Whenever I am doing a presales demonstration or training for Microsoft Dynamics NAV, I ask the question to participants, “What is a Dimension?”.
Sometimes people will answer with “A cube.” or “A reporting category.” but more often than not most people look at me blankly. Microsoft describes dimensions as
A dimension is data that you can add to an entry as a kind of marker so that the program can group entries with similar characteristics and easily retrieve these groups for analysis purposes.
Let’s simplify this by describing a Dimension in NAV as a tag that I can attach to any entry that I post to my ledgers. I can then analyse these tags by grouping them together or looking at each separately across my ledgers at a later stage. The benefits of dimensions mean that I can minimise the number of accounts in my Ledger as I do not need to have several different accounts per dimension, e.g. I can have one Stationery G/L Account that operates across a range of Departments. Each department (e.g. Sales, Manufacturing, Head Office, etc.) would be a separate dimension value attached to the Department dimension.
Still not clear? Don’t worry, you are not alone. Let’s step away from Ledgers and Departments and the familiarity that people often get caught up in and hence get confused by when trying to grasp the concept of dimensions. This is an analogy I often use to help people understand the concept of dimensions and I hope it will help you…
Imagine yourself at the butchers counter on a busy day. Now imagine that this is Pension day so there are several little old ladies lined up waiting to buy their meat from a very fraught looking butcher. They are all holding their tickets to be served in a particular order. You take your ticket from the ticket machine and stand in line behind the old ladies.
As you stand there you start to notice some characteristics about all of these old ladies. Some of them are holding walking sticks, some have look grumpy, some happy and some are dressed in pink while others are in purple attire. You also notice that most are buying beef mince or bacon. The butcher is keeping records of each sale for different meat types separately.
Now let’s apply what you have noticed about this particular set of biddies to Dimensions…
First we have the numbered tickets which denote the order in which they were served. Let’s apply this to the Posting Date of a transaction. This is not a dimension but does allow us to filter results in the ledger by a particular date.
We then have the type of meat they were purchasing – Beef mince or Bacon. Let’s apply this to the G/L Account which will be affected by the transaction. Once again this is not a dimension but rather the top level analysis of the G/L Account. We can analyse each account separately or as a group of accounts across a selection of dimensions.
Now let’s look at the characteristics of this group of ladies. These form the Dimensions and Dimensions Values. We can define the Dimensions for them as:
- Walking Sticks
The Dimension Values would fit under the different Dimensions.
Walking Sticks Dimension would contain values for the type of wood and colour of the walking stick. E.g.
- Light Ash
- Dark Oak
- Light Oak
The Mood Dimension would contain values about the type of mood each old lady was in. E.g.
The Attire Dimension would contain Values for the colour of their clothing. E.g.
Lucky for us our butcher knows his clients very well and knows that Mrs. Green is a generally cranky lady that likes to wear pink and orders bacon every time.
If we had to analyse the transaction in NAV Financial terms for Mrs Green, we would see that there is a transaction in the ledger for an amount of money processed against a sale to the G/L Account for Bacon on a particular date (don’t forget the tickets), with Dimension Entries present for Mood equal to Grumpy and Attire equal to Pink. She does not have a Walking Stick and this dimension would therefore be blank.
The butcher also served Granny Smith. She is a lovely natured lady who also has a love of the colour pink and is always very happy. The butcher thinks she may fancy him a bit. She purchases a pound of beef mince every week.
If we had to analyse the transaction in NAV Financial terms for Granny Smith, we would see that there is a transaction in the ledger for an amount of money processed against a sale to the G/L Account for Beef Mince on a particular date, with Dimension Entries present for Mood equal to Happy and Attire equal to Pink. She does not have a Walking Stick and this dimension would therefore be blank.
If we wanted to know the value of all transactions across our ledger for the sales to all clients wearing pink vs. those wearing purple to check market research that people wearing pink will spend more money than those that wear other colours, we could choose to run a report to analyse all entries with the Dimension tag of ATTIRE and filter this by the Dimension Value of PINK. This would show us the total amount of postings to the ledger across a period of time by Dimension. We would see entries for both Mrs Green and for Granny Smith.
Now that you (hopefully) understand the concept of Dimensions, try to think about the dimensions in your company. Remember that NAV allows you as many Dimensions and supporting Dimension Values as you want, however, you can only view 8 dimension columns for each transaction as standard. The 8 dimensions are defined in the General Ledger Setup. Over the next few weeks I will be taking you through the following topics:
- Global vs. Shortcut Dimensions and Setups. I will cover the difference between Global and Shortcut Dimensions, how they are used and where to set them up.
- Default Dimensions and Dimension Combinations. I will cover the different rules applicable to ensure that users post dimensions correctly.
- Dimensional Reporting. I will cover the different ways in which we can analyse data posted using Analysis by Dimensions Reports and other tools such as G/L Dimension Overview.
I will conclude this post with a warning: Dimensions should be used to analyse the data posted to your ledgers and not to build that data. A dimension that is the same as Master Data (e.g. Items) in your system means that you are using Dimensions to build up analysis data and you should perhaps take a step back and look at the reasons for doing this and your other options for setups before using dimensions and may slow your system down when doing analysis.