Beyond Factsheet Automation: Solving the Data Paradox

Factsheets are an integral part of any asset manager’s sales and market efforts. An asset manager may be producing anywhere from a few dozen factsheets to several thousand in a quarter. Asset managers also have to ensure that their factsheets cover multiple language, geographies, and share classes.

Most asset managers have implemented some form of factsheet automation solution, but manual data processes they rely on undermines the efficacy of the overall factsheet production. This can lead to: 

  • Error-filled factsheet production
  • Time and effort spent in rectifying errors
  • Data inaccuracies leading to client escalations
  • Increased time to market for sales teams

Factsheet automations are only successful if they are supported by robust data processes. Automated data feeds and validations are able to streamline the process for data sourcing and processing, while also ensuring the accuracy of factsheets and other marketing collateral at the same time. A robust automated factsheet production process is made-up of three components: data, production, and review with automated checks and reviews throughout the process.

The data component focuses on the automation of sourcing and processing relevant data. In order to combat the possible data inaccuracies and the production issues that can result from them, two layers of checks are applied to this first component. The Level 1 Check automates the review of raw data files and feeds for errors. Once these errors have been rectified and processed, the required factsheet data structures are created, and a Level 2 Check automates the validation process before the production component.  

The production component automates the generation of factsheets across multiple languages and share classes, which helps decrease the time to market for sales teams. This is then followed by the review component, which consists of a final Level 3 Check for final proof reading prior to finalizing the Factsheets.

A robust data process not only makes factsheet production more efficient and error-free, but it also has more wide-ranging implications on related business processes following similar data sets. RfP teams, consultant databases, product marketing, etc. all have similar data needs and data challenges that can be effectively resolved through a central data hub that automates the process from data sourcing, validation, and distribution. Some key benefits of a centralized data process include:

  • Improved bandwidth due to the elimination of redundant data requests across business functions, which helps teams spend less time on data sourcing. 
  • Elimination of data errors for all teams as a central function ensures errors are rectified at the source prior to distributing the data for downstream consumption. 
  • Efficient error resolution through clearly defined data ownership, ensuring that any follow-ups, error handling, and queries can be efficiently handled. 
  • Minimization of repetitive errors through a readily accessible central error and rectifications log to data users. 

Evalueserve’s proprietary system, Publishwise, provides a robust platform to automate all data processes and factsheet production needs. To learn how your final factsheets can achieve 100% accuracy, contact us for more information.

Mayank Sharma
Senior Practice Expert, Investment Management Posts

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