Request a Consultation

CheckPoint Consulting Blog

Welcome back! In Part I of this series, member mappings and the mapping process in FDMEE were explained. Now that a brief introduction has been given, we will go continue on identifying the reasoning behind having a large volume of maps.

In the many applications that I have come across, I have seen a number of different ways a company controls their maps. No matter how location maps are controlled, whether by an overlooking admin or a power user assigned to individual location maps, it all goes back to how the mappings are reviewed and maintained. Without guidelines and proper care, a dimension’s mappings can steadily grow through each month’s close to a point where maintenance eventually becomes terribly difficult.

Maintaining a dimension’s mappings brings about several questions - “what type of mapping format is best to use?”; “why is there an increase in explicit mappings for one location as opposed to another?”; “how do I utilize my maps in the most efficient way possible?” Well, the answer is not that simple. Many of the factors that go into creating maps depend on the location and centralization of accounting itself. There is no specific type or right number of mappings as long as there is some kind of standardization and governance in the mapping design so you don’t see mappings increase and decrease by the thousands each month for a single location. Not everybody encounters such drastic changes in their mappings. If a location has experienced a drastic increase in explicit mappings over a period of time, then it is necessary to identify the reasoning for that and find a solution before a dimension for a location map grows to, let’s say, over 400,000 explicit mappings and almost 2000 implicit rules…yes, I have seen this. 

So, both a single location map, and a group of location maps contain a large volume of mappings and you have identified a reason. Let’s break this down further and identify other possible areas where the issue could be stemming from. Below I’ve created a cause-and-effect diagram outlining mapping volume.



An overabundance of mappings for a particular location or master location, depending on how data is loaded, can lead to a great deal of potential problems including incorrect import format strings, poor use of the import format fields, and long performance times in FDMEE to name a few. Coming up in Part III of this blog series, these causes are explained in greater detail.

Disclaimer:  This article is intended to be a resource only and is not intended to be nor does it constitute legal product advice. Any recommendations are based on our direct experience in this environment during the time in which this was posted.