  

  1. Aggregated Data – Integration of and access to all internal and external data sets relevant to DI
  2. Data Governance – Data stewards/owners are empowered, data validations are automated, and trust in data is high 
  3. Self-Service – Significant leverage of BI tools by client-facing sales personnel for research and analysis 

Culture-Centric Enablers:  

  1. Executive Champions – Data-influenced selling model is articulated by leadership, funded, and incentivized 
  2. Seat-at-the-Table – DI has a voice along with Sales, Marketing, and Product regarding market strategies and tactics   
  3. Internal Engagement – There is a high degree of collaboration and exploration between DI and Sales

The asset management industry clearly believes in the promise of DI, particularly given the pandemic-induced acceleration of digital selling, and has seen success in more sophisticated lead generation and market segmentation models.  After significant investments in data and analytics talent, external data sources, distribution data warehouses, BI tools, and emerging successes with sales early adopters, the industry appears to be on the cusp of truly moving the needle with its DI practices.  And those who appreciate that it is both a technical and an organizational transformation will have the most success. 

We welcome the opportunity to share more details on our DI Impact Model and benchmarking.   

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