4 Common Data Problems Faced by Fund Marketers

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By Noel RodolfoFour problems with data faced by fund marketers

When talking with prospective clients, it’s not uncommon for us to hear, “Our data is a bit of a mess,” or “Our data could use a little housekeeping.”  In my experience working with some of the best fund marketing teams in the industry, I have learned that in many cases, marketers have become the de facto experts on fund data.

The reason is, in my opinion, because fund marketers themselves are routinely chasing-down their data from many disparate sources (both internal and external) and then trying to extract good clean data for use in their customer-facing marketing materials. To make the process even more challenging, it has to be done in a very tight time frame with the highest levels of accuracy and consistency.

This article will highlight a few of the more common data issues that fund marketers experience when preparing fund data for building factsheets, performance reports, and other marketing documents. Then we’ll discuss how fund data management systems can address each of these common data issues, as well as provide other benefits to investment marketing teams.

When loading data through an automated process (such as a document automation system), or even better through a dedicated fund data management system, certain validations and checks can be put in place to reduce and even eliminate many of these data issues. Here are four common data problems faced by fund marketers:

Problem #1: Data is Missing

Although sometimes we hear the term “static data” used in regard to fund data, fund data in general is anything but static.  Fund names change.  Fund-to-benchmark mappings change. New funds are launched while others are closed.  These events and others often cause issues in data sources and reports used by fund marketers for document production.   To the fund marketer that is preparing documents at quarter end, having data go missing and simply “popping off” of the data source is alarming and slows down document production.

When data is missing from a source file, in the best cases, it may get noticed by someone and a resolution cycle can begin.  In other cases, it may go unnoticed, causing problems in the documents.  In all cases, missing data is a source of frustration for the responsible fund marketers when their mind is on producing documents rather than QA’ing data.

How fund data automation solves it: When using a data automation  system to manage the fund data, the problem of missing data can be located and identified, and in many cases rectified before the fund marketer needs it for production.  Data automation systems can perform a number of validations or checks on the data as it is loaded.   For example, the system can be configured to look for expected patterns.  A simple example of this is to look for expected headings and values.  Also, the system can provide a notification when data appeared last month, but didn’t appear this month. And all of this is managed by the data source owner, and not the fund marketer!

Problem #2: The data is confusing

Unexpected or confusing data is another common issue, especially with files that are manually created or modified.  We’ve often seen data files come in with redundant data. For example, performance for a fund may come in twice or more in the same file!  When this happens, the performance numbers are sometimes different. So how do you know which one is valid?  Other times, the format of the data may differ, causing confusion and aggravation for the fund marketer.

How fund data automation solves it: Again in this case, a data automation system can be used to perform various checks and validations against the data.   For example a check may be put in to notify the data owner if a data point is provided more than once.  Similarly, if the source data format doesn’t match, a notification can be sent back to the owner for the appropriate resolution.

Problem #3: Data isn’t mapped correctly

Wrong Mapping is one of the most commonly faced data issues by fund marketers.  This is typically an issue when name changes occur, a fund launches or closes, benchmarks change, etc.  But honestly, this can happen at the strangest of times because data files rely heavily upon mapping.  And with so many disparate sources, there are many different mapping values for the same particular data item. For example, a fund may be referenced by its cusip, ticker, or internal identifiers. Switching between the different mapping values is cumbersome and problematic when doing this manually or even using Excel VLOOKUP and INDEX/MATCH functions.

How fund data automation solves it: With a data automation system in place, mapping values can be programmed and maintained easily. When mapping values don’t match, notifications go to the responsible parties prior to marketing involvement. In addition, when a  new mapping key appears for which a corresponding mapping value doesn’t exist, an “action required” notification is sent to the interested parties. This is a heavy burden lifted off of the marketing team.

Problem #4: Performance values don’t add up

Have you ever seen a pie chart with values that add up to over 100%? Trust us, this happens far too often and in many cases is simply dealt with by adding some disclosure text stating that funds may not add up to 100%.  Another example of bad data is a simple mis-placement of a decimal place.This happens more commonly in a manually created or modified source file, but it could also happen in a data file that underwent some coding or procedural changes.

How fund data automation solves it: Having a data validation check in place ensures that a specific data type is checked for summation tolerances. In the case of the misplaced decimal place, a tolerance +/- check can be put into place. For example, your data management provider can tell the system to flag any performance values that are +/- more than 25%. That may be a large enough swing in a single quarterly period to flag a potential mistake.

Infographic: How to get clean data for fund marketing.

Clean-Fund-Data-Infographic-2

Chasing down your data and then getting it in a clean format that is usable for marketing can be daunting, but is doesn’t have to be. With a feature-rich data management system in place,  you can save time and have confidence in your numbers across all your sales and marketing materials.

Thanks for reading!

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Noel is a Product Manager at Synthesis. He has an MBA from the University of Illinois at Chicago and over 15 years of experience in the software industry. In his free time, Noel likes to go camping, hiking, and fishing with his family.

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